Briefly describe the detection technology of LiDAR
Lidar (Light Detection and Ranging) uses the distance values of target point clouds/pixels to estimate the three-dimensional (3D) shape of targets, and has rapidly developed in non structured environment perception such as autonomous driving, robot navigation, terrain mapping, and remote sensing.
Unlike passive 3D imaging technology that can only restore 3D information of ambient lighting scenes, LiDAR can actively obtain 3D information of the surrounding environment and combine algorithms such as point cloud generation, noise filtering, coordinate registration, and feature description to achieve scene understanding. Based on different light detection methods, existing LiDAR can usually be divided into direct detection and coherent detection.
Directly detecting using pulsed light and detecting the echo intensity of the target through a photodetector. A typical incoherent LiDAR is a time-of-flight (TOF) ranging technology that dominates many applications due to its mature hardware configuration and signal processing methods. However, the detection range and resolution of TOF LiDAR are limited by the performance of the photodetector and the peak power of the pulsed laser, and its echo signal may also be affected by sunlight or other radar system laser beams.
In contrast, coherent detection using optical mixing technology between the echo beam and the local oscillator beam can effectively resist environmental light interference and improve the system signal-to-noise ratio. Traditional LiDAR mainly relies on intensity, 3D coordinates, or velocity for imaging, and the insufficient information dimension results in limited recognition and classification capabilities of these LiDAR. Especially for targets with diverse structures, there is ambiguity in determining the point cloud on the target, resulting in uncertainty in the recognition of the 3D shape of the target.
One feasible method is to use the polarization component of light, which can effectively improve the certainty of target point clouds/pixels. By analyzing the interaction between polarized light and materials, the structure and composition information of the target can be inferred. Polarization coherent LiDAR integrates cutting-edge directions from multiple disciplines such as optics, mechanics, control, and electronic information, covering core theories such as information detection, beam scanning, and polarization imaging.
Post time: Jul-02-2026