Distance–Intensity Image Strategy for Pulsed LiDAR Based on the Double-Scale Intensity-Weighted Centroid Algorithm

We report on a self-adaptive waveform centroid algorithm that combines the selection of double-scale data and intensity-weighted (DSIW) method for accurate LiDAR distance–intensity imaging. A time window is set to adaptively select effective data. At same time, can reduce influence sharp noise calculation. The horizontal vertical coordinates point obtained by proposed are utilized record distance echo intensity information, respectively. was experimentally tested, achieving an average ranging error less than 0.3 ns under various conditions in listed tests, thus exerting better precision compared digital constant fraction discriminator (DCFD) algorithm, peak (PK) Gauss fitting (GF) traditional (TC) algorithm. Furthermore, fairly robust, with remarkably successful rates above 97% all tests this paper. laser measured proved be robust work accordance transmission characteristics LiDAR. Finally, we provide cloud image calibrated our empirical findings study new understanding using draw multi-dimensional images.