基于视觉信息的航天器位姿估计迭代算法  

A Novel Binocular OI(Orthogonal Iteration) Fusion Algorithm Better for Estimation of Spacecraft Position and Attitude

作　　者：岳晓奎[1] 武媛媛[1] 吴侃之[1] 

机构地区：[1]西北工业大学航天学院,陕西西安710072

出　　处：《西北工业大学学报》2011年第4期559-563,共5页Journal of Northwestern Polytechnical University

基　　金：国家自然科学基金(10772145);高等学校博士点专项科研基金(20106102110003)资助

摘　　要：基于视觉信息的空间目标相对位姿估计问题是未来空间操作的关键所在,正交迭代算法是一种具有实时性好且全局收敛特点的单目位姿估计算法。为了有效利用多个摄像机获取的数据,进一步提高位姿估计算法的综合性能,提出了一种双目正交迭代融合算法,取两个摄像机获取的所有特征点的目标空间共线性误差平方和作为误差函数,推导得到使两个摄像机总的目标空间共线性误差最小的迭代求解过程,进而采用单位四元数法求解算法中的目标函数得到目标位姿的估计值,从根本上解决传统算法旋转矩阵计算误差大的问题。最后通过仿真算例验证了该算法在计算精度、抗噪性能以及稳定性等方面具有的优势。The introduction of the full paper reviews some papers in the open literature and then proposes a novel OI fusion algorithm, which we believe is better. Sections 1 and 2 explain our better algorithm. Section 1 briefs OI algorithm. The core of section 2 consists of： （ 1 ） we use as error function, which is given by eq. （ 10）, the quadratic sum of collinearity errors of all the feature points in target space obtained from two cameras; （2） we deduce the four-step iterative procedure to get the minimum target space collinearity error as indicated in eq. （12） ; （3） we estimate the target position and attitude through unit quaternion of the target, thus avoiding fundamentally the troublesome rotation matrix error in traditional algorithms. Simulation results, presented in Figs. 2 through 5 and Table 1, and their analysis demonstrate preliminarily that our novel OI fusion algorithm is significantly better in precision, anti-noise ability and stability performances.

关 键 词：视觉导航 位姿估计 正交迭代 单位四元数 

分 类 号：V412.4[航空宇航科学与技术—航空宇航推进理论与工程]