A Survey of Sound Source Localization Methods in Wireless Acoustic Sensor Networks
---
paper_title: Simultaneous Ranging and Self-Positioning in Unsynchronized Wireless Acoustic Sensor Networks

paper_content:

Automatic ranging and self-positioning is a very desirable property in wireless acoustic sensor networks, where nodes have at least one microphone and one loudspeaker. However, due to environmental noise, interference, and multipath effects, audio-based ranging is a challenging task. This paper presents a fast ranging and positioning strategy that makes use of the correlation properties of pseudonoise sequences for estimating simultaneously relative time-of-arrivals from multiple acoustic nodes. To this end, a proper test signal design adapted to the acoustic node transducers is proposed. In addition, a novel self-interference reduction method and a peak matching algorithm are introduced, allowing for increased accuracy in indoor environments. Synchronization issues are removed by following a BeepBeep strategy, providing range estimates that are converted to absolute node positions by means of multidimensional scaling. The proposed approach is evaluated both with simulated and real experiments under different acoustical conditions. The results using a real network of smartphones and laptops confirm the validity of the proposed approach, reaching an average ranging accuracy below 1 cm.
---
paper_title: A robust and low-complexity source localization algorithm for asynchronous distributed microphone networks

paper_content:

In this paper, we propose a robust and low-complexity acoustic source localization technique based on time differences of arrival (TDOA), which addresses the scenario of distributed sensor networks in 3D environments. Network nodes are assumed to be unsynchronized, i.e., TDOAs between microphones belonging to different nodes are not available. We begin with showing how to select feasible TDOAs for each sensor node, exploiting both geometrical considerations and a characterization of the overall generalized cross correlation (GCC) shape. We then show how to localize sources in the space-range reference frame, where TDOA measurements have a clear geometrical interpretation that can be fruitfully used in the scenario of unsynchronized sensors. In this framework, in fact, the source corresponds to the apex of a hypercone passing through points described by the sole microphone positions and TDOA measurements. The localization problem is therefore approached as a hypercone fitting problem. Finally, in order to improve the robustness of the estimate, we include an outlier detection procedure based on the evaluation of the hypercone fitting residuals. A refinement of source location estimate is then performed ignoring the contributions coming from outlier measurements. A set of simulations shows the performance of individual blocks of the system, with particular focus on the effect of TDOA selection on source localization and refinement steps. Experiments on real data validate the localization algorithm in an everyday scenario, proving that good accuracy can be obtained while saving computational cost in comparison with state-of-the-art techniques.
---
paper_title: Energy-Based Acoustic Source Localization Methods: A Survey

paper_content:

Energy-based source localization is an important problem in wireless sensor networks (WSNs), which has been studied actively in the literature. Numerous localization algorithms, e.g., maximum likelihood estimation (MLE) and nonlinear-least-squares (NLS) methods, have been reported. In the literature, there are relevant review papers for localization in WSNs, e.g., for distance-based localization. However, not much work related to energy-based source localization is covered in the existing review papers. Energy-based methods are proposed and specially designed for a WSN due to its limited sensor capabilities. This paper aims to give a comprehensive review of these different algorithms for energy-based single and multiple source localization problems, their merits and demerits and to point out possible future research directions.
---
paper_title: Closed-form solutions for robust acoustic sensor localization

paper_content:

This paper deals with the localization of acoustic sensors based on signals emitted by loudspeakers at known positions. In particular, a model for distortions in time-of-flight (TOF) estimates applicable to the sensor localization problem is presented along with closed-form solutions with low computational cost. The proposed techniques are able to approximate the sensor position even when the TOFs are corrupted by an unknown delay, there is a sampling frequency mismatch between the A/D and D/A converters associated with sensor and loudspeakers, and the speed of sound is unknown. Simulations and an experiment on real data demonstrate that the proposed methods are able to estimate sensor positions with less than 2 cm of error in the evaluated scenarios.
---
paper_title: Acoustic Source Localization With Distributed Asynchronous Microphone Networks

paper_content:

We propose a method for localizing an acoustic source with distributed microphone networks. Time Differences of Arrival (TDOAs) of signals pertaining the same sensor are estimated through Generalized Cross-Correlation. After a TDOA filtering stage that discards measurements that are potentially unreliable, source localization is performed by minimizing a fourth-order polynomial that combines hyperbolic constraints from multiple sensors. The algorithm turns to exhibit a significantly lower computational cost compared with state-of-the-art techniques, while retaining an excellent localization accuracy in fairly reverberant conditions.
---
paper_title: On Energy-Based Acoustic Source Localization for Sensor Networks

paper_content:

In this paper, energy-based localization methods for source localization in sensor networks are examined. The focus is on least-squares-based approaches due to a good tradeoff between performance and complexity. A suite of methods are developed and compared. First, two previously proposed methods (quadratic elimination and one step) are shown to yield the same location estimate for a source. Next, it is shown that, as the errors which perturb the least-squares equations are nonidentically distributed, it is more appropriate to consider weighted least-squares methods, which are observed to yield significant performance gains over the unweighted methods. Finally, a new weighted direct least-squares formulation is presented and shown to outperform the previous methods with much less computational complexity. Unlike the quadratic elimination method, the weighted direct least-squares method is amenable to a correction technique which incorporates the dependence of unknown parameters leading to further performance gains. For a sufficiently large number of samples, simulations show that the weighted direct solution with correction (WDC) can be more accurate with significantly less computational complexity than the maximum-likelihood estimator and approaches Cramer-Rao bound (CRB). Furthermore, it is shown that WDC attains CRB for the case of a white source.
---
paper_title: Exact and Approximate Solutions of Source Localization Problems

paper_content:

We consider least squares (LS) approaches for locating a radiating source from range measurements (which we call R-LS) or from range-difference measurements (RD-LS) collected using an array of passive sensors. We also consider LS approaches based on squared range observations (SR-LS) and based on squared range-difference measurements (SRD-LS). Despite the fact that the resulting optimization problems are nonconvex, we provide exact solution procedures for efficiently computing the SR-LS and SRD-LS estimates. Numerical simulations suggest that the exact SR-LS and SRD-LS estimates outperform existing approximations of the SR-LS and SRD-LS solutions as well as approximations of the R-LS and RD-LS solutions which are based on a semidefinite relaxation.
---
paper_title: The generalized correlation method for estimation of time delay

paper_content:

A maximum likelihood (ML) estimator is developed for determining time delay between signals received at two spatially separated sensors in the presence of uncorrelated noise. This ML estimator can be realized as a pair of receiver prefilters followed by a cross correlator. The time argument at which the correlator achieves a maximum is the delay estimate. The ML estimator is compared with several other proposed processors of similar form. Under certain conditions the ML estimator is shown to be identical to one proposed by Hannan and Thomson [10] and MacDonald and Schultheiss [21]. Qualitatively, the role of the prefilters is to accentuate the signal passed to the correlator at frequencies for which the signal-to-noise (S/N) ratio is highest and, simultaneously, to suppress the noise power. The same type of prefiltering is provided by the generalized Eckart filter, which maximizes the S/N ratio of the correlator output. For low S/N ratio, the ML estimator is shown to be equivalent to Eckart prefiltering.
---
paper_title: Robust Acoustic Positioning for Safety Applications in Underground Mining

paper_content:

The surroundings of underground mining machines still constitute an unsafe area for miners due to bad visibility conditions. In this paper, we present a novel acoustic position estimation system for safety applications in such hazardous environments. Our system is based on a pulse compression technique and utilizes linear (LFM) and hyperbolic (HFM) frequency-modulated signals in the frequency range of 5–20 kHz. As the miners are moving, we incorporated a means of Doppler-shift compensation. This system not only provides the positions of moving targets but also their velocity and direction. In stationary measurements, we evaluated LFM signals at noisy conditions both in an indoor laboratory environment and in the vicinity of a mining machine. The movement of a miner has been emulated in dynamic laboratory measurements at constant speeds up to 1 m/s using both LFM and HFM signals. Our results show that the acoustic signal can be evaluated down to a low signal-to-noise ratio of −30 dB. The results of the dynamic measurements clearly demonstrate the insensitivity of the HFM signals to Doppler-shifts both with regard to the estimated position and estimated velocity.
---
paper_title: The Cricket location-support system

paper_content:

This paper presents the design, implementation, and evaluation of Cricket , a location-support system for in-building, mobile, location-dependent applications. It allows applications running on mobile and static nodes to learn their physical location by using listeners that hear and analyze information from beacons spread throughout the building. Cricket is the result of several design goals, including user privacy, decentralized administration, network heterogeneity, and low cost. Rather than explicitly tracking user location, Cricket helps devices learn where they are and lets them decide whom to advertise this information to; it does not rely on any centralized management or control and there is no explicit coordination between beacons; it provides information to devices regardless of their type of network connectivity; and each Cricket device is made from off-the-shelf components and costs less than U.S. $10. We describe the randomized algorithm used by beacons to transmit information, the use of concurrent radio and ultrasonic signals to infer distance, the listener inference algorithms to overcome multipath and interference, and practical beacon configuration and positioning techniques that improve accuracy. Our experience with Cricket shows that several location-dependent applications such as in-building active maps and device control can be developed with little effort or manual configuration.
---
paper_title: Audio Signal Processing for Next-Generation Multimedia Communication Systems

paper_content:

Preface. Contributing Authors. 1: Introduction Yiteng (Arden) Huang, J. Benesty. 1. Multimedia Communications. 2. Challenges and Opportunities. 3. Organization of the Book. I: Speech Acquisition and Enhancement. 2: Differential Microphone Arrays G.W. Elko. 1. Introduction. 2. Differential Microphone Arrays. 3. Array Directional Gain. 4. Optimal Arrays for Isotropic Fields. 5. Design Examples. 6. Sensitivity to Microphone Mismatch and Noise. 7. Conclusions. 3: Spherical Microphone Arrays for 3D Sound Recording J. Meyer, G.W. Elko. 1. Introduction. 2. Fundamental Concept. 3. The Eigenbeamformer. 4. Modal-Beamformer. 5. Robustness Measure. 6. Beampattern Design. 7. Measurements. 8. Summary. 9. Appendix A. 4: Subband Noise Reduction Methods for Speech Enhancement E.J. Diethorn. 1. Introduction. 2. Wiener Filtering. 3. Speech Enhancement by Short-Time Spectral Modification. 4. Averaging Techniques for Envelope Estimation. 5. Example Implementation. 6. Conclusion. II: Acoustic Echo Cancellation. 5: Adaptive Algorithms for MIMO Acoustic Echo Cancellation J. Benesty, T. Gansler, Yiteng (Arden) Huang, M. Rupp. 1. Introduction. 2. Normal Equations and Identification of a MIMO System. 3. The Classical and Factorized Multichannel RLS. 4. The Multichannel Fast RLS. 5. TheMultichannel LMS Algorithm. 6. The Multichannel APA. 7. The Multichannel Exponentiated Gradient Algorithm. 8. The Multichannel Frequency-domain Adaptive Algorithm. 9. Conclusions. 6: Double-talk Detectors for Acoustic Echo Cancellers T. Gansler, J. Benesty. 1. Introduction. 2. Basics of AEC and DTD. 3. Double-talk Detection Algorithms. 4. Comparison of DTDs by Means of the ROC. 5. Discussion. 7: The WinEC: A Real-Time Hands-Free Stereo Communication System T. Gansler, V. Fischer, E.J. Diethorn, J. Benesty. 1. Introduction. 2. System Description. 3. Algorithms of the Echo Canceller Module. 4. Residual Echo and Noise Suppression. 5. Simulations. 6. Real-Time Tests with Different Modes of Operation. 7. Discussion. III: Sound Source Tracking and Separation. 8: Time Delay Estimation Jingdong Chen, Yiteng (Arden) Huang, J. Benesty. 1. Introduction. 2. Signal Models. 3. Generalized Cross-Correlation Method. 4. The Multichannel Cross-Correlation Algorithm. 5. Adaptive Eigenvalue Decomposition Algorithm. 6. Adaptive Multichannel Time Delay Estimation. 7. Experiments. 8. Conclusions. 9: Source Localization Yiteng (Arden) Huang, J. Benesty, G.W. Elko. 1. Introduction. 2. Source Localization Problem. 3. Measurement Model and Cramer-Rao lower Bound for Source Localization. 4. Maximum Liklihood Estimator. 5. Least Squares Estimate. 6. Example
---
paper_title: A Linear Closed-Form Algorithm for Source Localization From Time-Differences of Arrival

paper_content:

Microphone arrays often operate in the near field, which complicates the problem of determining a source location from time-difference-of-arrival (TDOA) measurements typically derived from generalized cross-correlation functions. Each TDOA satisfies the equation of a hyperboloid in space and methods have been developed to either solve for intersecting hyperboloids or make some approximation to them, keeping source-location determination a nonlinear, somewhat complex problem. We introduce a closed-form, analytic solution for the problem (the GS algorithm). It is so simple that we were surprised that, until very recently, there have been no other solutions similar to ours. The method uses a minimum of five microphones in three dimensions, one more than other solutions, but, for nonsingular layouts of the microphones, it is very fast and accurate. First, the new method is compared to other closed-form methods for accuracy and sensitivity to noise using simulated data. Then, several variants of GS are compared to two other real-time algorithms, LEMSalg and SRP-PHAT, using real, human-talker data from a large array in a noisy room.
---
paper_title: Self-Localization of Ad-Hoc Arrays Using Time Difference of Arrivals

paper_content:

This work was supported by the U.K. Engineering and Physical Sciences Research Council (EPSRC) under Grant EP/K007491/1.
---
paper_title: Disambiguation of TDOA Estimation for Multiple Sources in Reverberant Environments

paper_content:

This paper presents a novel approach to estimate the time difference of arrival (TDOA) for multiple sources in reverberant environments. It resolves ambiguities in TDOA estimation caused by multipath propagation and multiple sources. By exploiting two TDOA constraints, the raster condition and the zero cyclic sum condition, we are able to identify and reject the echo path TDOAs and to assign the direct path TDOAs correctly to different sources. For the latter purpose, an efficient algorithm for the synthesis of approximately consistent TDOA graphs has been developed. A real experiment demonstrates the superior performance of our algorithms.
---
paper_title: Reliability criteria evaluation for TDOA estimates in a variety of real environments

paper_content:

Time delay estimates in microphone pairs are commonly used for acoustic sound source localization. In real environments, the reliability of time delay estimates quickly degrades for increasing noise or room reverberation levels. The paper presents two computationally non-demanding criteria to determine the reliability of time delay estimates. The criteria are evaluated for real data in a variety of acoustic environments with different reverberation and noise levels. The results show the generality of the proposed reliability indicators in delivering information on the credibility of the current time delay estimate for many typical room environments.
---
paper_title: Energy based collaborative source localization using acoustic micro-sensor array

paper_content:

