对激光雷达距离探测中的回波信号建模, 提出一种窗宽自适应形心修正算法, 根据窗宽与饱和度的关系建立窗宽自适应模型以获取形心, 并采用中位数修正, 实现高精度饱和波形时刻提取.利用Matlab进行仿真分析, 结果表明当信噪比为10 dB时, 窗宽自适应形心修正算法精度为0.3 ns, 相比于传统形心算法提高92%, 可有效解决形心漂移问题.利用板级系统实测波形验证算法, 并针对实测波形的微小畸变修正该算法, 结果表明在饱和波形下该算法时间精度可达0.5 ns, 可实现7.5 cm的测距精度, 有效增大测距动态范围, 降低系统复杂度.

An adaptive window width centroid correction algorithm is proposed based on echo signal modeling for lidar distance detection. An adaptive window width model is established to obtain centroids based on the relationship between window width and saturation. The algorithm is adjusted by the median, and achieves high-accuracy time extraction of saturated waveforms. The simulation is carried out through Matlab, and the results show that when the SNR reaches 10 dB, the accuracy of the adaptive window width centroid correction algorithm is 0.3 ns. Compared with traditional waveform centroid algorithms, the accuracy of the proposed algorithm is improved by 92% and the problem of centroid drift can be effectively solved. The algorithm is verified utilizing board-level measured waveforms and is corrected for distortion of the measured waveforms, the results show that the time accuracy of algorithm can reach 0.5 ns , and ranging accuracy can achieve 7.5 cm in case of saturated waveforms. The proposed algorithm can effectively increase the dynamic range of ranging and reduce system complexity.