AUTONEWS
New lidar system maps location, speed and material properties in a single measurement
Researchers have developed a new kind of lidar system that simultaneously measures the location, speed and material properties of objects in a scene. This type of information could be useful for applications such as robotics, autonomous driving and remote sensing.
Lidar uses laser pulses to measure distances and create highly detailed 3D maps of objects and terrain. However, most commercial lidar systems, such as the ones used in autonomous cars, primarily measure distance.
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.
“Although some emerging lidar technologies can also measure velocity, real-world perception often requires understanding an object's surface as well,” said Dongyu Du from the University of Toronto in Canada. “Our new system uses a single measurement at each scanned point to capture millimeter-accurate distance, velocity and surface material while using eye-safe laser power.”
In Optica, Optica Publishing Group’s journal for high-impact research, the researchers from the University of Toronto and network technology company Ciena Corporation describe their new lidar system, which combines new analysis methods with a standard telecommunications device that enables sensing of distance, velocity and surface material by capturing polarization information.
“Although this work is still at the research-prototype stage, it points toward future sensing systems that could help machines understand the physical world more reliably,”
said Du. “This could lead to safer autonomous vehicles, more capable robots, better industrial inspection and sensing systems that work in poor visibility caused by glare, fog, or heavy rain.”
Adapting telecom technology for lidar...The new work grew out of a collaboration between research groups at the University of Toronto and Ciena Corporation, which have been exploring how a device called a coherent optical modem could be adapted for lidar. These mass-produced modems can simultaneously measure many different properties of light, including its frequency, polarization, phase and amplitude.
“Coherent optical modems are used to send internet traffic through cities and even across continents by encoding information into light,” said Du. “As a result, they can control and measure light with very high speed and precision, come in compact form factors and naturally solve many of the same sensing challenges encountered with lidar.”
The researchers developed a lidar system that uses a coherent optical modem as the transmitter and receiver. This made it possible to send and detect multiple properties of light with extremely high speed and precision and, thus, extract far more information from each measurement than is possible with a conventional lidar system.
The system works by illuminating a target with a laser beam that is randomly modulated at extremely fast speeds — tens of billions of times per second — in two orthogonal polarization channels. While conventional lidar systems measure the time delay between when light is emitted and when it returns to calculate distance, the new system also measures how the polarization properties of light change after interacting with the target surface, making it possible to recover distance, velocity and material properties.
Extracting the lidar signal...The researchers also developed a new way to make sense of the measurements, which are difficult to recover and are degraded by noise and unavoidable distortions induced by the lidar system’s internal optics.
“Previous systems lacked the computational tools to separate out the signal of interest from the internal distortions,” said Du. “We developed a new polarization-aware model of how light propagates through our system and interacts with the scene, along with algorithms that can disentangle all of these effects to produce clean estimates of distance, velocity and material properties.”
To test the system, the researchers first compared its depth and velocity measurements to those obtained with other lidar processing methods using controlled scenes with static and moving objects. The new method outperformed existing techniques on both fronts, particularly in challenging low-signal regions where other approaches struggled with noise. They also showed that the system works reliably under strong ambient light, which can cause other polarimetric lidar systems to fail.
The researchers then showed that the lidar system could recover surface material properties of everyday materials, including metals, plastics and objects with varying surface roughness. They also measured polarization speckle — an interference pattern created by laser light — and demonstrated that these patterns carry information about surface roughness, thereby providing a means to characterize materials at fine scales.
Finally, the researchers demonstrated that the polarization information obtained with the system can be helpful for imaging through scattering media with optical thickness up to 4.76. This capability could be useful for imaging in conditions where visibility is limited by fog, rain or dust.
The researchers are now working to improve the system’s hardware readout bandwidth, streaming acquisition and data transfer to enable more direct and faster capture of continuously evolving dynamic scenes.
Source: optica.org
