

The system, which is to be presented at the CLEO 2014 conference in San Jose next week, combines frequency-modulated continuous-wave Lidar with something called MEMS (micro-electrical-mechanical system) tunable VCSELs (vertical cavity surface-emitting lasers). That mouthful essentially means that it emits "frequency chirped" light (that is, laser light of increasing or decreasing frequency) from a low-power laser tuned to the natural resonance frequency of the MEMS mirror, which greatly amplifies the signal without increasing power drain. Measuring changes in the frequency of reflected light allows the system to gauge the distance an object from the sensor.

The technology is seen as a smaller, less power-hungry alternative to current high-resolution Lidar imaging systems, which require big, bulky boxes and typically have their operating range and accuracy severely affected by a phenomenon known as Brownian noise limitation – a kind of signal noise produced by Brownian motion, which is the term used to describe random movement of particles as they collide with atoms, molecules, and other particles in the air. Brownian motion in conventional Lidar systems causes excessive interference – more specifically, beat frequency, or variation in the frequency of returning light – for reliable readings over longer distances, but this effect is severely reduced by tuning the laser to its mechanical resonance frequency.

This new system will now be scaled down, and the researchers expect that it will fit on a microchip, thereby making it possible to integrate Kinect-like hand gestures that allow you to silence your ringtone from 30 ft away or to play virtual tennis in an area approaching the size of a real tennis court.

Lead researcher Behnam Behroozpour believes the system also has "a host of new applications that have not even been invented yet." But its utility seems most apparent in fields related to robotics, as a safety measure that enables self-driving cars to see hazards half a block away or to improve the depth sensing of drones and other autonomous or semi-autonomous robots.

Source: The Optical Society