A novel sensor network source localization method based on acoustic energy measurements is presented. This method makes use of the characteristics that the acoustic energy decays exponentially with respect to the distance from an omni-directional acoustic source. By comparing energy readings measured at surrounding acoustic sensors during the same time interval can be accurately estimated. We show that the potential target location is restricted to a hyper-sphere in the sensor field given the acoustic energy reading at a pair of sensors. Given multiple sensor acoustic energy readings, the target location is solved as the location that is closest (in the least square sense) to all the corresponding hyper-spheres. We further simplified this nonlinear least square problem to an unconstrained linear least square problem that yields a closed form solution. Experiment results using military vehicle acoustic data show great promise of this novel approach.
---
paper_title: Energy based collaborative source localization using acoustic micro-sensor array

paper_content:

A novel sensor network source localization method based on acoustic energy measurements is presented. This method makes use of the characteristics that the acoustic energy decays exponentially with respect to the distance from an omni-directional acoustic source. By comparing energy readings measured at surrounding acoustic sensors during the same time interval can be accurately estimated. We show that the potential target location is restricted to a hyper-sphere in the sensor field given the acoustic energy reading at a pair of sensors. Given multiple sensor acoustic energy readings, the target location is solved as the location that is closest (in the least square sense) to all the corresponding hyper-spheres. We further simplified this nonlinear least square problem to an unconstrained linear least square problem that yields a closed form solution. Experiment results using military vehicle acoustic data show great promise of this novel approach.
---
paper_title: Energy-Based Acoustic Source Localization Methods: A Survey

paper_content:

Energy-based source localization is an important problem in wireless sensor networks (WSNs), which has been studied actively in the literature. Numerous localization algorithms, e.g., maximum likelihood estimation (MLE) and nonlinear-least-squares (NLS) methods, have been reported. In the literature, there are relevant review papers for localization in WSNs, e.g., for distance-based localization. However, not much work related to energy-based source localization is covered in the existing review papers. Energy-based methods are proposed and specially designed for a WSN due to its limited sensor capabilities. This paper aims to give a comprehensive review of these different algorithms for energy-based single and multiple source localization problems, their merits and demerits and to point out possible future research directions.
---
paper_title: An Accurate Algebraic Closed-Form Solution for Energy-Based Source Localization

paper_content:

The localization of an acoustic source can be based on the energy measurements at a number of spatially separated microphones. This is because the amount of source energy attenuation at a microphone is proportional to the square of the distance between the source and the microphone. This paper develops an algebraic closed-form solution for the acoustic source localization problem using energy measurements, under the condition of direct line-of-sight and free space propagation. First-order analysis is applied to the proposed solution to study its performance, where only the linear noise terms are kept in obtaining the mean-square localization error. The first-order analytical results show that the proposed solution reaches the Cramer-Rao lower bound (CRLB) accuracy for Gaussian noise as the signal-to-noise ratio tends to infinity. In addition, the proposed solution provides much better accuracy than other closed-form solutions available in literature. Improvement on the proposed solution that extends its operating range beyond the threshold noise level was made by imposing nonnegative constraints. Simulations are included to corroborate the performance of the proposed method.
---
paper_title: Passive source localization employing intersecting spherical surfaces from time-of-arrival differences

paper_content:

Problems associated with the use of intersecting hyperboloids for passive source localization from time-of-arrival difference signals are discussed. A closed-form solution for source location is presented given time-of-arrival difference measurements when the distance from the source to any arbitrary reference is unknown.
---
paper_title: On Energy-Based Acoustic Source Localization for Sensor Networks

paper_content:

In this paper, energy-based localization methods for source localization in sensor networks are examined. The focus is on least-squares-based approaches due to a good tradeoff between performance and complexity. A suite of methods are developed and compared. First, two previously proposed methods (quadratic elimination and one step) are shown to yield the same location estimate for a source. Next, it is shown that, as the errors which perturb the least-squares equations are nonidentically distributed, it is more appropriate to consider weighted least-squares methods, which are observed to yield significant performance gains over the unweighted methods. Finally, a new weighted direct least-squares formulation is presented and shown to outperform the previous methods with much less computational complexity. Unlike the quadratic elimination method, the weighted direct least-squares method is amenable to a correction technique which incorporates the dependence of unknown parameters leading to further performance gains. For a sufficiently large number of samples, simulations show that the weighted direct solution with correction (WDC) can be more accurate with significantly less computational complexity than the maximum-likelihood estimator and approaches Cramer-Rao bound (CRB). Furthermore, it is shown that WDC attains CRB for the case of a white source.
---
paper_title: A Closed-Form Location Estimator for Use with Room Environment Microphone Arrays

paper_content:

The linear intersection (LI) estimator, which is a closed-form method for the localization of source positions given sensor array time-delay estimate information, is presented. The LI estimator is shown to be robust and accurate, to closely model the search-based ML estimator, and to outperform a benchmark algorithm. The computational complexity of the LI estimator is suitable for use in real-time microphone-array applications where search-based location algorithms may be infeasible.
---
paper_title: Maximum likelihood multiple-source localization using acoustic energy measurements with wireless sensor networks

paper_content:

A maximum likelihood (ML) acoustic source location estimation method is presented for the application in a wireless ad hoc sensor network. This method uses acoustic signal energy measurements taken at individual sensors of an ad hoc wireless sensor network to estimate the locations of multiple acoustic sources. Compared to the existing acoustic energy based source localization methods, this proposed ML method delivers more accurate results and offers the enhanced capability of multiple source localization. A multiresolution search algorithm and an expectation-maximization (EM) like iterative algorithm are proposed to expedite the computation of source locations. The Crame/spl acute/r-Rao Bound (CRB) of the ML source location estimate has been derived. The CRB is used to analyze the impacts of sensor placement to the accuracy of location estimates for single target scenario. Extensive simulations have been conducted. It is observed that the proposed ML method consistently outperforms existing acoustic energy based source localization methods. An example applying this method to track military vehicles using real world experiment data also demonstrates the performance advantage of this proposed method over a previously proposed acoustic energy source localization method.
---
paper_title: Closed-form least-squares source location estimation from range-difference measurements

paper_content:

Three noniterative techniques are presented for localizing a single source given a set of noisy range-difference measurements. The localization formulas are derived from linear least-squares "equation error" minimization, and in one case the maximum likelihood bearing estimate is approached. Geometric interpretations of the equation error norms minimized by the three methods are given, and the statistical performances of the three methods are compared via computer simulation.
---
paper_title: The spherical interpolation method of source localization

paper_content:

A closed-form least squares approximate maximum likelihood method for localization of broad-band emitters from time-difference-of-arrival (TDOA) measurements, called the spherical interpolation (SI) method, is presented. The localization formula is derived from least squares "equation-error" minimization. Computer simulation results show that the SI method has variance approaching the Cramer-Rap lower bound.
---
paper_title: Energy-based sensor network source localization via projection onto convex sets

paper_content:

This correspondence addresses the problem of locating an acoustic source using a sensor network in a distributed manner, i.e., without transmitting the full data set to a central point for processing. This problem has been traditionally addressed through the maximum-likelihood framework or nonlinear least squares. These methods, even though asymptotically optimal under certain conditions, pose a difficult global optimization problem. It is shown that the associated objective function may have multiple local optima and saddle points, and hence any local search method might stagnate at a suboptimal solution. In this correspondence, we formulate the problem as a convex feasibility problem and apply a distributed version of the projection-onto-convex-sets (POCS) method. We give a closed-form expression for the projection phase, which usually constitutes the heaviest computational aspect of POCS. Conditions are given under which, when the number of samples increases to infinity or in the absence of measurement noise, the convex feasibility problem has a unique solution at the true source location. In general, the method converges to a limit point or a limit cycle in the neighborhood of the true location. Simulation results show convergence to the global optimum with extremely fast convergence rates compared to the previous methods
---
paper_title: TDOA-Based Speed of Sound Estimation for Air Temperature and Room Geometry Inference

paper_content:

Spatially distributed acoustic sensors find increasingly many new applications in speech-based human-machine interfaces. One well researched topic is the localization of sound sources from Time Differences Of Arrival (TDOAs) measurements. Typically, the propagation speed of sound is considered a known constant. However due to temperature variations its value is known only up to some uncertainty. This paper exploits TDOA-based localization techniques in order to estimate accurately the actual speed of sound. Experimental results using both simulated and real data demonstrate the feasibility of the proposed method. Furthermore, the practical validation of this work considers two distinct experiments that are aimed at inferring information about enclosed sound fields. The first experiment concerns the calculation of the air temperature from the estimated speed of sound. The second experiment highlights the effects of temperature variations on the inference of the physical location of reflective boundaries of the acoustic enclosure. In the latter case it is shown that the position estimates of the reflective surfaces in a room can be improved when the correct propagation speed is first estimated using this method.
---
paper_title: Revisiting trilateration for robot localization

paper_content:

Locating a robot from its distances, or range measurements, to three other known points or stations is a common operation, known as trilateration. This problem has been traditionally solved either by algebraic or numerical methods. An approach that avoids the direct algebrization of the problem is proposed here. Using constructive geometric arguments, a coordinate-free formula containing a small number of Cayley-Menger determinants is derived. This formulation accommodates a more thorough investigation of the effects caused by all possible sources of error, including round-off errors, for the first time in this context. New formulas for the variance and bias of the unknown robot location estimation, due to station location and range measurements errors, are derived and analyzed. They are proved to be more tractable compared with previous ones, because all their terms have geometric meaning, allowing a simple analysis of their asymptotic behavior near singularities.
---
paper_title: Multiple Source Localization in Wireless Sensor Networks Based on Time of Arrival Measurement

paper_content:

We investigate the localization of multiple signal sources based on sensors performing time-of-arrival (TOA) measurement in wireless sensor networks. Moving beyond the widely studied single source localization problem, concurrently active multiple sources substantially complicate the problem since anchored sensor nodes are unaware of associations between measured signals and source nodes. At the same time, as the total number of possible source-measurement associations grows exponentially with the number of sensor nodes, it is inefficient to attempt conventional single-source localization algorithm for each possible association in a brute-force manner. In this work, we address this difficult problem from a joint optimization perspective. Specifically, we consider simultaneous estimation of source-measurement associations and the source locations, in addition to finding the initial signal transmission time. This joint optimization problem includes both discrete and continuous variables. We propose an efficient three-step algorithm that progressively simplifies the original problem through convex relaxation and sensible approximations. Our proposed algorithm demonstrates results comparable to a genie-aided method that utilizes known source-measurement associations.
---
paper_title: Position calibration of microphones and loudspeakers in distributed computing platforms

paper_content:

We present a novel algorithm to automatically determine the relative three-dimensional (3-D) positions of audio sensors and actuators in an ad-hoc distributed network of heterogeneous general purpose computing platforms such as laptops, PDAs, and tablets. A closed form approximate solution is derived, which is further refined by minimizing a nonlinear error function. Our formulation and solution accounts for the lack of temporal synchronization among different platforms. We compare two different estimators, one based on the time of flight and the other based on time difference of flight. We also derive an approximate expression for the mean and covariance of the implicitly defined estimator using the implicit function theorem and approximate Taylors' series expansion. The theoretical performance limits for estimating the sensor 3-D positions are derived via the Crame/spl acute/r-Rao bound (CRB) and analyzed, with respect to the number of sensors and actuators, as well as their geometry. We report extensive simulation results and discuss the practical details of implementing our algorithms in a real-life system.
---
paper_title: Method for positioning GSM mobile stations using absolute time delay measurements

paper_content:

A trilateration based method for locating mobile stations (MSs) in GSM cellular communication network is proposed. Measurements are processed with an extended Kalman filter (EKF), in order to track MSs and to establish their position. An analytical study of positioning accuracy is also developed.
---
paper_title: Reliable computation of the points of intersection of $n$ spheres in $R^n$

paper_content:

The problem of determining the points of intersection of n spheres in R n has many applications. Examples in 3-D include problems in navigation, in positioning of specific atoms in crystal structures, in reconstructing torso geometries in experimental cardiology, in the `Pentacle Problem,' and in many other problems of distance geometry. The problem is easily formulated as a system of n nonlinear equations in the coordinates of the unknown point(s) of intersection and it is of interest to determine an efficient and reliable method of solution. It is shown that apart from a few square roots the problem is usually easily and robustly solved without iteration by employing standard techniques from linear algebra. In some applications, however, the radii of the spheres may not be known accurately and this can lead to difficulties, particularly when the required point is close to lying in the affine subspace defined by the n centres of the spheres. In such cases it is more appropriate to formulate a nonlinear least squares problem in order to identify a `best approximate solution.' The special structure of this nonlinear least squares problem allows a solution to be calculated through an efficient safeguarded Newton iteration.
---
paper_title: Statistical Methods in Surveying by Trilateration

paper_content:

Abstract Trilateration techniques use distance measurements to survey the spatial coordinates of unknown positions. In practice, distances are measured with error, and statistical methods can quantify the uncertainty in the estimate of the unknown location. Three methods for estimating the three-dimensional position of a point via trilateration are presented: a linear least-squares estimator, an iteratively reweighted least-squares estimator, and a non-linear least-squares technique. In general, the non-linear least-squares technique performs best, but in some situations a linear estimator could in theory be constructed that would outperform it. By eliminating the need to measure angles, trilateration facilitates the implementation of fully automated real-time positioning systems similar to the global positioning system (GPS). The methods presented in this paper are tested in the context of a realistic positioning problem that was posed by the Thunder Basin Coal Company in Wright, Wyoming.
---
paper_title: Position-Location Solutions by Taylor-Series Estimation

paper_content:

Taylor-series estimation gives a least-sum-squared-error solution to a set of simultaneous linearized algebraic equations. This method is useful in solving multimeasurement mixed-mode position-location problems typical of many navigational applications. While convergence is not proved, examples show that most problems do converge to the correct solution from reasonable initial guesses. The method also provides the statistical spread of the solution errors.
---
paper_title: Efficient solution and performance analysis of 3-D position estimation by trilateration

paper_content:

A new exact, explicit, and computationally efficient solution for three-dimensional (3-D) position estimation based on range measurements from three stations is proposed. The simple polynomial-type form of the new algorithm facilitates the performance analysis. Formulae are provided for both the variance and the bias of the position estimates. The systematic error is a joint effect of both the measurement noise and the system nonlinearity and its magnitude cannot be ignored if highly accurate localization is required. Performance evaluation results are presented for various conditions.
---
paper_title: A Linear Closed-Form Algorithm for Source Localization From Time-Differences of Arrival

paper_content:

