单光子激光雷达的时间相关多深度估计  

Time-correlated multi-depth estimation of Single-photon lidar

作　　者：邬淼 陆俣 冒添逸 何伟基[1] 陈钱[1] Wu Miao;Lu Yu;Mao Tianyi;He Weiji;Chen Qian(School of Electronic and Optical Engineering,Nanjing University of Science and Technology,Nanjing 210094,China)

机构地区：[1]南京理工大学电子工程与光电技术学院,江苏南京210094

出　　处：《红外与激光工程》2022年第2期32-40,共9页Infrared and Laser Engineering

基　　金：国家自然科学基金(61875088,62005128)。

摘　　要：单光子激光雷达广泛应用于获得三维场景的深度和强度信息。对于多表面目标,如激光经过半透明表面上时,一个像素上探测到的回波信号可能包含多个峰。传统方法在低光子或相对较高的背景噪声水平下无法准确估计多深度图像。因此,提出了一种单光子激光雷达时间相关多深度估计方法。该方法利用信号响应的时间相关性,对点云数据进行多深度快速去噪,能够从背景噪声中识别每个像素上来自多个表面的信号响应。并基于该信号响应集合的泊松分布模型,通过全变分正则化引入像素之间的空间相关性,建立多深度估计成本函数。使用快速收敛的交替方向乘子算法从成本函数中估计深度图像。实验结果表明,所提方法在距离约为1 km处的多深度目标上,相较于常规方法估计深度图像的均方根误差减少了至少27.05%,信号重建误差比提高了至少18.39%,同时数据量减少至原来的4%。证明该方法能够以更小的内存需求和计算复杂度提高单光子激光雷达的多深度图像估计性能。Single-photon lidar has been widely used to obtain depth and intensity information of a threedimensional scene.For multi-surface targets,such as when the laser transmit through a translucent surface,the echo signal detected on one pixel may contain multiple peaks.Traditional methods cannot accurately estimate multi-depth images under low photon or relatively high background noise levels.Therefore,a time-correlated multi-depth estimation method was introduced.Based on the time correlation of the signal responses,a multidepth fast denoising method was adopted to point cloud data,and could identify the signal responses of multiple surfaces from background noise on each pixel.Considering the Poisson distribution model of the signal response set,the spatial correlation between pixels was introduced through total variation(TV)regularization to establish a multi-depth estimation cost function.The fast-converging alternating direction method of multipliers(ADMM)was used to estimate the depth image from the cost function.Experimental results on a multi-depth target at a distance of about 1 km show that the root mean square error(RMSE)and signal to reconstruction-error ratio(SRE)of the depth image estimated by the proposed method can be at least 27.05%and 18.39%better than that of other state-of-the-art methods.In addition,the data volume of this method is reduced to 4%of the original.It is proved that this method can effectively improve the multi-depth image estimation of single-photon lidar with smaller memory requirements and computational complexity.

关 键 词：单光子激光雷达 多深度图像估计 时间相关性 交替方向乘子算法 

分 类 号：TN958[电子电信—信号与信息处理]