二维三维信息融合的空间非合作

为实现位置和姿态的测量，常用敏感器包括激光类敏感器和双目立体视觉类敏感器.激光类敏感器的测量结果受目标反射特性的影响较大，而双目立体视觉敏感器的测量精度又受杂光和自身基线长度的限制.针对这两类敏感器在各自应用中存在的问题，提出一种融合二维三维信息进行位置和姿态求解的方法，综合利用二维和三维测量敏感器各自的优势来获取目标信息和进行相对位置姿态测量.通过算法仿真和试验验证了方法的可行性.

An Attitude Computing of Non Cooperative Targets by Fusing 2D Image and 3D Point Clouds Information Fusion

The measurement of the pose of non cooperative targets is one of the very popular research directions in the field of space technology. The sensors include laser sensors and binocular measurement sensors. The precision of three dimension sensors such as lidar is sensitive to the reflectivity of the target surface. The precision of the binocular measurement sensors is limited by stray light and the length of base line. According to the shortage of lidar and the binocular measurement sensors, a computing method of the pose of non cooperative targets by fusing the 2D image and 3D point cloud is presented, in which the advantage of lidar and the binocular measurement sensors are utilized. The feasibility of the method is validated by simulating and experimentation.