基于特征值分解的小天体着陆自主导航系统可观度分析

Observability Analysis of Small Celestial Autonomous Landing Navigation System Based on Eigenvalue Decomposition

针对非线性导航系统中状态估计可观性与导航精度之间的关系,采用基于误差方差阵特征值分解的可观度分析方法,结合扩展卡尔曼滤波(EKF)算法对非线性预测滤波(NPF)算法进行改进,推导改进预测滤波的误差协方差矩阵,并对其进行特征值分解.分析特征值和特征向量与导航精度的关系,以小天体探测器着陆自主导航系统为例进行仿真验证,与EKF导航精度比较的基础上验证改进的NPF算法的有效性和精确性,并分析不同误差因素(模型误差,陀螺噪声,陆标误差)对可观度的影响,为航天器实际过程中自主导航系统的滤波器设计提供参考.

In order to solve the problem of the relationship between navigationobservability and accuracy in nonlinear navigation system, the observability analysis method based on the error covariance matrix is adopted. The nonlinear predictive filter( NPF) is improved combined with extended Kalman filter( EKF),and the error covariance of improved predictive filter is deduced. Then the eigenvalue decomposition is carried out to analyze the relationship between the eigenvalue and navigation accuracy. Taking the autonomous navigation system of the small celestial probe landing as an example, the simulation validation is carried out and the validity and accuracy of the improved NPF algorithm are verified comparin with the EKF. The influence of different error factors on observability is analyzed, which provide a reference for the filter design of autonomous navigation system in the actual spacecraft process.