Microphone arrays often operate in the near field, which complicates the problem of determining a source location from time-difference-of-arrival (TDOA) measurements typically derived from generalized cross-correlation functions. Each TDOA satisfies the equation of a hyperboloid in space and methods have been developed to either solve for intersecting hyperboloids or make some approximation to them, keeping source-location determination a nonlinear, somewhat complex problem. We introduce a closed-form, analytic solution for the problem (the GS algorithm). It is so simple that we were surprised that, until very recently, there have been no other solutions similar to ours. The method uses a minimum of five microphones in three dimensions, one more than other solutions, but, for nonsingular layouts of the microphones, it is very fast and accurate. First, the new method is compared to other closed-form methods for accuracy and sensitivity to noise using simulated data. Then, several variants of GS are compared to two other real-time algorithms, LEMSalg and SRP-PHAT, using real, human-talker data from a large array in a noisy room.
---
paper_title: An efficient least-squares trilateration algorithm for mobile robot localization

paper_content:

A novel efficient trilateration algorithm is presented to estimate the position of a target object, such as a mobile robot, in a 2D or 3D space. The proposed algorithm is derived from a nonlinear least-squares formulation, and provides an optimal position estimate from a number (greater than or equal to the dimension of the environment) of reference points and corresponding distance measurements. Using standard linear algebra techniques, the proposed algorithm has low computational complexity and high operational robustness. Error analysis has been conducted through simulations on representative examples. The results show that the proposed algorithm has lower systematic error and uncertainty in position estimation when dealing with erroneous inputs, compared with representative closed-form methods.
---
paper_title: Cumulative-Sum-Based Localization of Sound Events in Low-Cost Wireless Acoustic Sensor Networks

paper_content:

Wireless acoustic sensor networks (WASNs) are known for their potential applications in multiple areas, such as audio-based surveillance, binaural hearing aids or advanced acoustic monitoring. The knowledge of the spatial position of a source of interest is usually a requirement for many of these applications. Therefore, source localization is an important problem to be addressed in WASNs. Unfortunately, most localization algorithms need costly signal processing stages that prevent them from being implemented in low-cost sensor networks, requiring additional modules for signal acquisition and processing. This paper presents a low-complexity method for acoustic event detection and localization considering a change detection statistical framework. Two possible implementation approaches based on the efficient cumulative sum (CUSUM) algorithm are presented and discussed. Results from simulations and a real deployment show that the proposed techniques can be easily implemented in low-cost sensor networks, providing good localization accuracy and making good use of the available node resources.
---
paper_title: The generalized correlation method for estimation of time delay

paper_content:

A maximum likelihood (ML) estimator is developed for determining time delay between signals received at two spatially separated sensors in the presence of uncorrelated noise. This ML estimator can be realized as a pair of receiver prefilters followed by a cross correlator. The time argument at which the correlator achieves a maximum is the delay estimate. The ML estimator is compared with several other proposed processors of similar form. Under certain conditions the ML estimator is shown to be identical to one proposed by Hannan and Thomson [10] and MacDonald and Schultheiss [21]. Qualitatively, the role of the prefilters is to accentuate the signal passed to the correlator at frequencies for which the signal-to-noise (S/N) ratio is highest and, simultaneously, to suppress the noise power. The same type of prefiltering is provided by the generalized Eckart filter, which maximizes the S/N ratio of the correlator output. For low S/N ratio, the ML estimator is shown to be equivalent to Eckart prefiltering.
---
paper_title: Acoustic Source Localization With Distributed Asynchronous Microphone Networks

paper_content:

We propose a method for localizing an acoustic source with distributed microphone networks. Time Differences of Arrival (TDOAs) of signals pertaining the same sensor are estimated through Generalized Cross-Correlation. After a TDOA filtering stage that discards measurements that are potentially unreliable, source localization is performed by minimizing a fourth-order polynomial that combines hyperbolic constraints from multiple sensors. The algorithm turns to exhibit a significantly lower computational cost compared with state-of-the-art techniques, while retaining an excellent localization accuracy in fairly reverberant conditions.
---
paper_title: A robust and low-complexity source localization algorithm for asynchronous distributed microphone networks

paper_content:

In this paper, we propose a robust and low-complexity acoustic source localization technique based on time differences of arrival (TDOA), which addresses the scenario of distributed sensor networks in 3D environments. Network nodes are assumed to be unsynchronized, i.e., TDOAs between microphones belonging to different nodes are not available. We begin with showing how to select feasible TDOAs for each sensor node, exploiting both geometrical considerations and a characterization of the overall generalized cross correlation (GCC) shape. We then show how to localize sources in the space-range reference frame, where TDOA measurements have a clear geometrical interpretation that can be fruitfully used in the scenario of unsynchronized sensors. In this framework, in fact, the source corresponds to the apex of a hypercone passing through points described by the sole microphone positions and TDOA measurements. The localization problem is therefore approached as a hypercone fitting problem. Finally, in order to improve the robustness of the estimate, we include an outlier detection procedure based on the evaluation of the hypercone fitting residuals. A refinement of source location estimate is then performed ignoring the contributions coming from outlier measurements. A set of simulations shows the performance of individual blocks of the system, with particular focus on the effect of TDOA selection on source localization and refinement steps. Experiments on real data validate the localization algorithm in an everyday scenario, proving that good accuracy can be obtained while saving computational cost in comparison with state-of-the-art techniques.
---
paper_title: Three different reliability criteria for Time Delay estimates

paper_content:

Time Difference Of Arrival (TDOA) estimates are often used for passive acoustic single sound source localization with microphone arrays. Commonly, the Generalized Cross-Correlation method is applied for TDOA estimation. In real environments the reliability of TDOA estimates is degraded due to noise and especially to room reverberation. This work presents three reliability criteria allowing convincingly the evaluation of the confidence of every single TDOA estimate. The criteria are evaluated and compared to each other for real data recorded in a noisy and reverberant office room environment. The use of the reliability criteria permits a robust sound source localization even in adverse acoustic environments with increased reverberation times.
---
paper_title: Disambiguation of TDOA Estimation for Multiple Sources in Reverberant Environments

paper_content:

This paper presents a novel approach to estimate the time difference of arrival (TDOA) for multiple sources in reverberant environments. It resolves ambiguities in TDOA estimation caused by multipath propagation and multiple sources. By exploiting two TDOA constraints, the raster condition and the zero cyclic sum condition, we are able to identify and reject the echo path TDOAs and to assign the direct path TDOAs correctly to different sources. For the latter purpose, an efficient algorithm for the synthesis of approximately consistent TDOA graphs has been developed. A real experiment demonstrates the superior performance of our algorithms.
---
paper_title: Reliability criteria evaluation for TDOA estimates in a variety of real environments

paper_content:

Time delay estimates in microphone pairs are commonly used for acoustic sound source localization. In real environments, the reliability of time delay estimates quickly degrades for increasing noise or room reverberation levels. The paper presents two computationally non-demanding criteria to determine the reliability of time delay estimates. The criteria are evaluated for real data in a variety of acoustic environments with different reverberation and noise levels. The results show the generality of the proposed reliability indicators in delivering information on the credibility of the current time delay estimate for many typical room environments.
---
paper_title: Acoustic Source Localization With Distributed Asynchronous Microphone Networks

paper_content:

We propose a method for localizing an acoustic source with distributed microphone networks. Time Differences of Arrival (TDOAs) of signals pertaining the same sensor are estimated through Generalized Cross-Correlation. After a TDOA filtering stage that discards measurements that are potentially unreliable, source localization is performed by minimizing a fourth-order polynomial that combines hyperbolic constraints from multiple sensors. The algorithm turns to exhibit a significantly lower computational cost compared with state-of-the-art techniques, while retaining an excellent localization accuracy in fairly reverberant conditions.
---
paper_title: Audio Signal Processing for Next-Generation Multimedia Communication Systems

paper_content:

Preface. Contributing Authors. 1: Introduction Yiteng (Arden) Huang, J. Benesty. 1. Multimedia Communications. 2. Challenges and Opportunities. 3. Organization of the Book. I: Speech Acquisition and Enhancement. 2: Differential Microphone Arrays G.W. Elko. 1. Introduction. 2. Differential Microphone Arrays. 3. Array Directional Gain. 4. Optimal Arrays for Isotropic Fields. 5. Design Examples. 6. Sensitivity to Microphone Mismatch and Noise. 7. Conclusions. 3: Spherical Microphone Arrays for 3D Sound Recording J. Meyer, G.W. Elko. 1. Introduction. 2. Fundamental Concept. 3. The Eigenbeamformer. 4. Modal-Beamformer. 5. Robustness Measure. 6. Beampattern Design. 7. Measurements. 8. Summary. 9. Appendix A. 4: Subband Noise Reduction Methods for Speech Enhancement E.J. Diethorn. 1. Introduction. 2. Wiener Filtering. 3. Speech Enhancement by Short-Time Spectral Modification. 4. Averaging Techniques for Envelope Estimation. 5. Example Implementation. 6. Conclusion. II: Acoustic Echo Cancellation. 5: Adaptive Algorithms for MIMO Acoustic Echo Cancellation J. Benesty, T. Gansler, Yiteng (Arden) Huang, M. Rupp. 1. Introduction. 2. Normal Equations and Identification of a MIMO System. 3. The Classical and Factorized Multichannel RLS. 4. The Multichannel Fast RLS. 5. TheMultichannel LMS Algorithm. 6. The Multichannel APA. 7. The Multichannel Exponentiated Gradient Algorithm. 8. The Multichannel Frequency-domain Adaptive Algorithm. 9. Conclusions. 6: Double-talk Detectors for Acoustic Echo Cancellers T. Gansler, J. Benesty. 1. Introduction. 2. Basics of AEC and DTD. 3. Double-talk Detection Algorithms. 4. Comparison of DTDs by Means of the ROC. 5. Discussion. 7: The WinEC: A Real-Time Hands-Free Stereo Communication System T. Gansler, V. Fischer, E.J. Diethorn, J. Benesty. 1. Introduction. 2. System Description. 3. Algorithms of the Echo Canceller Module. 4. Residual Echo and Noise Suppression. 5. Simulations. 6. Real-Time Tests with Different Modes of Operation. 7. Discussion. III: Sound Source Tracking and Separation. 8: Time Delay Estimation Jingdong Chen, Yiteng (Arden) Huang, J. Benesty. 1. Introduction. 2. Signal Models. 3. Generalized Cross-Correlation Method. 4. The Multichannel Cross-Correlation Algorithm. 5. Adaptive Eigenvalue Decomposition Algorithm. 6. Adaptive Multichannel Time Delay Estimation. 7. Experiments. 8. Conclusions. 9: Source Localization Yiteng (Arden) Huang, J. Benesty, G.W. Elko. 1. Introduction. 2. Source Localization Problem. 3. Measurement Model and Cramer-Rao lower Bound for Source Localization. 4. Maximum Liklihood Estimator. 5. Least Squares Estimate. 6. Example
---
paper_title: A robust and low-complexity source localization algorithm for asynchronous distributed microphone networks

paper_content:

In this paper, we propose a robust and low-complexity acoustic source localization technique based on time differences of arrival (TDOA), which addresses the scenario of distributed sensor networks in 3D environments. Network nodes are assumed to be unsynchronized, i.e., TDOAs between microphones belonging to different nodes are not available. We begin with showing how to select feasible TDOAs for each sensor node, exploiting both geometrical considerations and a characterization of the overall generalized cross correlation (GCC) shape. We then show how to localize sources in the space-range reference frame, where TDOA measurements have a clear geometrical interpretation that can be fruitfully used in the scenario of unsynchronized sensors. In this framework, in fact, the source corresponds to the apex of a hypercone passing through points described by the sole microphone positions and TDOA measurements. The localization problem is therefore approached as a hypercone fitting problem. Finally, in order to improve the robustness of the estimate, we include an outlier detection procedure based on the evaluation of the hypercone fitting residuals. A refinement of source location estimate is then performed ignoring the contributions coming from outlier measurements. A set of simulations shows the performance of individual blocks of the system, with particular focus on the effect of TDOA selection on source localization and refinement steps. Experiments on real data validate the localization algorithm in an everyday scenario, proving that good accuracy can be obtained while saving computational cost in comparison with state-of-the-art techniques.
---
paper_title: Passive source localization employing intersecting spherical surfaces from time-of-arrival differences

paper_content:

Problems associated with the use of intersecting hyperboloids for passive source localization from time-of-arrival difference signals are discussed. A closed-form solution for source location is presented given time-of-arrival difference measurements when the distance from the source to any arbitrary reference is unknown.
---
paper_title: On Energy-Based Acoustic Source Localization for Sensor Networks

paper_content:

In this paper, energy-based localization methods for source localization in sensor networks are examined. The focus is on least-squares-based approaches due to a good tradeoff between performance and complexity. A suite of methods are developed and compared. First, two previously proposed methods (quadratic elimination and one step) are shown to yield the same location estimate for a source. Next, it is shown that, as the errors which perturb the least-squares equations are nonidentically distributed, it is more appropriate to consider weighted least-squares methods, which are observed to yield significant performance gains over the unweighted methods. Finally, a new weighted direct least-squares formulation is presented and shown to outperform the previous methods with much less computational complexity. Unlike the quadratic elimination method, the weighted direct least-squares method is amenable to a correction technique which incorporates the dependence of unknown parameters leading to further performance gains. For a sufficiently large number of samples, simulations show that the weighted direct solution with correction (WDC) can be more accurate with significantly less computational complexity than the maximum-likelihood estimator and approaches Cramer-Rao bound (CRB). Furthermore, it is shown that WDC attains CRB for the case of a white source.
---
paper_title: Exact and Approximate Solutions of Source Localization Problems

paper_content:

We consider least squares (LS) approaches for locating a radiating source from range measurements (which we call R-LS) or from range-difference measurements (RD-LS) collected using an array of passive sensors. We also consider LS approaches based on squared range observations (SR-LS) and based on squared range-difference measurements (SRD-LS). Despite the fact that the resulting optimization problems are nonconvex, we provide exact solution procedures for efficiently computing the SR-LS and SRD-LS estimates. Numerical simulations suggest that the exact SR-LS and SRD-LS estimates outperform existing approximations of the SR-LS and SRD-LS solutions as well as approximations of the R-LS and RD-LS solutions which are based on a semidefinite relaxation.
---
paper_title: Passive acoustic source localization for video camera steering

paper_content:

