凝视成像激光雷达技术是空间非合作目标位姿测量重要手段。激光雷达指标选取极大影响航天器载荷, 优化选取激光雷达指标, 使之既能满足空间任务需求, 又能有效减少航天器载荷, 减少能源消耗, 意义重大。传统解决此问题的方法是通过经验选取, 激光雷达指标与目标属性相容性宏模型的提出, 可以为激光雷达激光输出功率、分辨率、视场角和测距精度四项指标选取提供理论依据。具体的, 利用目标尺度和雷达目标距离计算雷达分辨率和视场角初值, 对雷达最大可测距离进行迭代求解, 为优化激光雷达发射功率提供依据。充分利用深度共生矩阵二阶参数迭代优化, 确定雷达最优分辨率和视场角。最后, 通过点云配准算法迭代得出测量该目标的合适的测距精度。实验结果表明, 激光雷达宏模型优化选取的雷达指标满足雷达指标选择的需求。

The staring imaging lidar, whose indexes selection influences the load of spacecrafts seriously, is an important method for the pose measurement of non-cooperation target in space. Selecting the indexes of lidar reasonable is significant, opposite to the traditional method by experience, making it not only satisfy the demands of space mission, but also effectively reduce the load of spacecrafts and energy consumption. Macro model for compatibility between indexes of on-orbit lidar and attribute of target was proposed to provide a theoretical basis for indexes selection of lidar. Four indexes included lidar output power, lidar resolution, lidar field angle and lidar ranging precision. The processes were as follows. The initial values of the lidar resolution and field angle can be calculated by the scale of the target and distance between lidar and target. The transmitting power can be acquisited by iterating the maximum measurement distance. The reasonable resolution and field angle can be measured by iterating the second order parameters of the target surface depth co-occurrence matrix. The ranging precision of the lidar can be acquired by iterating the result of the point clouds registration algorithm. The experimental result of lidar indexes selection shows that proposed model can satisfy the requirement for the lidar parameters optimal selection.