项目名称: 运动模型/立体视觉深组合的非合作航天器超近距相对导航
项目编号: No.61203197
项目类型: 青年科学基金项目
立项/批准年度: 2013
项目学科: 自动化学科
项目作者: 郁丰
作者单位: 南京航空航天大学
项目金额: 24万元
中文摘要: 在0-10m的距离上,主动航天器实时可靠精确地测量其与非合作航天器之间,或者两者局部区域之间的相对位置姿态及其变化率,是实现航天器无人在轨服务的关键支撑之一,具有重要的理论意义和应用价值。目前已有的相对位姿测量算法尚不能完全满足这类特殊导航的实际需求,本项目提出了一种基于相对运动模型与立体视觉信息深组合导航新方法。根据在轨辨识或上时刻立体成像得到的非合作航天器的初步知识,结合运动模型预报下时刻图像知识以辅助立体视觉快速可靠的图像处理与位姿测量;基于在轨辨识得到的目标粗略运动模型,根据超近距离上的立体视觉信息,拟研究辨识模型误差的非线性批处理算法,逐步提高相对导航精度;基于比例控制的负反馈信息融合结构,研究一种新的具有自适应调节功能的信息融合算法与设计方法,提高信息融合速度与精度;拟设计高低两个速度的计算回路协同工作,以兼顾实时性与精度,并通过仿真和试验等手段验证与评价算法。
中文关键词: 故障航天器;相对导航;信息融合;立体视觉;深组合
英文摘要: Estimating the relative states including position, attitude, and rotational and translational velocities in the range of 10 meters between chaser and non-cooperative target, or the portions of the two spacecrafts is one of the keys of unmanned on orbit service, and the process must be real-time, reliable and precise. So the technologies are valuable whatever in theories and applications. The actual demands of the kind of navigation are not satisfied by the existing relative pose estimation algorithms, this research project suggests a new method based on ultra tight coupling relative motion model and stereo vision system. The next image knowledge forecasted by the relative motion model and the tentative knowledge of non-cooperative spacecraft which is available by on-orbit recognition or last images of stereo vision is adopted to assist the image process and pose measurement to enhance efficiency and reliability. A nonlinear batch estimation algorithm is to be researched to recognize model error based on target tentative motion model attained by on-orbit recognition and stereo vision information on ultra close distance, so the navigation precision enhancement is achieved step by step. A new adaptive information fusion algorithm and design method found on the negative feedback portion control information fusion ar
英文关键词: malfunctioned spacecraft;relative navigation;information fusion;stereo vision;ultra tight coupling