Achieve accurate recognition of 3D point cloud images by studying the scattering characteristics of typical targets

• Theoretical modeling of the scattering characteristics of some typical lidar targets is carried out. • We propose a double-scale intensity-weighted centroid algorithm to extract the intensity and distance information. • The lidar system performed scanning experiments on complex scenes. Three-dimensional imaging lidar has been widely used in various fields due to its high measurement accuracy, strong directionality, and three-dimensional visualization. At present, the three-dimensional point cloud imaging method of lidar mainly depends on the distance information of the target, but the intensity information of the target can play an auxiliary role in the recognition of the target, and it has also received extensive attention. The combination of intensity information and distance information enables the system to make more accurate decisions and improve the redundancy of the system. When scanning non-cooperative targets, if there is only distance information, the target will not be accurately identified, which may cause errors in decision-making. This paper studies and analyzes the scattering characteristics of typical lidar targets. The intensity of the scattered echo signal of the target is related to the target material, target distance, gray value and detection angle, so the detector's receiving scattering rate is different. For the extraction of the intensity and the distance signal, we propose a double-scale intensity-weighted centroid algorithm to achieve it, which ensures the accuracy of the signal. To this end, we build a database of the scattering characteristics of related targets, combined with the original distance information to realize the accurate recognition of the target in the lidar 3D point cloud image.