A multi-input one-step least-squares (OSLS) algorithm for passive source localization is proposed. It is shown that the OSLS algorithm is mathematically equivalent to the so-called spherical interpolation (SI) method but with less computational complexity. The OSLS/SI method uses spherical equations (instead of hyperbolic equations) and solves them in a least-squares sense. Based on the adaptive eigenvalue decomposition time delay estimation method previously proposed by the same authors and the OSLS source localization algorithm, a real-time passive source localization system for video camera steering is presented. The system demonstrates many desirable features such as accuracy, portability, and robustness.
---
paper_title: TDOA-based acoustic source localization in the space–range reference frame

paper_content:

In this paper we consider a class of geometric methods for acoustic source localization based on range differences (or time differences of arrival), and we offer a new and unifying perspective on such methods based on the adoption of a multidimensional reference frame obtained by adding the range difference coordinate to the spatial coordinates of the source. In this extended coordinate system the working principles of a wide range of source localization methods becomes clear and immediate. The space---range reference frame, however, has a practical purpose as well, as it can be used for gaining insight on why some configurations of microphones lead to better localization performance than others and it suggests methods for improving existing localization techniques. In particular, we derive a closed-form solution of the constrained least-squares localization problem for linear arrays of microphones.
---
paper_title: Real-time passive source localization: a practical linear-correction least-squares approach

paper_content:

A linear-correction least-squares estimation procedure is proposed for the source localization problem under an additive measurement error model. The method, which can be easily implemented in a real-time system with moderate computational complexity, yields an efficient source location estimator without assuming a priori knowledge of noise distribution. Alternative existing estimators, including likelihood-based, spherical intersection, spherical interpolation, and quadratic-correction least-squares estimators, are reviewed and comparisons of their complexity, estimation consistency and efficiency against the Cramer-Rao lower bound are made. Numerical studies demonstrate that the proposed estimator performs better under many practical situations.
---
paper_title: The spherical interpolation method for closed-form passive source localization using range difference measurements

paper_content:

The problem of estimating the location of a radiating source from range difference measurements taken from a passive, stationary array is discussed. A new closed-form source location estimator, termed the Spherical Interpolation Estimator, is presented and analyzed. The location estimates produced by the Spherical Interpolation Estimator are approximate minimizers of a weighted equation error norm, and are shown to approach the maximum likelihood source location estimator.
---
paper_title: Closed-form least-squares source location estimation from range-difference measurements

paper_content:

Three noniterative techniques are presented for localizing a single source given a set of noisy range-difference measurements. The localization formulas are derived from linear least-squares "equation error" minimization, and in one case the maximum likelihood bearing estimate is approached. Geometric interpretations of the equation error norms minimized by the three methods are given, and the statistical performances of the three methods are compared via computer simulation.
---
paper_title: A Linear Closed-Form Algorithm for Source Localization From Time-Differences of Arrival

paper_content:

Microphone arrays often operate in the near field, which complicates the problem of determining a source location from time-difference-of-arrival (TDOA) measurements typically derived from generalized cross-correlation functions. Each TDOA satisfies the equation of a hyperboloid in space and methods have been developed to either solve for intersecting hyperboloids or make some approximation to them, keeping source-location determination a nonlinear, somewhat complex problem. We introduce a closed-form, analytic solution for the problem (the GS algorithm). It is so simple that we were surprised that, until very recently, there have been no other solutions similar to ours. The method uses a minimum of five microphones in three dimensions, one more than other solutions, but, for nonsingular layouts of the microphones, it is very fast and accurate. First, the new method is compared to other closed-form methods for accuracy and sensitivity to noise using simulated data. Then, several variants of GS are compared to two other real-time algorithms, LEMSalg and SRP-PHAT, using real, human-talker data from a large array in a noisy room.
---
paper_title: The spherical interpolation method of source localization

paper_content:

A closed-form least squares approximate maximum likelihood method for localization of broad-band emitters from time-difference-of-arrival (TDOA) measurements, called the spherical interpolation (SI) method, is presented. The localization formula is derived from least squares "equation-error" minimization. Computer simulation results show that the SI method has variance approaching the Cramer-Rap lower bound.
---
paper_title: Energy-based sensor network source localization via projection onto convex sets

paper_content:

This correspondence addresses the problem of locating an acoustic source using a sensor network in a distributed manner, i.e., without transmitting the full data set to a central point for processing. This problem has been traditionally addressed through the maximum-likelihood framework or nonlinear least squares. These methods, even though asymptotically optimal under certain conditions, pose a difficult global optimization problem. It is shown that the associated objective function may have multiple local optima and saddle points, and hence any local search method might stagnate at a suboptimal solution. In this correspondence, we formulate the problem as a convex feasibility problem and apply a distributed version of the projection-onto-convex-sets (POCS) method. We give a closed-form expression for the projection phase, which usually constitutes the heaviest computational aspect of POCS. Conditions are given under which, when the number of samples increases to infinity or in the absence of measurement noise, the convex feasibility problem has a unique solution at the true source location. In general, the method converges to a limit point or a limit cycle in the neighborhood of the true location. Simulation results show convergence to the global optimum with extremely fast convergence rates compared to the previous methods
---
paper_title: Localization of Acoustic Sources Through the Fitting of Propagation Cones Using Multiple Independent Arrays

paper_content:

In this paper, we propose a novel acoustic source localization method that accommodates the general scenario of multiple independent microphone arrays. The method is based on a 3-D parameter space defined by the 2-D spatial location of a source and the range difference extracted from the time difference of arrival (TDOA). In this space, the set of points that correspond to a given range lie on a circle that expand as the range increases, forming a cone whose apex is the actual location of the source. In this parameter space, the lack of synchronization between arrays results in the fact that clusters of data associated to individual arrays are free to shift along the range axis. The cone constraint, in fact, enables the realignment of such clusters while positioning the cone vertex (source location), thus resulting in a joint data re-synchronization and source localization. We also propose a novel and general analysis methodology for swiftly assessing the localization error as a function of the TDOA uncertainties, which is remarkably accurate for small localization bias. With the aid of this method, simulations and experiments on real data, we show that the cone-fitting process offers excellent localization accuracy in the scenario of multiple unsynchronized arrays, as well as in simpler single-array scenarios, also in comparison with state-of-the-art techniques. We also show that the proposed method offers the desired flexibility for adapting to arbitrary geometries of microphone clusters.
---
paper_title: Broadband variations of the MUSIC high-resolution method for Sound Source Localization in Robotics

paper_content:

The MUSIC algorithm (multiple signal classification) is a well-known high-resolution method to sound source localization. However, as it is essentially narrowband, several extensions can be envisaged when dealing with broadband sources like human voice. This paper presents such extensions and proposes a comparative study w.r.t. specific robotics constraints. An online beamspace MUSIC method, together with a recently developed beamforming scheme, are shown to constitute a mathematically sound and potentially efficient solution.
---
paper_title: ESPRIT-estimation of signal parameters via rotational invariance techniques

paper_content:

An approach to the general problem of signal parameter estimation is described. The algorithm differs from its predecessor in that a total least-squares rather than a standard least-squares criterion is used. Although discussed in the context of direction-of-arrival estimation, ESPRIT can be applied to a wide variety of problems including accurate detection and estimation of sinusoids in noise. It exploits an underlying rotational invariance among signal subspaces induced by an array of sensors with a translational invariance structure. The technique, when applicable, manifests significant performance and computational advantages over previous algorithms such as MEM, Capon's MLM, and MUSIC. >
---
paper_title: Robust acoustic source localization based on modal beamforming and time–frequency processing using circular microphone arrays

paper_content:

Uniform circular array processing has been shown to be a very useful tool for broadband acoustic source localization over 360°. Specifically, beamforming methods based on circular harmonics have attracted a lot of research attention in the last several years, as modal array signal processing is a very active research topic. On the other hand, due to the sparsity properties of speech, source localization methods in the time-frequency (T-F) domain have also demonstrated their capability to locate several simultaneous sources with high accuracy. In this paper, a localization framework based on circular harmonics beamforming and T-F processing that provides accurate localization performance under very adverse acoustic conditions is presented. Modal processing and sparsity-based localization are jointly addressed to estimate the direction-of-arrival of multiple concurrent speech sources. Experiments in real and simulated environments with different microphone setups are discussed, showing the validity of the proposed approach and comparing its performance with other state-of-the-art methods.
---
paper_title: Generalized State Coherence Transform for Multidimensional TDOA Estimation of Multiple Sources

paper_content:

According to the physical meaning of the frequency-domain blind source separation (FD-BSS), each mixing matrix estimated by independent component analysis (ICA) contains information on the physical acoustic propagation related to each source and then can be used for localization purposes. In this paper, we analyze the Generalized State Coherence Transform (GSCT) which is a non-linear transform of the space represented by the whole demixing matrices. The transform enables an accurate estimation of the propagation time-delay of multiple sources in multiple dimensions. Furthermore, it is shown that with appropriate nonlinearities and a statistical model for the reverberation, GSCT can be considered an approximated kernel density estimator of the acoustic propagation time-delay. Experimental results confirm the good properties of the transform and its effectiveness in addressing multiple source TDOA detection (e.g., 2-D TDOA estimation of several sources with only three microphones).
---
paper_title: Real-Time Multiple Sound Source Localization and Counting Using a Circular Microphone Array

paper_content:

In this work, a multiple sound source localization and counting method is presented, that imposes relaxed sparsity constraints on the source signals. A uniform circular microphone array is used to overcome the ambiguities of linear arrays, however the underlying concepts (sparse component analysis and matching pursuit-based operation on the histogram of estimates) are applicable to any microphone array topology. Our method is based on detecting time-frequency (TF) zones where one source is dominant over the others. Using appropriately selected TF components in these “single-source” zones, the proposed method jointly estimates the number of active sources and their corresponding directions of arrival (DOAs) by applying a matching pursuit-based approach to the histogram of DOA estimates. The method is shown to have excellent performance for DOA estimation and source counting, and to be highly suitable for real-time applications due to its low complexity. Through simulations (in various signal-to-noise ratio conditions and reverberant environments) and real environment experiments, we indicate that our method outperforms other state-of-the-art DOA and source counting methods in terms of accuracy, while being significantly more efficient in terms of computational complexity.
---
paper_title: On exploiting propagation delays for passive target localization using bearings-only measurements

paper_content:

For many cases, target localization accuracy can significantly improve by accounting for the propagation delay between the target source and the sensors. This paper considers when it is advantageous to compensate for the propagation delay for the case of a network of nodes where each node consists of an array of sensors. Each node calculates a direction of arrival (DOA) from the raw data, and these DOAs are combined to localize the target. First, we consider the case when no prior data are given and the localization occurs using DOA measurements from a single snapshot. Such localization methods are necessary to initiate a target track. Finally, we investigate the case where an extended Kalman filter is used to aggregate measurements over multiple snapshots.
---
paper_title: Real-time localization of multiple audio sources in a wireless acoustic sensor network

paper_content:

In this work we propose a grid-based method to estimate the location of multiple sources in a wireless acoustic sensor network, where each sensor node contains a microphone array and only transmits direction-of-arrival (DOA) estimates in each time interval, minimizing the transmissions to the central processing node. We present new work on modeling the DOA estimation error in such a scenario. Through extensive, realistic simulations, we show our method outperforms other state-of-the-art methods, in both accuracy and complexity. We present localization results of real recordings in an outdoor cell of a sensor network.
---
paper_title: Method for positioning GSM mobile stations using absolute time delay measurements

paper_content:

A trilateration based method for locating mobile stations (MSs) in GSM cellular communication network is proposed. Measurements are processed with an extended Kalman filter (EKF), in order to track MSs and to establish their position. An analytical study of positioning accuracy is also developed.
---
paper_title: Statistical theory of d.f. fixing

paper_content:

The paper deals with the location of an object of u nknown position, on which bearings are taken from two or more stations whose positions are known, and provides solutions to the two problems:-(a) Given a set of bearings, what is the most probable position of the object?(b) How far from the true position is the position indicated by the “fix” likely to be?Diagrams are given to show the results of applying the theory to typical practical cases.It is shown that, subject to certain qualifications, reliability of a fix does not depend on the size of the particular “cocked hat” from which it is derived.It is proposed that the reciprocal of the root-mean-square error expected in the position of the fix should be adopted as the conventional standard quantity for measuring the reliability of a fix.
---
paper_title: Statistical Methods in Surveying by Trilateration

paper_content:

Abstract Trilateration techniques use distance measurements to survey the spatial coordinates of unknown positions. In practice, distances are measured with error, and statistical methods can quantify the uncertainty in the estimate of the unknown location. Three methods for estimating the three-dimensional position of a point via trilateration are presented: a linear least-squares estimator, an iteratively reweighted least-squares estimator, and a non-linear least-squares technique. In general, the non-linear least-squares technique performs best, but in some situations a linear estimator could in theory be constructed that would outperform it. By eliminating the need to measure angles, trilateration facilitates the implementation of fully automated real-time positioning systems similar to the global positioning system (GPS). The methods presented in this paper are tested in the context of a realistic positioning problem that was posed by the Thunder Basin Coal Company in Wright, Wyoming.
---
paper_title: Fundamental properties and performance of conventional bearings-only target motion analysis

paper_content:

This paper considers the problem of estimating the position and velocity of an object from noise corrupted bearing measurements obtained by a single moving observation platform. The process is inherently nonlinear and exhibits unusual observability properties that are geometry-dependent. A maximum likelihood estimate (MLE) of the target motion analysis solution is developed and its performance analyzed. A comparison is drawn between the MLE and two previously reported methods, a nonlinear modified-instrumental variable estimate (MIV) and the pseudo-linear estimate (PLE). Both the MIV and PLE are shown to derive from approximations to the nonlinear measurement equation and therefore share some common properties with the MLE. The limits on performance that can be expected from processing bearing data are detailed. Specifically, for long range-to-baseline geometries, approximate expressions for the Cramer-Rao bound are derived. Extension of the results to the practical filters approximately predicts numerically observed behavior. For less restrictive geometries, bounds are presented. Incorporation of a target speed constraint on the MLE results in a transition to a lower dimensional problem as noise level and range increases. Monte Carlo experimental results are presented and the improvements realized by the MLE techniques are evident.
---
paper_title: Bearings-only and Doppler-bearing tracking using instrumental variables

paper_content:

