Localization in Wireless Sensor Networks: A Survey
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paper_title: Research of TDOA Based Self-localization Approach in Wireless Sensor Network

paper_content:

Sensor Network, which has integrated wireless communication, date collection and information processing capacities, is a booming technique in information collecting. With the development of research on Wireless Sensor Networks (WSNs), localization in the WSNs has become a very important research point. At present, there are mainly two kinds of approaches, range-based approach and range-free approach. Localization precision of range-based approach is higher than the range-free approach. In the range-based approach, time difference of arrival (TDOA) method needs less requirements for time synchronization. This paper proposes a self-localization approach based on TDOA, which utilizes average value of time difference by rolling average to decrease the measurement error, and adopts unconstrained least squares (LS) estimator to achieve the accurate localization. Simulation results and error analysis prove its validity.
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paper_title: Path loss exponent estimation for wireless sensor network localization

paper_content:

The wireless received signal strength (RSS) based localization techniques have attracted significant research interest for their simplicity. The RSS based localization techniques can be divided into two categories: the distance estimation based and the RSS profiling based techniques. The path loss exponent (PLE) is a key parameter in the distance estimation based localization algorithms, where distance is estimated from the RSS. The PLE measures the rate at which the RSS decreases with distance, and its value depends on the specific propagation environment. Existing techniques on PLE estimation rely on both RSS measurements and distance measurements in the same environment to calibrate the PLE. However, distance measurements can be difficult and expensive to obtain in some environments. In this paper we propose several techniques for online calibration of the PLE in wireless sensor networks without relying on distance measurements. We demonstrate that it is possible to estimate the PLE using only power measurements and the geometric constraints associated with planarity in a wireless sensor network. This may have a significant impact on distance-based wireless sensor network localization.
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paper_title: A Self-Localization Method for Wireless Sensor Networks

paper_content:

We consider the problem of locating and orienting a network of unattended sensor nodes that have been deployed in a scene at unknown locations and orientation angles. This self-calibration problem is solved by placing a number of source signals, also with unknown locations, in the scene. Each source in turn emits a calibration signal, and a subset of sensor nodes in the network measures the time of arrival and direction of arrival (with respect to the sensor node's local orientation coordinates) of the signal emitted from that source. From these measurements we compute the sensor node locations and orientations, along with any unknown source locations and emission times. We develop necessary conditions for solving the self-calibration problem and provide a maximum likelihood solution and corresponding location error estimate. We also compute the Cramer-Rao bound of the sensor node location and orientation estimates, which provides a lower bound on calibration accuracy. Results using both synthetic data and field measurements are presented.
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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.
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paper_title: Probability grid: a location estimation scheme for wireless sensor networks

paper_content:

Location information is of paramount importance for wireless sensor networks (WSN). The accuracy of the collected data can significantly be affected by an imprecise positioning of the event of interest. Despite the importance of location information, real system implementations that do not use specialized hardware for localization purposes have not been successful. In this paper, we propose a location estimation scheme that uses a probabilistic approach for estimating the location of a node in a sensor network. Our localization scheme makes use of additional knowledge of topology deployment. We assume a sensor network is deployed in a controlled manner, where the goal of the deployment is to form a grid topology. We evaluate our localization scheme through simulations, showing localization errors as low as 3% of radio range. We outperform similar localization schemes by obtaining 50% less error in localization. We also evaluate our localization solution and the DV-hop scheme in a real implementation, obtaining an average error in location of 79% of radio range, outperforming DV-hop by approximately 40%. We analyze the significant differences in performance between simulations and a real implementation and stress the importance of further evaluations of real implementations. The result is an effective and realistic protocol that works in an actual implementation, under certain assumptions, because it exploits deployment information.
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paper_title: Emitter Location Accuracy Using TDOA and Differential Doppler

paper_content:

