三维(3D)非扫描激光雷达具有多表面目标距离分辨能力,可以用于对隐藏和伪装目标的识别。为了快速、准确地估计3D非扫描激光雷达多表面目标距离信息,提出了基于期望值最大化(EM)的单像素多表面目标的距离估计算法,通过对系统点扩展函数的参数化,该算法可以同时估计出成像系统点扩展函数和目标的距离信息。仿真实验结果表明,相比于传统的混合高斯匹配算法和维纳空间滤波算法,该算法在系统点扩展函数未知的条件下,可以将目标的距离估计精度分别提升大约70%和40%。 Three-dimensional (3D) non-scanning lidar with multi-surface target distance resolution, can be used for identification of hidden and camouflaged targets. In order to quickly and accurately estimate the multi-target distance information of 3D non-scanning lidar, a single pixel multi-surface target distance estimation algorithm based on expectation maximization (EM) is proposed. By parameterizing the system point spread function, At the same time, the distance information between the point spread function of the imaging system and the target is estimated. Simulation results show that compared with the traditional hybrid Gaussian matching algorithm and Wiener spatial filtering algorithm, the proposed algorithm can improve the target’s estimation accuracy by about 70% and 40% respectively under the condition that the system point spread function is unknown.