In bearings-only tracking (BOT) or Doppler and bearing tracking (DBT), both common passive sonar problems, the measurement equations are nonlinear. To apply the Kalman filter, it is necessary either to linearize the equations or to embed the nonlinearities into the noise terms. The former sometimes leads to filter divergence, while the latter produces biased estimates. A formulation of BOT and DBT which has a constant state vector and simplifies the tracking problem to one of constant parameter estimation is given. The solution is by the instrumental variable method. The instrumental variables are obtained from predictions based on past measurements and are therefore independent of the present noisy measurements. The result is a recursive unbiased estimator. The theoretical developments are verified by simulation, which also shows that the formulation leads to near optimal estimators whose errors are close to the Cramer-Rao lower bound (CRLB). >
---
paper_title: Performance analysis of bearing-only target location algorithms

paper_content:

The performance of two well-known bearing-only location techniques, the maximum likelihood (ML) and the Stansfield estimators, is examined. Analytical expressions are obtained for the bias and the covariance matrix of the estimation error, which permit performance comparison for any case of interest. It is shown that the Stansfield algorithm provides biased estimates even for large numbers of measurements, in contrast with the ML method. The RMS error of the Stansfield technique is not necessarily larger than the RMS of the ML technique. However, it is shown that the ML technique is superior to the Stansfield method when the number of measurements is large enough. Simulation results verify the predicted theoretical performance. >
---
paper_title: On the bias of linear least squares algorithms for passive target localization

paper_content:

The paper derives analytical bias expressions for the least squares bearings-only target localization algorithms. A detailed analysis of the interplay between the target localization geometry and the estimation bias is provided for the cases of elliptical and linear observer trajectories. It is observed that the estimation bias is proportional to the distance between the target and the centre of mass of the observer positions. The effect of the localization geometry parameters on the estimation bias is illustrated analytically and by way of numerical examples. The theoretical findings of the paper are backed up with simulation studies.
---
paper_title: A Novel Location-Penalized Maximum Likelihood Estimator for Bearing-Only Target Localization

paper_content:

In this paper, we present a location-penalized maximum likelihood (LPML) estimator for bearing only target localization. We develop a new penalized maximum likelihood cost function by transforming the variables of target position and bearings. The new penalized likelihood function can also be recognized as a posterior distribution under a Bayesian framework by penalizing a prior. We give analysis of the asymptotic properties and show that both traditional bearing maximum likelihood (TBML) and LPML estimators are asymptotically efficient estimators. To compare the performances of the TBML and LPML estimators, we analyze the Cramer-Rao lower bound (CRLB) of the two estimators and show that the bound of the LPML estimator is lower than that of the TBML estimator. Extensive simulations are performed. It is observed that the new LPML algorithm consistently outperforms other well-known algorithms. Field experiments are also conducted by applying this method to localize a vehicle using real-world data acquired by an acoustic array sensor network. The new LPML algorithm demonstrates superior performance in all the field experiments.
---
paper_title: Bearings-only target localization using total least squares

paper_content:

A total least-squares (TLS) algorithm is developed for two-dimensional location estimation of a stationary target by using only passive bearing measurements of the target. This problem has been studied extensively for several decades and has applications in electronic warfare, surveillance, passive sonar, interference location and suppression, and so forth. The nonlinear nature of the estimation problem poses a number of challenges related to complexity, convergence and estimation bias. After a critical review of the least-squares (LS) algorithms, a TLS estimation algorithm is developed based on the method of orthogonal vectors with the advantage of simplicity and reduced bias in the presence of bearing noise and observer position errors. A constrained TLS (CTLS) algorithm is also developed to improve the estimation accuracy, especially in the case of large measurement errors. Numerical examples are provided to compare the performance of the TLS and CTLS algorithms with the LS target localization algorithms, viz. the maximum likelihood estimator, Stansfield estimator and the method of orthogonal vectors.
---
paper_title: Maximum likelihood methods for bearings-only target localization

paper_content:

We develop four maximum likelihood (ML) methods to localize a moving target using a network of acoustical sensor arrays. Each array transmits a direction-of-arrival (DOA) estimate to a central processor, which employs one of the localization techniques. The four ML approaches use different target signal models where the time retardation factor for the target position and the degradation of the target signal through the air may or may not be included in the model. We compare these methods along with a linear least squares approach through a number of simulations at various signal to noise levels.
---
paper_title: Bearing-Only Localization using Geometrically Constrained Optimization

paper_content:

We examine the problem of optimal bearing-only localization of a single target using synchronous measurements from multiple sensors. We approach the problem by forming geometric relationships between the measured parameters and their corresponding errors in the relevant emitter localization scenarios. Specifically, we derive a geometric constraint equation on the measurement errors in such a scenario. Using this constraint, we formulate the localization task as a constrained optimization problem that can be performed on the measurements in order to provide the optimal values such that the solution is consistent with the underlying geometry. We illustrate and confirm the advantages of our approach through simulation, offering detailed comparison with traditional maximum likelihood (TML) estimation.
---
paper_title: Localizing multiple audio sources in a wireless acoustic sensor network

paper_content:

In this work, we propose a grid-based method to estimate the location of multiple sources in a wireless acoustic sensor network, where each sensor node contains a microphone array and only transmits direction-of-arrival (DOA) estimates in each time interval, reducing the transmissions to the central processing node. We present new work on modeling the DOA estimation error in such a scenario. Through extensive, realistic simulations, we show that our method outperforms other state-of-the-art methods, in both accuracy and complexity. We also present localization results of real recordings in an outdoor cell of a sensor network. HighlightsWe examine localization in a WASN where each node transmits DOA estimates.We perform DOA estimation error modeling and examine the merging of nearby sources.We present a real-time low-complexity method for localization of multiple sources.Results indicate the advantages of our method in accuracy/computational complexity.We present localization results of real recordings in an outdoor cell of a sensor network.
---
paper_title: Bias compensation for the bearings-only pseudolinear target track estimator

paper_content:

The bearings-only pseudolinear target track estimator is known to suffer from severe bias problems. This paper presents a bias analysis for the pseudolinear estimator and develops a method of bias compensation, resulting in a closed-form reduced-bias pseudolinear estimator. The reduced-bias estimator is then incorporated into an instrumental variable estimator to produce asymptotically unbiased target motion parameter estimates. Unlike batch iterative estimators, the proposed instrumental variable estimator has a closed-from solution and therefore avoids the convergence problems associated with iterative estimators. The performance of the proposed instrumental variable estimator is illustrated by way of simulation examples and is shown to be almost identical to that of the computationally more demanding iterative maximum likelihood estimator.
---
paper_title: Reducing the bias of a bearings-only TLS target location estimator through geometry translations

paper_content:

Despite its simplicity, the pseudolinear estimator for bearings-only target localization is known to suffer from severe estimation bias. To overcome this problem, the method of total least squares (TLS) can be employed which attempts to correct errors not only in the data vector but also in the measurement matrix. The paper examines the relationship between the target localization geometry and the TLS estimation bias for the target location. The paper shows that translations of the target localization geometry through simple shift and/or rotation operations do affect the bias of the TLS estimator and can be exploited to reduce the TLS estimation bias significantly.
---
paper_title: Passive emitter localization using weighted instrumental variables

paper_content:

The linear least-squares algorithms for emitter localization such as the pseudolinear estimator are known to exhibit large estimation bias because of the correlation between the measurement matrix and the bearing noise. The paper presents a new bearings-only emitter localization algorithm with a closed-form solution that overcomes this bias by making use of instrumental variables obtained from a biased location estimate. By way of computer simulations, the new algorithm is shown to outperform the pseudolinear estimator while having a performance identical to that of the computationally more expensive maximum likelihood estimator.
---
paper_title: Localizing multiple audio sources from DOA estimates in a wireless acoustic sensor network

paper_content:

In this work we propose a method to estimate the position of multiple sources in a wireless acoustic sensor network, where each sensor node only transmits direction-of-arrival (DOA) estimates each time interval, minimizing the transmissions to the processing node. Our method is based on the intersection of DOA estimates with outlier removal, and as such is very computationally efficient. We explore the performance of our method through extensive simulations and real measurements.
---
paper_title: ON THE WINDOW-DISJOINT-ORTHOGONALITY OF SPEECH SOURCES IN REVERBERANT HUMANOID SCENARIOS

paper_content:

Many speech source separation approaches are based on the assumption of orthogonality of speech sources in the time-frequency domain. The target speech source is demixed from the mixture by applying the ideal binary mask to the mixture. The time-frequency orthogonality of speech sources is investigated in detail only for anechoic and artificially mixed speech mixtures. This paper evaluates how the orthogonality of speech sources decreases when using a realistic reverberant humanoid recording setup and indicates strategies to enhance the separation capabilities of algorithms based on ideal binary masks under these conditions. It is shown that the SIR of the target source demixed from the mixture using the ideal binary mask decreases by approximately 3 dB for reverberation times of T60 = 0.6 s opposed to the anechoic scenario. For humanoid setups, the spatial distribution of the sources and the choice of the correct ear channel introduces differences in the SIR of further 3 dB, which leads to specific strategies to choose the best channel for demixing.
---
paper_title: ESPRIT-estimation of signal parameters via rotational invariance techniques

paper_content:

An approach to the general problem of signal parameter estimation is described. The algorithm differs from its predecessor in that a total least-squares rather than a standard least-squares criterion is used. Although discussed in the context of direction-of-arrival estimation, ESPRIT can be applied to a wide variety of problems including accurate detection and estimation of sinusoids in noise. It exploits an underlying rotational invariance among signal subspaces induced by an array of sensors with a translational invariance structure. The technique, when applicable, manifests significant performance and computational advantages over previous algorithms such as MEM, Capon's MLM, and MUSIC. >
---
paper_title: Source localization for multiple speech sources using low complexity non-parametric source separation and clustering

paper_content:

This article presents a new method for localization of multiple concurrent speech sources that relies on simultaneous blind signal separation and direction of arrival (DOA) estimation, as well as a method to solve the intersection point selection problem that arises when locating multiple speech sources using multiple sensor arrays. The proposed method is based on a low complexity non-parametric blind signal separation method, making is suitable for real-time applications on embedded platforms. On top of reduced complexity in comparison to a previously presented method, the DOA estimation accuracy is also improved. Evaluation of the performance is done with both real recording and simulations, and a real-time prototype of the proposed method has been implemented on a DSP platform to evaluate the computational and the memory complexities in a real application.
---
paper_title: Maximum a Posteriori Binary Mask Estimation for Underdetermined Source Separation Using Smoothed Posteriors

paper_content:

Sound source separation has become a topic of intensive research in the last years. The research effort has been specially relevant for the underdetermined case, where a considerable number of sparse methods working in the time-frequency (T-F) domain have appeared. In this context, although binary masking seems to be a preferred choice for source demixing, the estimated masks differ substantially from the ideal ones. This paper proposes a maximum a posteriori (MAP) framework for binary mask estimation. To this end, class-conditional source probabilities according to the observed mixing parameters are modeled via ratios of dependent Cauchy distributions while source priors are iteratively calculated from the observed histograms. Moreover, spatially smoothed posteriors in the T-F domain are proposed to avoid noisy estimates, showing that the estimated masks are closer to the ideal ones in terms of objective performance measures.
---
paper_title: Multiple-source localization using line-of-bearing measurements: Approaches to the data association problem

paper_content:

In this paper, we consider the data association problem of multiple-source localization using line-of-bearing measurements. More specifically, we propose two approaches that circumvent the very high complexity of a brute-force solution to this problem. The first approach relies on statistical clustering of the intersections of line-of-bearing measurements and the second approach exploits cyclostationary features of the received signals to allow for line-of-bearing measurement separation based on each signalpsilas transmission modes. These two proposed approaches have reduced time and computational complexity, while maintaining a reasonable amount of accuracy, and are of great value for dense environments with large numbers of sensors and/or targets.
---
paper_title: Passive acoustic source localization for video camera steering

paper_content:

A multi-input one-step least-squares (OSLS) algorithm for passive source localization is proposed. It is shown that the OSLS algorithm is mathematically equivalent to the so-called spherical interpolation (SI) method but with less computational complexity. The OSLS/SI method uses spherical equations (instead of hyperbolic equations) and solves them in a least-squares sense. Based on the adaptive eigenvalue decomposition time delay estimation method previously proposed by the same authors and the OSLS source localization algorithm, a real-time passive source localization system for video camera steering is presented. The system demonstrates many desirable features such as accuracy, portability, and robustness.
---
paper_title: m-best S-D assignment algorithm with application to multitarget tracking

paper_content:

In this paper we describe a novel data association algorithm, termed m-best S-D, that determines in O(mSkn/sup 3/) time (m assignments, S/spl ges/3 lists of size n, k relaxations) the (approximately) m-best solutions to an S-D assignment problem. The m-best S-D algorithm is applicable to tracking problems where either the sensors are synchronized or the sensors and/or the targets are very slow moving. The significance of this work is that the m-best S-D assignment algorithm (in a sliding window mode) can provide for an efficient implementation of a suboptimal multiple hypothesis tracking (MHT) algorithm by obviating the need for a brute force enumeration of an exponential number of joint hypotheses. We first describe the general problem for which the m-best S-D applies. Specifically, given line of sight (LOS) (i.e., incomplete position) measurements from S sensors, sets of complete position measurements are extracted, namely, the 1st, 2nd, ..., mth best (in terms of likelihood) sets of composite measurements are determined by solving a static S-D assignment problem. Utilizing the joint likelihood functions used to determine the m best S-D assignment solutions, the composite measurements are then quantified with a probability of being correct using a JPDA-like (joint probabilistic data association) technique. Lists of composite measurements from successive scans, along with their corresponding probabilities, are used in turn with a state estimator in a dynamic 2-D assignment algorithm to estimate the states of moving targets over time. The dynamic assignment cost coefficients are based on a likelihood function that incorporates the "true" composite measurement probabilities obtained from the (static) m-best S-D assignment solutions. We demonstrate the merits of the m-best S-D algorithm by applying it to a simulated multitarget passive sensor track formation and maintenance problem, consisting of multiple time samples of LOS measurements originating from multiple (S=7) synchronized high frequency direction finding sensors.
---
paper_title: A generalized S-D assignment algorithm for multisensor-multitarget state estimation

paper_content:

We develop a new algorithm to associate measurements from multiple sensors to identify the real targets in a surveillance region, and to estimate their states at any given time. The central problem in a multisensor-multitarget state estimation problem is that of data association-the problem of determining from which target, if any, a particular measurement originated. The data association problem is formulated as a generalized S-dimensional (S-D) assignment problem, which is NP-hard for S/spl ges/3 sensor scans (i.e., measurement lists). We present an efficient and recursive generalized S-D assignment algorithm (S/spl ges/3) employing a successive Lagrangian relaxation technique, with application to the localization of an unknown number of emitters using multiple high frequency direction finder sensors (S=3, 5, and 7).
---
paper_title: Bearings-only target localization for an acoustical unattended ground sensor network

paper_content:

