采用基于单步预测的卡尔曼滤波器，利用含噪声图像的自身特性估计噪声参数，研究了一种对多帧静止相干激光雷达距离像进行复原的方法。通过对仿真图像进行复原，研究了在可利用图像帧数较少时的滤波性能和帧数足够多时滤波性能的极限值，并与在相同帧数下的图像平均法进行比较。结果表明，该算法收敛速度快、具有更高的图像改善信噪比和极限值。

A restoration method for multi-frame stillness coherent lidar images is studied based on one-step predictive Kalman filter. Parameters of noise are estimated from the characteristic of the degradation images. In the image restoration progress of simulation, performance of the filter is studied under the condition of using less available images, as well as the limit value of the performance under the condition of using enough available images. The data are compared with those of an image averaging method. The results show that the method has a fast convergence speed, a higher improvement-in-signal-to-noise-ratio and a higher limit value.