Two methods for locating a radio or sonar transmitter are briefly described: time difference of arrival (TDOA). d differential Doppler. Two formulas are derived which relate the accuracy of the time and frequency measurements the ?one-sigma widths? of the lines of constant TDOA onstant differential Doppler on the surface of the FDOA.
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paper_title: Probability grid: a location estimation scheme for wireless sensor networks

paper_content:

Location information is of paramount importance for wireless sensor networks (WSN). The accuracy of the collected data can significantly be affected by an imprecise positioning of the event of interest. Despite the importance of location information, real system implementations that do not use specialized hardware for localization purposes have not been successful. In this paper, we propose a location estimation scheme that uses a probabilistic approach for estimating the location of a node in a sensor network. Our localization scheme makes use of additional knowledge of topology deployment. We assume a sensor network is deployed in a controlled manner, where the goal of the deployment is to form a grid topology. We evaluate our localization scheme through simulations, showing localization errors as low as 3% of radio range. We outperform similar localization schemes by obtaining 50% less error in localization. We also evaluate our localization solution and the DV-hop scheme in a real implementation, obtaining an average error in location of 79% of radio range, outperforming DV-hop by approximately 40%. We analyze the significant differences in performance between simulations and a real implementation and stress the importance of further evaluations of real implementations. The result is an effective and realistic protocol that works in an actual implementation, under certain assumptions, because it exploits deployment information.
---
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.
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paper_title: Convex position estimation in wireless sensor networks

paper_content:

A method for estimating unknown node positions in a sensor network based exclusively on connectivity-induced constraints is described. Known peer-to-peer communication in the network is modeled as a set of geometric constraints on the node positions. The global solution of a feasibility problem for these constraints yields estimates for the unknown positions of the nodes in the network. Providing that the constraints are tight enough, simulation illustrates that this estimate becomes close to the actual node positions. Additionally, a method for placing rectangular bounds around the possible positions for all unknown nodes in the network is given. The area of the bounding rectangles decreases as additional or tighter constraints are included in the problem. Specific models are suggested and simulated for isotropic and directional communication, representative of broadcast-based and optical transmission respectively, though the methods presented are not limited to these simple cases.
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Title: Localization in Wireless Sensor Networks: A Survey

Section 1: INTRODUCTION
Description 1: This section provides an overview of wireless sensor networks, their applications, and the importance of localization in these networks.

Section 2: CONCEPTS AND PROPERTIES OF LOCALIZATION
Description 2: This section discusses the fundamental concepts and properties of localization in wireless sensor networks, including the different types and methods used.

Section 3: Known location based localization
Description 3: This subsection explains how sensor nodes can use known location references provided manually or by GPS devices for localization.

Section 4: Proximity based localization
Description 4: This subsection describes the technique where sensor nodes localize themselves based on their proximity to cluster heads or known nodes using Infrared, Bluetooth, etc.

Section 5: Range based localization
Description 5: This subsection covers localization techniques that estimate the range using methods like RSSI, ToA, and TDoA.

Section 6: Distance based localization
Description 6: This subsection explains how sensor nodes use hop distances and propagation methods like DV-hop for localization.

Section 7: LOCALIZATION TECHNIQUES
Description 7: This section categorizes the various localization techniques into range-based and range-free approaches, and describes each in detail.

Section 8: Range based approach
Description 8: This subsection delves into range-based localization approaches, further detailing techniques that use anchor nodes and those that do not.

Section 9: Using anchor nodes
Description 9: This part of the range-based approach describes how some nodes use pre-determined location references or GPS to aid other nodes in localization.

Section 10: Without using anchor nodes
Description 10: This part of the range-based approach explains localization techniques that utilize GPS attached devices without relying on anchor nodes.

Section 11: Range free approach
Description 11: This subsection describes range-free localization techniques that do not require special hardware, using methods such as DV hop or DV distance.

Section 12: Performance of Localization Techniques
Description 12: This section compares the performance of different localization schemes, discussing trade-offs, advantages, and issues like scalability, error rates, and deployment costs.