Researchers from the University of Toronto, the Vector Institute, Ciena, and POSTECH have developed a LiDAR system capable of measuring location, speed, and material properties in a single measurement. The technology, described as Polarimetric Full-Wavefield Coherent LiDAR, was detailed in the journal Optica. This system aims to expand 3D sensing capabilities for applications such as autonomous driving and robotics.
Most commercial LiDAR systems currently used in autonomous vehicles primarily measure distance to build a three-dimensional understanding of surroundings. However, interpreting the nature of objects, such as distinguishing between a sign, pavement, or pedestrian, typically requires input from additional sensors like cameras, radar, and thermal imagers. The new coherent LiDAR system seeks to reduce this reliance by providing richer data directly from the sensor.
The system utilizes a coherent optical modem for both transmission and reception. This design allows for the detection of multiple light properties with high speed and precision. By analyzing frequency shifts, the platform calculates the exact speed of moving objects in real-time. The technology also measures how polarization properties of light change after interacting with a target surface, enabling the recovery of material properties alongside distance and velocity.
Coherent detection functions as an optical filter, largely ignoring ambient sunlight and noise that might overwhelm standard sensors. Mixing the return signal with a local oscillator amplifies weak return light, allowing the system to operate at lower laser powers while maintaining long-range detection. A Doppler velocity map generated by the system can identify moving vehicles and separate them from static backgrounds.
The primary advantage of LiDAR over radar lies in the short wavelength of light, which enables precise measurements. The new platform delivers four-dimensional data by instantly measuring both a target's distance and its velocity. This capability could lead to safer autonomous vehicles and sensing systems that perform better in poor visibility conditions.
