Researchers from the University of Toronto and telecommunications firm Ciena Corporation have developed a prototype lidar system capable of simultaneously measuring distance, velocity, and surface material properties within a single scan. Published in Optica, the technology addresses a critical limitation in conventional lidar, which typically captures only spatial coordinates and, in some cases, speed. By integrating a commercially available coherent optical modem as both transmitter and receiver, the system leverages the frequency, phase, amplitude, and polarization states of 1,550-nanometer laser pulses to extract multidimensional data. Unlike traditional time-of-flight lidar, this new architecture analyzes how light polarization shifts upon reflecting off targets. This approach enables millimeter-accurate ranging, Doppler velocimetry, and polarimetric material characterization without requiring multiple scanning passes. The team developed specialized computational models and algorithms to disentangle internal optical distortions and environmental noise, allowing the system to maintain performance in challenging conditions such as high ambient light, fog, rain, or dust. Experimental demonstrations successfully distinguished between static and dynamic objects, resolved surface textures through polarization speckle patterns, and identified material differences between artificial and real vegetation. Dongyu Du, lead researcher at the University of Toronto, noted that while the prototype currently operates in controlled settings, the underlying methodology significantly advances machine perception. The system operates at eye-safe power levels and recovers detailed physical characteristics from scattered light, making it particularly valuable for autonomous vehicles, industrial inspection, and robotics operating in degraded visibility. The research team is now focused on upgrading hardware readout bandwidth, streamlining data acquisition, and optimizing transfer speeds to support real-time tracking of continuously moving scenes. This innovation marks a pivotal step toward deploying robust, multi-parameter sensing platforms capable of navigating complex, dynamic environments with greater reliability and safety.