This paper extends our development of acoustical bearings-only target localization for the case of multiple moving targets. The resulting techniques can be used to locate and track targets traveling through a network of acoustical sensor arrays. Each array computes and transmits multiple direction-of-arrival (DOA) estimates to a central processor, which employs the target localization technique. In previous work, we developed ML techniques that may or may not account for the fact that a bearing measurement points to the location of a moving target at a retarded time. By inserting a simple bearings association computation in the ML methods, we define quasi-ML techniques that can estimate the location and velocity of multiple targets using multiple bearing estimates per a sensor array.
---
paper_title: Factorial models and refiltering for speech separation and denoising

paper_content:

This paper proposes the combination of several ideas, some old and some new, from machine learning and speech processing. We review the max approximation to log spectrograms of mixtures, show why this motivates a “refiltering” approach to separation and denoising, and then describe how the process of inference in factorial probabilistic models performs a computation useful for deriving the masking signals needed in refiltering. A particularly simple model, factorial-max vector quantization (MAXVQ), is introduced along with a branch-and-bound technique for efficient exact inference and applied to both denoising and monaural separation. Our approach represents a return to the ideas of Ephraim, Varga and Moore but applied to auditory scene analysis rather than to speech recognition. 1. Sparsity & Redundancy in Spectrograms 1.1. The Log-MaxApproximation When two clean speech signals are mixed additively in the time domain, what is the relationship between the individual log spectrograms of the sources and the log spectrogram of the mixture? Unless the sources are highly dependent (synchronized), the spectrogram of the mixture is almost exactly the maximum of the individual spectrograms, with the maximum operating over small time-frequency regions (fig. 2). This amazing fact, first noted by Roger Moore in 1983, comes from the fact that unless e1 and e2 are both large and almost equal, log(e1 + e2) ≈ max(log e1, log e2) (fig. 1a). The sparse nature of the speech code across time and frequency is the key to the practical usefulness of this approximation: most narrow frequency bands carry substantial energy only a small fraction of the time and thus it is rare that two independent sources inject large amounts of energy into the same subband at the same time. (Figure 1b shows a plot of the relative energy of two simultaneous speakers in a narrow subband; most of the time at least one of the two sources shows negligible power.) 1.2. Masking and Refiltering Fortunately, the speech code is also redundant across timefrequency. Different frequency bands carry, to a certain extent, independent information and so if information in some bands is suppressed or masked, even for significant durations, other bands can fill in. (A similar effect occurs over time: if brief sections of the signal are obscured, even across all bands, the speech is still intelligible; while also useful, we do not exploit this here.) This is partly why humans perform so well on many monaural speech separation and denoising tasks. When we solve the cocktail party problem or recognize degraded speech, we are doing structural analysis, or a kind of “perceptual grouping” on the incoming sound. There is substantial evidence that the appropriate subparts of an audio signal for use in grouping may be narrow frequency bands over short times. To generate these parts computationally, we can perform multiband analysis – break the original speech signal y(t) into many subband signals bi(t) each lo g e2 ma
---
paper_title: A new relaxation algorithm and passive sensor data association

paper_content:

The static problem of associating measurements at a given time from three angle-only sensors in the presence of clutter, missed detections, and an unknown number of targets is addressed. The measurement-target association problem is formulated as one of maximizing the joint likelihood function of the measurement partition. Mathematically, this formulation leads to a generalization of the 3-D assignment (matching) problem, which is known to be NP hard. The solution to the optimization problem developed is a Lagrangian relaxation technique that successively solves a series of generalized two-dimensional (2-D) assignment problems. The algorithm is illustrated by several application examples. >
---
paper_title: Real-Time Multiple Sound Source Localization and Counting Using a Circular Microphone Array

paper_content:

In this work, a multiple sound source localization and counting method is presented, that imposes relaxed sparsity constraints on the source signals. A uniform circular microphone array is used to overcome the ambiguities of linear arrays, however the underlying concepts (sparse component analysis and matching pursuit-based operation on the histogram of estimates) are applicable to any microphone array topology. Our method is based on detecting time-frequency (TF) zones where one source is dominant over the others. Using appropriately selected TF components in these “single-source” zones, the proposed method jointly estimates the number of active sources and their corresponding directions of arrival (DOAs) by applying a matching pursuit-based approach to the histogram of DOA estimates. The method is shown to have excellent performance for DOA estimation and source counting, and to be highly suitable for real-time applications due to its low complexity. Through simulations (in various signal-to-noise ratio conditions and reverberant environments) and real environment experiments, we indicate that our method outperforms other state-of-the-art DOA and source counting methods in terms of accuracy, while being significantly more efficient in terms of computational complexity.
---
paper_title: Localizing multiple audio sources in a wireless acoustic sensor network

paper_content:

In this work, we propose a grid-based method to estimate the location of multiple sources in a wireless acoustic sensor network, where each sensor node contains a microphone array and only transmits direction-of-arrival (DOA) estimates in each time interval, reducing the transmissions to the central processing node. We present new work on modeling the DOA estimation error in such a scenario. Through extensive, realistic simulations, we show that our method outperforms other state-of-the-art methods, in both accuracy and complexity. We also present localization results of real recordings in an outdoor cell of a sensor network. HighlightsWe examine localization in a WASN where each node transmits DOA estimates.We perform DOA estimation error modeling and examine the merging of nearby sources.We present a real-time low-complexity method for localization of multiple sources.Results indicate the advantages of our method in accuracy/computational complexity.We present localization results of real recordings in an outdoor cell of a sensor network.
---
paper_title: Localization of Acoustic Sources Through the Fitting of Propagation Cones Using Multiple Independent Arrays

paper_content:

In this paper, we propose a novel acoustic source localization method that accommodates the general scenario of multiple independent microphone arrays. The method is based on a 3-D parameter space defined by the 2-D spatial location of a source and the range difference extracted from the time difference of arrival (TDOA). In this space, the set of points that correspond to a given range lie on a circle that expand as the range increases, forming a cone whose apex is the actual location of the source. In this parameter space, the lack of synchronization between arrays results in the fact that clusters of data associated to individual arrays are free to shift along the range axis. The cone constraint, in fact, enables the realignment of such clusters while positioning the cone vertex (source location), thus resulting in a joint data re-synchronization and source localization. We also propose a novel and general analysis methodology for swiftly assessing the localization error as a function of the TDOA uncertainties, which is remarkably accurate for small localization bias. With the aid of this method, simulations and experiments on real data, we show that the cone-fitting process offers excellent localization accuracy in the scenario of multiple unsynchronized arrays, as well as in simpler single-array scenarios, also in comparison with state-of-the-art techniques. We also show that the proposed method offers the desired flexibility for adapting to arbitrary geometries of microphone clusters.
---
paper_title: Addressing the data-association problem for multiple sound source localization using DOA estimates

paper_content:

In this paper, we consider the data association problem that arises when localizing multiple sound sources using direction of arrival (DOA) estimates from multiple microphone arrays. In such a scenario, the association of the DOAs across the arrays that correspond to the same source is unknown and must be found for accurate localization. We present an association algorithm that finds the correct DOA association to the sources based on features extracted for each source that we propose. Our method results in high association and localization accuracy in scenarios with missed detections, reverberation, and noise and outperforms other recently proposed methods.
---
paper_title: Towards wireless acoustic sensor networks for location estimation and counting of multiple speakers in real-life conditions

paper_content:

Speaker localization and counting in real-life conditions remains a challenging task. The computational burden, transmission usage and synchronization issues pose several limitations. Moreover, the physical characteristics of real speakers in terms of directivity pattern and orientation, as well as restrictions in the microphone array positioning, which commonly have to be placed close to walls, deteriorate the localization performance. In this paper, we propose a localization and counting method that accounts for the adjacent wall reflections and evaluate it using a dataset of real recorded signals of actual speakers that we collected. Our dataset is publicly available to foster further investigation towards localization in real-life scenarios.
---
paper_title: Informed Spatial Filtering for Sound Extraction Using Distributed Microphone Arrays

paper_content:

Hands-free acquisition of speech is required in many human-machine interfaces and communication systems. The signals received by integrated microphones contain a desired speech signal, spatially coherent interfering signals, and background noise. In order to enhance the desired speech signal, state-of-the-art techniques apply data-dependent spatial filters which require the second order statistics (SOS) of the desired signal, the interfering signals and the background noise. As the number of sources and the reverberation time increase, the estimation accuracy of the SOS deteriorates, often resulting in insufficient noise and interference reduction. In this paper, a signal extraction framework with distributed microphone arrays is developed. An expectation maximization (EM)-based algorithm detects the number of coherent speech sources and estimates source clusters using time-frequency (TF) bin-wise position estimates. Subsequently, the second order statistics (SOS) are estimated using bin-wise speech presence probability (SPP) and a source probability for each source. Finally, a desired source is extracted using a minimum variance distortionless response (MVDR) filter, a multichannel Wiener filter (MWF) and a parametric multichannel Wiener filter (PMWF). The same framework can be employed for source separation, where a spatial filter is computed for each source considering the remaining sources as interferers. Evaluation using simulated and measured data demonstrates the effectiveness of the framework in estimating the number of sources, clustering, signal enhancement, and source separation.
---
paper_title: Multiple sound source location estimation and counting in a wireless acoustic sensor network

paper_content:

In this work, we consider the multiple sound source location estimation and counting problem in a wireless acoustic sensor network, where each sensor consists of a microphone array. Our method is based on inferring a location estimate for each frequency of the captured signals. A clustering approach-where the number of clusters (i.e., sound sources) is also an unknown parameter-is then employed to decide on the number of sources and their locations. The efficiency of our proposed method is evaluated through simulations and real recordings in scenarios with up to three simultaneous sound sources for different signal-to-noise ratios and reverberation times.
---
paper_title: Simplified acoustic localization by linear arrays for wireless sensor networks

paper_content:

The application of wireless sensor networks (WSN) for the task of acoustic localization provides great opportunities for distributed cooperative tracking of sound sources in large areas. However WSNs are significantly more limited in terms of computational resources and power than typical computer systems. Therefore the methods applied for acoustic localization in WSN must be optimized for minimal resource consumption. This paper builds on the advances of Steered Response Power with Phase Transform (SRP-PHAT) optimization and proposes a further simplification in terms of additional minimization of the initial search volume. By using several linear microphone arrays we are able to estimate the initial region of sound source and reduce the number of computations by at least one order of magnitude. The results of several experiments on real signals confirm the achieved improvements.
---
paper_title: Optimized Acoustic Localization with SRP-PHAT for Monitoring in Distributed Sensor Networks

paper_content:

Acoustic localization by means of sensor arrays has a variety of applications, from conference telephony to environment monitoring. Many of these tasks are appealing for implementation on embedded systems, however large dataflows and computational complexity of multi-channel signal processing impede the development of such systems. This paper proposes a method of acoustic localization targeted for distributed systems, such as Wireless Sensor Networks (WSN). The method builds on an optimized localization algorithm of Steered Response Power with Phase Transform (SRP-PHAT) and simplifies it further by reducing the initial search region, in which the sound source is contained. The sensor array is partitioned into sub-blocks, which may be implemented as independent nodes of WSN. For the region reduction two approaches are handled. One is based on Direction of Arrival estimation and the other - on multilateration. Both approaches are tested on real signals for speaker localization and industrial machinery monitoring applications. Experiment results indicate the method’s potency in both these tasks.
---
paper_title: A two-stage approach to 2D DOA estimation for a compact circular microphone array

paper_content:

Microphone arrays and, specifically, circular arrays have been used for sound source localization and multimedia applications for more than a decade. In recent years the development of compact arrays for implementation in Wireless Sensor Networks (WSN) has risen in popularity. This paper considers a 2D Direction of Arrival (DOA) estimation method for a compact circular array, equipped with additional vertically placed microphones. The proposed method is aimed at reducing the computational cost of DOA estimation for implementation on embedded hardware of WSN smart sensors. The method is compared with a well known localization algorithm of SRP-PHAT and is proven to provide adequate DOA estimates, while being more computationally effective.
---
paper_title: Robust Localization in Reverberant Rooms

paper_content:

Talker localization with microphone arrays has received significant attention lately as a means for the automated tracking of individuals in an enclosure and as a necessary component of any general purpose speech capture system. Several algorithmic approaches are available for speech source localization with multi-channel data. This chapter summarizes the current field and comments on the general merits and shortcomings of each genre. A new localization method is then presented in detail. By utilizing key features of existing methods, this new algorithm is shown to be significantly more robust to acoustical conditions, particularly reverberation effects, than the traditional localization techniques in use today.
---
paper_title: A Modified SRP-PHAT Functional for Robust Real-Time Sound Source Localization With Scalable Spatial Sampling

paper_content:

The Steered Response Power - Phase Transform (SRP-PHAT) algorithm has been shown to be one of the most robust sound source localization approaches operating in noisy and reverberant environments. However, its practical implementation is usually based on a costly fine grid-search procedure, making the computational cost of the method a real issue. In this letter, we introduce an effective strategy that extends the conventional SRP-PHAT functional with the aim of considering the volume surrounding the discrete locations of the spatial grid. As a result, the modified functional performs a full exploration of the sampled space rather than computing the SRP at discrete spatial positions, increasing its robustness and allowing for a coarser spatial grid. To this end, the Generalized Cross-Correlation (GCC) function corresponding to each microphone pair must be properly accumulated according to the defined microphone setup. Experiments carried out under different acoustic conditions confirm the validity of the proposed approach.
---
paper_title: Closed-form solutions for robust acoustic sensor localization

paper_content:

This paper deals with the localization of acoustic sensors based on signals emitted by loudspeakers at known positions. In particular, a model for distortions in time-of-flight (TOF) estimates applicable to the sensor localization problem is presented along with closed-form solutions with low computational cost. The proposed techniques are able to approximate the sensor position even when the TOFs are corrupted by an unknown delay, there is a sampling frequency mismatch between the A/D and D/A converters associated with sensor and loudspeakers, and the speed of sound is unknown. Simulations and an experiment on real data demonstrate that the proposed methods are able to estimate sensor positions with less than 2 cm of error in the evaluated scenarios.
---
paper_title: On the performance of multi-GPU-based expert systems for acoustic localization involving massive microphone arrays

paper_content:

Expert system for passive sound source localization that makes use of multiple GPUs.Fine spatial grids and a high number of microphones provide excellent localization.GPU resources for managing a large expert system are described.A complete set of simulations evaluates the performance of the expert system.Excellent localization accuracy is achieved even in adverse environments. Sound source localization is an important topic in expert systems involving microphone arrays, such as automatic camera steering systems, human-machine interaction, video gaming or audio surveillance. The Steered Response Power with Phase Transform (SRP-PHAT) algorithm is a well-known approach for sound source localization due to its robust performance in noisy and reverberant environments. This algorithm analyzes the sound power captured by an acoustic beamformer on a defined spatial grid, estimating the source location as the point that maximizes the output power. Since localization accuracy can be improved by using high-resolution spatial grids and a high number of microphones, accurate acoustic localization systems require high computational power. Graphics Processing Units (GPUs) are highly parallel programmable co-processors that provide massive computation when the needed operations are properly parallelized. Emerging GPUs offer multiple parallelism levels; however, properly managing their computational resources becomes a very challenging task. In fact, management issues become even more difficult when multiple GPUs are involved, adding one more level of parallelism. In this paper, the performance of an acoustic source localization system using distributed microphones is analyzed over a massive multichannel processing framework in a multi-GPU system. The paper evaluates and points out the influence that the number of microphones and the available computational resources have in the overall system performance. Several acoustic environments are considered to show the impact that noise and reverberation have in the localization accuracy and how the use of massive microphone systems combined with parallelized GPU algorithms can help to mitigate substantially adverse acoustic effects. In this context, the proposed implementation is able to work in real time with high-resolution spatial grids and using up to 48 microphones. These results confirm the advantages of suitable GPU architectures in the development of real-time massive acoustic signal processing systems.
---
paper_title: A Fast Microphone Array SRP-PHAT Source Location Implementation using Coarse-To-Fine Region Contraction(CFRC)

paper_content:

Most real microphone-array applications require sound sources to be localized in a noisy, reverberant environment. In such conditions, the steered response power using the phase transform (SRP-PHAT) has been shown to be more robust than faster, two-stage, time-difference of arrival methods. The complication is that the SRP-PHAT space has many local extrema which has required computationally costly grid-search methods. In this paper, we introduce the use of coarse-to-fine region contraction (CFRC) to make computing the SRP practical. We compare CFRC cost and performance to that of using stochastic region contraction (SRC), a method we presented recently at ICASSP 2007, which showed the computation for SRC was reduced by about 3 orders of magnitude from a comparatively fine grid-search. Results here from real data from human talkers show that CFRC costs about the same as SRC overall, but requires only about 63% of SRC's cost under very noisy conditions.
---
paper_title: A Real-Time SRP-PHAT Source Location Implementation using Stochastic Region Contraction(SRC) on a Large-Aperture Microphone Array

paper_content:

In most microphone array applications, it is essential to localize sources in a noisy, reverberant environment. It has been shown that computing the steered response power (SRP) is more robust than faster, two-stage, direct time-difference of arrival methods. The problem with computing SRP is that the SRP space has many local maxima and thus computationally-intensive grid-search methods are used to find a global maximum. Grid search is too expensive for a real-time system. Several papers have addressed this issue. In this paper we propose using stochastic region contraction (SRC) to make computing the SRP practical. We discuss one important SRP method, computing it from the phase transform (SRP-PHAT), review SRC, and show the computational saving. Using real data from human talkers, we show that SRC saves computation by more than two orders of magnitude with almost no loss in accuracy.
---
paper_title: Proposal and validation of an analytical generative model of SRP-PHAT power maps in reverberant scenarios

paper_content:

The algorithms for acoustic source localization based on PHAT filtering have been profusely used with good results in reverberant and noisy environments. However, there are very few studies that give a formal explanation of their robustness, most of them providing just an empirical validation or showing results on simulated data. In this work we present a novel analytical model for predicting the behavior of both the SRP-PHAT power maps and the GCC-PHAT functions. The results show that they are only affected by the signal bandwidth, the microphone array topology, and the room geometry, being independent of the spectral content of the received signal. The proposed model is shown to be valid in reverberant environments and under far and near field conditions. Using this result, an analysis study on how the aforementioned factors affect the SRP-PHAT power maps is presented providing well supported theoretical and practical considerations. The model validation is based on both synthetic and real data, obtaining in all cases a high accuracy of the model to reproduce the SRP-PHAT power maps, both in anechoic and non-anechoic scenarios, becoming thus an excellent tool to be exploited for the improvement of real world relevant applications related to acoustic localization. HighlightsA novel parametric analytical model to predict SRP-PHAT power maps is formulated.An exhaustive evaluation is done on both synthetic and real data.Results show high accuracy for very different acoustical and geometrical conditions.The paper also addresses practical issues in the model implementation.
---
paper_title: A Steered-Response Power Algorithm Employing Hierarchical Search for Acoustic Source Localization Using Microphone Arrays

paper_content:

The localization of a speaker inside a closed environment is often approached by real-time processing of multiple audio signals captured by a set of microphones. One of the leading related methods for sound source localization, the steered-response power (SRP), searches for the point of maximum power over a spatial grid. High-accuracy localization calls for a dense grid and/or many microphones, which tends to impractically increase computational requirements. This paper proposes a new method for sound source localization (called H-SRP), which applies the SRP approach to space regions instead of grid points. This arrangement makes room for the use of a hierarchical search inspired by the branch-and-bound paradigm, which is guaranteed to find the global maximum in anechoic environments and shown experimentally to also work under reverberant conditions. Besides benefiting from the improved robustness of volume-wise search over point-wise search as to reverberation effects, the H-SRP attains high performance with manageable complexity. In particular, an experiment using a 16-microphone array in a typical presentation room yielded localization errors of the order of 7 cm, and for a given fixed complexity, competing methods' errors are two to three times larger.
---
paper_title: Parallel SRP-PHAT for GPUs

paper_content:

Abstract The steered response power phase transform (SRP-PHAT) is one of the widely used algorithms for sound source localization. Since it must examine a large number of candidate sound source locations, conventional SRP-PHAT approaches may not be used in real time. To overcome this problem, an effort was made previously to parallelize the SRP-PHAT on graphics processing units (GPUs). However, the full capacities of the GPU were not exploited since on-chip memory usage was not addressed. In this paper, we propose GPU-based parallel algorithms of the SRP-PHAT both in the frequency domain and time domain. The proposed methods optimize the memory access patterns of the SRP-PHAT and efficiently use the on-chip memory. As a result, the proposed methods demonstrate a speedup of 1276 times in the frequency domain and 80 times in the time domain compared to CPU-based algorithms, and 1.5 times in the frequency domain and 6 times in the time domain compared to conventional GPU-based methods.
---
paper_title: A steered response power iterative method for high-accuracy acoustic source localization.

paper_content:

Source localization using the steered response power (SRP) usually requires a costly grid-search procedure. To address this issue, a modified SRP algorithm was recently introduced, providing improved robustness when using coarser spatial grids. In this letter, an iterative method based on the modified SRP is presented. A coarse spatial grid is initially evaluated with the modified SRP, selecting the point with the highest accumulated value. Then, its corresponding volume is iteratively decomposed by using a finer spatial grid. Experiments have shown that this method provides almost the same accuracy as the fine-grid search with a substantial reduction of functional evaluations.
---
paper_title: A Modified SRP-PHAT Functional for Robust Real-Time Sound Source Localization With Scalable Spatial Sampling

paper_content:

The Steered Response Power - Phase Transform (SRP-PHAT) algorithm has been shown to be one of the most robust sound source localization approaches operating in noisy and reverberant environments. However, its practical implementation is usually based on a costly fine grid-search procedure, making the computational cost of the method a real issue. In this letter, we introduce an effective strategy that extends the conventional SRP-PHAT functional with the aim of considering the volume surrounding the discrete locations of the spatial grid. As a result, the modified functional performs a full exploration of the sampled space rather than computing the SRP at discrete spatial positions, increasing its robustness and allowing for a coarser spatial grid. To this end, the Generalized Cross-Correlation (GCC) function corresponding to each microphone pair must be properly accumulated according to the defined microphone setup. Experiments carried out under different acoustic conditions confirm the validity of the proposed approach.
---
paper_title: Steered Response Power Localization of Acoustic Passband Signals

paper_content:

The vast majority of localization approaches using phase transform (PHAT) consider that the sources of interest are wideband low-pass sources. While this may be the usual case for common audio signals such as speech, PHAT methods are affected negatively by modulation artifacts when the sources to be localized are passband signals. In these cases, steered response power PHAT localization becomes less robust. This letter analyzes the form of generalized cross-correlation functions with PHAT when passband acoustic signals are considered, proposing approaches for increasing the localization performance through the mitigation of these negative effects.
---
paper_title: Microphone array position calibration by basis-point classical multidimensional scaling

paper_content:

Classical multidimensional scaling (MDS) is a global, noniterative technique for finding coordinates of points given their interpoint distances. We describe the algorithm and show how it yields a simple, inexpensive method for calibrating an array of microphones with a tape measure (or similar measuring device). We present an extension to the basic algorithm, called basis-point classical MDS (BCMDS), which handles the case when many of the distances are unavailable, thus yielding a technique that is practical for microphone arrays with a large number of microphones. We also show that BCMDS, when combined with a calibration target consisting of four synchronized sound sources, can be used for automatic calibration via time-delay estimation. We evaluate the accuracy of both classical MDS and BCMDS, investigating the sensitivity of the algorithms to noise and to the design parameters to yield insight as to the choice of those parameters. Our results validate the practical applicability of the algorithms, showing that errors on the order of 10-20 mm can be achieved in real scenarios.
---
paper_title: Position calibration of microphones and loudspeakers in distributed computing platforms

paper_content:

We present a novel algorithm to automatically determine the relative three-dimensional (3-D) positions of audio sensors and actuators in an ad-hoc distributed network of heterogeneous general purpose computing platforms such as laptops, PDAs, and tablets. A closed form approximate solution is derived, which is further refined by minimizing a nonlinear error function. Our formulation and solution accounts for the lack of temporal synchronization among different platforms. We compare two different estimators, one based on the time of flight and the other based on time difference of flight. We also derive an approximate expression for the mean and covariance of the implicitly defined estimator using the implicit function theorem and approximate Taylors' series expansion. The theoretical performance limits for estimating the sensor 3-D positions are derived via the Crame/spl acute/r-Rao bound (CRB) and analyzed, with respect to the number of sensors and actuators, as well as their geometry. We report extensive simulation results and discuss the practical details of implementing our algorithms in a real-life system.
---
paper_title: Microphone position and gain calibration for a large-aperture microphone array

paper_content:

Large-aperture microphone arrays have the potential for providing quality speech acquisition from multiple talkers over a large focal area for such applications as teleconferencing and speech-recognition input. The cost of computing is rapidly approaching the point at which these arrays will be practical in many common environments. However, an important issue is the calibration of an array. We discuss procedures to accurately determine both the coordinates in three-dimensions for the position of each microphone and the individual gains of each microphone/microphone channel. For the positions, we found that calibration by direct measurement, using a surveyor's transit, is simply too error prone, time consuming, and difficult for large arrays and is too inaccurate for small arrays. We have also seen that without the careful matching of inexpensive electret microphones, the channel sensitivities vary by as much as 6 dB and performance can be enhanced by suitable compensation. This paper describes new apparatus and techniques for automatic calibration using acoustic signals. Experimental results using both small and large-aperture microphone array systems show the acoustically-determined positions to be more consistent than the ones measured directly. Gain measurements are somewhat more difficult but gains can be found within 1-2 dB with reasonable care.
---
paper_title: Automatic position calibration of multiple microphones

paper_content:

We describe a method to determine automatically the relative three dimensional positions of multiple microphones using at least five loudspeakers in unknown positions. The only assumption we make is that there is a microphone which is very close to a loudspeaker. In our experimental setup, we attach one microphone to each loudspeaker. We derive the maximum likelihood estimator and the solution turns out to be a non-linear least squares problem. A closed form solution which can be used as the initial guess for the minimization routine is derived. We also derive an approximate expression for the covariance of the estimator using the implicit function theorem. Using this, we analyze the performance of the estimator with respect to the positions of the loudspeakers. The algorithm is validated using both Monte-Carlo simulations and a real-time experimental setup.
---
paper_title: Microphone Array Shape Calibration in Diffuse Noise Fields

paper_content:

This correspondence presents a microphone array shape calibration procedure for diffuse noise environments. The procedure estimates intermicrophone distances by fitting the measured noise coherence with its theoretical model and then estimates the array geometry using classical multidimensional scaling. The technique is validated on noise recordings from two office environments.
---
paper_title: BeepBeep: a high accuracy acoustic ranging system using COTS mobile devices

paper_content:

We present the design, implementation, and evaluation of BeepBeep, a high-accuracy acoustic-based ranging system. It operates in a spontaneous, ad-hoc, and device-to-device context without leveraging any pre-planned infrastructure. It is a pure software-based solution and uses only the most basic set of commodity hardware -- a speaker, a microphone, and some form of device-to-device communication -- so that it is readily applicable to many low-cost sensor platforms and to most commercial-off-the-shelf mobile devices like cell phones and PDAs. It achieves high accuracy through a combination of three techniques: two-way sensing, self-recording, and sample counting. The basic idea is the following. To estimate the range between two devices, each will emit a specially-designed sound signal ("Beep") and collect a simultaneous recording from its microphone. Each recording should contain two such beeps, one from its own speaker and the other from its peer. By counting the number of samples between these two beeps and exchanging the time duration information with its peer, each device can derive the two-way time of flight of the beeps at the granularity of sound sampling rate. This technique cleverly avoids many sources of inaccuracy found in other typical time-of-arrival schemes, such as clock synchronization, non-real-time handling, software delays, etc. Our experiments on two common cell phone models have shown that we can achieve around one or two centimeters accuracy within a range of more than ten meters, despite a series of technical challenges in implementing the idea.
---
paper_title: CDMA-based acoustic local positioning system for portable devices with multipath cancellation

paper_content:

Abstract This paper presents an acoustic local positioning system (ALPS) suitable for indoor positioning of portable devices such as smartphones or tablets, based on the transmission of high frequency CDMA-coded signals from a fixed network of beacons. The main novelty of the proposed ALPS is its capability to mitigate the effects of multipath propagation by performing an accurate estimation of the Line-of-Sight Time-of-Flights (LOS-TOF) through the Matching Pursuit algorithm. Signal detection, multipath cancellation and positioning estimation all take place within the portable device, which provides a graphical representation of the updated position in less than a second. The performance of the Matching Pursuit algorithm is analyzed in a real scenario and the results show that the proposed method is capable to retrieve the multipath-free System Availability under strong multipath conditions with SNR levels as low as 0 dB.
---
paper_title: Towards acoustic self-localization of ad hoc smartphone arrays

paper_content:

The advent of the smartphone in recent years opened new possibilities for the concept of ubiquitous computing. We propose to use multiple smartphones spontaneously assembled into an ad hoc microphone array as part of a teleconferencing system. The unknown spatial positions, the asynchronous sampling and the unknown time offsets between clocks of smartphones in the ad hoc array are the main problems for such an application as well as for almost all other acoustic signal processing algorithms. A maximum likelihood approach using time of arrival measurements of short calibration pulses is proposed to solve this self-localization problem. The global orientation of each phone, obtained by the means of nowadays common built-in geomagnetic compasses, in combination with the constant microphone-loudspeaker distance lead to a nonlinear optimization problem with a reduced dimensionality in contrast to former methods. The applicability of the proposed self-localization is shown in simulation and via recordings in a typical reverberant and noisy conference room.
---
paper_title: On Energy-Based Acoustic Source Localization for Sensor Networks

paper_content:

In this paper, energy-based localization methods for source localization in sensor networks are examined. The focus is on least-squares-based approaches due to a good tradeoff between performance and complexity. A suite of methods are developed and compared. First, two previously proposed methods (quadratic elimination and one step) are shown to yield the same location estimate for a source. Next, it is shown that, as the errors which perturb the least-squares equations are nonidentically distributed, it is more appropriate to consider weighted least-squares methods, which are observed to yield significant performance gains over the unweighted methods. Finally, a new weighted direct least-squares formulation is presented and shown to outperform the previous methods with much less computational complexity. Unlike the quadratic elimination method, the weighted direct least-squares method is amenable to a correction technique which incorporates the dependence of unknown parameters leading to further performance gains. For a sufficiently large number of samples, simulations show that the weighted direct solution with correction (WDC) can be more accurate with significantly less computational complexity than the maximum-likelihood estimator and approaches Cramer-Rao bound (CRB). Furthermore, it is shown that WDC attains CRB for the case of a white source.
---
paper_title: Robust Acoustic Positioning for Safety Applications in Underground Mining

paper_content:

The surroundings of underground mining machines still constitute an unsafe area for miners due to bad visibility conditions. In this paper, we present a novel acoustic position estimation system for safety applications in such hazardous environments. Our system is based on a pulse compression technique and utilizes linear (LFM) and hyperbolic (HFM) frequency-modulated signals in the frequency range of 5–20 kHz. As the miners are moving, we incorporated a means of Doppler-shift compensation. This system not only provides the positions of moving targets but also their velocity and direction. In stationary measurements, we evaluated LFM signals at noisy conditions both in an indoor laboratory environment and in the vicinity of a mining machine. The movement of a miner has been emulated in dynamic laboratory measurements at constant speeds up to 1 m/s using both LFM and HFM signals. Our results show that the acoustic signal can be evaluated down to a low signal-to-noise ratio of −30 dB. The results of the dynamic measurements clearly demonstrate the insensitivity of the HFM signals to Doppler-shifts both with regard to the estimated position and estimated velocity.
---
paper_title: Reliability criteria evaluation for TDOA estimates in a variety of real environments

paper_content:

Time delay estimates in microphone pairs are commonly used for acoustic sound source localization. In real environments, the reliability of time delay estimates quickly degrades for increasing noise or room reverberation levels. The paper presents two computationally non-demanding criteria to determine the reliability of time delay estimates. The criteria are evaluated for real data in a variety of acoustic environments with different reverberation and noise levels. The results show the generality of the proposed reliability indicators in delivering information on the credibility of the current time delay estimate for many typical room environments.
---
paper_title: Closed-form solutions for robust acoustic sensor localization

paper_content:

This paper deals with the localization of acoustic sensors based on signals emitted by loudspeakers at known positions. In particular, a model for distortions in time-of-flight (TOF) estimates applicable to the sensor localization problem is presented along with closed-form solutions with low computational cost. The proposed techniques are able to approximate the sensor position even when the TOFs are corrupted by an unknown delay, there is a sampling frequency mismatch between the A/D and D/A converters associated with sensor and loudspeakers, and the speed of sound is unknown. Simulations and an experiment on real data demonstrate that the proposed methods are able to estimate sensor positions with less than 2 cm of error in the evaluated scenarios.
---
paper_title: Exact and Approximate Solutions of Source Localization Problems

paper_content:

We consider least squares (LS) approaches for locating a radiating source from range measurements (which we call R-LS) or from range-difference measurements (RD-LS) collected using an array of passive sensors. We also consider LS approaches based on squared range observations (SR-LS) and based on squared range-difference measurements (SRD-LS). Despite the fact that the resulting optimization problems are nonconvex, we provide exact solution procedures for efficiently computing the SR-LS and SRD-LS estimates. Numerical simulations suggest that the exact SR-LS and SRD-LS estimates outperform existing approximations of the SR-LS and SRD-LS solutions as well as approximations of the R-LS and RD-LS solutions which are based on a semidefinite relaxation.
---
paper_title: Localizing multiple audio sources from DOA estimates in a wireless acoustic sensor network

paper_content:

In this work we propose a method to estimate the position of multiple sources in a wireless acoustic sensor network, where each sensor node only transmits direction-of-arrival (DOA) estimates each time interval, minimizing the transmissions to the processing node. Our method is based on the intersection of DOA estimates with outlier removal, and as such is very computationally efficient. We explore the performance of our method through extensive simulations and real measurements.
---
paper_title: Simultaneous Ranging and Self-Positioning in Unsynchronized Wireless Acoustic Sensor Networks

paper_content:

Automatic ranging and self-positioning is a very desirable property in wireless acoustic sensor networks, where nodes have at least one microphone and one loudspeaker. However, due to environmental noise, interference, and multipath effects, audio-based ranging is a challenging task. This paper presents a fast ranging and positioning strategy that makes use of the correlation properties of pseudonoise sequences for estimating simultaneously relative time-of-arrivals from multiple acoustic nodes. To this end, a proper test signal design adapted to the acoustic node transducers is proposed. In addition, a novel self-interference reduction method and a peak matching algorithm are introduced, allowing for increased accuracy in indoor environments. Synchronization issues are removed by following a BeepBeep strategy, providing range estimates that are converted to absolute node positions by means of multidimensional scaling. The proposed approach is evaluated both with simulated and real experiments under different acoustical conditions. The results using a real network of smartphones and laptops confirm the validity of the proposed approach, reaching an average ranging accuracy below 1 cm.
---
paper_title: Microphone array position calibration by basis-point classical multidimensional scaling

paper_content:

Classical multidimensional scaling (MDS) is a global, noniterative technique for finding coordinates of points given their interpoint distances. We describe the algorithm and show how it yields a simple, inexpensive method for calibrating an array of microphones with a tape measure (or similar measuring device). We present an extension to the basic algorithm, called basis-point classical MDS (BCMDS), which handles the case when many of the distances are unavailable, thus yielding a technique that is practical for microphone arrays with a large number of microphones. We also show that BCMDS, when combined with a calibration target consisting of four synchronized sound sources, can be used for automatic calibration via time-delay estimation. We evaluate the accuracy of both classical MDS and BCMDS, investigating the sensitivity of the algorithms to noise and to the design parameters to yield insight as to the choice of those parameters. Our results validate the practical applicability of the algorithms, showing that errors on the order of 10-20 mm can be achieved in real scenarios.
---
paper_title: BeepBeep: A high-accuracy acoustic-based system for ranging and localization using COTS devices

paper_content:

We present the design and implementation of BeepBeep, a high-accuracy acoustic-based system for ranging and localization. It is a pure software-based solution and uses the most basic set of commodity hardware -- a speaker, a microphone, and some form of interdevice communication. The ranging scheme works without any infrastructure and is applicable to sensor platforms and commercial-off-the-shelf mobile devices. It achieves high accuracy through three techniques: two-way sensing, self-recording, and sample counting. We further devise a scalable and fast localization scheme. Our experiments show that up to one-centimeter ranging accuracy and three-centimeter localization accuracy can be achieved.
---
paper_title: Multipath cancellation in broadband acoustic local positioning systems

paper_content:

This work proposes a novel method to estimate the Line-of-Sight Time-of-Flights (LOS-TOFs) in a broadband acoustic local positioning system (ALPS) with strong multipath interference. The proposed method is based on the Matching Pursuit channel estimation algorithm that provides a low complexity approximation to the Maximum Likelihood solution for sparse channels. A multichannel version of this algorithm has been implemented to estimate a minimum of three coefficients in the channel responses of a particular ALPS, composed of four beacons that perform the simultaneous emission of BPSK modulated 255-bit Kasami codes. A statistical analysis of performance has been carried out by using a set of test signals synthetically generated to simulate different positions and reflection coefficients of the environment. The results of this analysis show the enhanced capability of the proposed method to estimate the LOS-TOFs under strong multipath interference, with respect to that of a classical system based on correlation + thresholding.
---
paper_title: Robust Acoustic Positioning for Safety Applications in Underground Mining

paper_content:

The surroundings of underground mining machines still constitute an unsafe area for miners due to bad visibility conditions. In this paper, we present a novel acoustic position estimation system for safety applications in such hazardous environments. Our system is based on a pulse compression technique and utilizes linear (LFM) and hyperbolic (HFM) frequency-modulated signals in the frequency range of 5–20 kHz. As the miners are moving, we incorporated a means of Doppler-shift compensation. This system not only provides the positions of moving targets but also their velocity and direction. In stationary measurements, we evaluated LFM signals at noisy conditions both in an indoor laboratory environment and in the vicinity of a mining machine. The movement of a miner has been emulated in dynamic laboratory measurements at constant speeds up to 1 m/s using both LFM and HFM signals. Our results show that the acoustic signal can be evaluated down to a low signal-to-noise ratio of −30 dB. The results of the dynamic measurements clearly demonstrate the insensitivity of the HFM signals to Doppler-shifts both with regard to the estimated position and estimated velocity.
---
paper_title: BeepBeep: a high accuracy acoustic ranging system using COTS mobile devices

paper_content:

We present the design, implementation, and evaluation of BeepBeep, a high-accuracy acoustic-based ranging system. It operates in a spontaneous, ad-hoc, and device-to-device context without leveraging any pre-planned infrastructure. It is a pure software-based solution and uses only the most basic set of commodity hardware -- a speaker, a microphone, and some form of device-to-device communication -- so that it is readily applicable to many low-cost sensor platforms and to most commercial-off-the-shelf mobile devices like cell phones and PDAs. It achieves high accuracy through a combination of three techniques: two-way sensing, self-recording, and sample counting. The basic idea is the following. To estimate the range between two devices, each will emit a specially-designed sound signal ("Beep") and collect a simultaneous recording from its microphone. Each recording should contain two such beeps, one from its own speaker and the other from its peer. By counting the number of samples between these two beeps and exchanging the time duration information with its peer, each device can derive the two-way time of flight of the beeps at the granularity of sound sampling rate. This technique cleverly avoids many sources of inaccuracy found in other typical time-of-arrival schemes, such as clock synchronization, non-real-time handling, software delays, etc. Our experiments on two common cell phone models have shown that we can achieve around one or two centimeters accuracy within a range of more than ten meters, despite a series of technical challenges in implementing the idea.
---
paper_title: CDMA-based acoustic local positioning system for portable devices with multipath cancellation

paper_content:

Abstract This paper presents an acoustic local positioning system (ALPS) suitable for indoor positioning of portable devices such as smartphones or tablets, based on the transmission of high frequency CDMA-coded signals from a fixed network of beacons. The main novelty of the proposed ALPS is its capability to mitigate the effects of multipath propagation by performing an accurate estimation of the Line-of-Sight Time-of-Flights (LOS-TOF) through the Matching Pursuit algorithm. Signal detection, multipath cancellation and positioning estimation all take place within the portable device, which provides a graphical representation of the updated position in less than a second. The performance of the Matching Pursuit algorithm is analyzed in a real scenario and the results show that the proposed method is capable to retrieve the multipath-free System Availability under strong multipath conditions with SNR levels as low as 0 dB.
---
paper_title: Self-Localization of Ad-Hoc Arrays Using Time Difference of Arrivals

paper_content:

This work was supported by the U.K. Engineering and Physical Sciences Research Council (EPSRC) under Grant EP/K007491/1.
---
paper_title: TDOA-Based Speed of Sound Estimation for Air Temperature and Room Geometry Inference

paper_content:

Spatially distributed acoustic sensors find increasingly many new applications in speech-based human-machine interfaces. One well researched topic is the localization of sound sources from Time Differences Of Arrival (TDOAs) measurements. Typically, the propagation speed of sound is considered a known constant. However due to temperature variations its value is known only up to some uncertainty. This paper exploits TDOA-based localization techniques in order to estimate accurately the actual speed of sound. Experimental results using both simulated and real data demonstrate the feasibility of the proposed method. Furthermore, the practical validation of this work considers two distinct experiments that are aimed at inferring information about enclosed sound fields. The first experiment concerns the calculation of the air temperature from the estimated speed of sound. The second experiment highlights the effects of temperature variations on the inference of the physical location of reflective boundaries of the acoustic enclosure. In the latter case it is shown that the position estimates of the reflective surfaces in a room can be improved when the correct propagation speed is first estimated using this method.
---

Title: A Survey of Sound Source Localization Methods in Wireless Acoustic Sensor Networks
Section 1: General Considerations
Description 1: This section explains the notations and general aspects of Wireless Acoustic Sensor Networks (WASNs).

Section 2: Energy-Based Source Localization
Description 2: This section discusses methods of localizing sound sources based on energy readings.

Section 3: TOA-Based Localization
Description 3: This section presents approaches that use Time of Arrival (TOA) measurements for localization.

Section 4: TDOA-Based Localization
Description 4: This section describes techniques that rely on Time Difference of Arrival (TDOA) measurements for localizing sound sources.

Section 5: DOA-Based Localization
Description 5: This section discusses methods based on Direction of Arrival (DOA) measurements.

Section 6: SRP-Based Localization
Description 6: This section explains Steered Response Power (SRP) methods and their variations, focusing on improving localization accuracy.

Section 7: Self-Localization of Acoustic Sensor Nodes
Description 7: This section reviews methods for self-localizing the sensor nodes within the network.

Section 8: Challenges and Future Directions
Description 8: This section addresses various practical challenges and future directions in the field of sound source localization in WASNs.

Section 9: Conclusion
Description 9: This section summarizes the key points and findings from the survey.