论文部分内容阅读
为了提高深空探测器的自主导航系统性能,文章提出一种基于改进动静态滤波的脉冲星/CNS组合导航方法。脉冲星观测数据和星光角距信息通过改进动静态滤波器进行信息融合。其中,动态滤波采用UKF处理采样速率快、测量方程非线性强的星光角距测量量,静态滤波采用EKF处理采样速率慢、测量方程线性特征明显的脉冲星测量量,其运行周期可以是动态滤波的若干倍。利用该改进动静态滤波进行组合导航,可避免联邦滤波器中由于各局部滤波器采用相同的状态方程而导致的融合滤波结果不具备最优性的问题。仿真分析表明,基于所提出的组合导航系统,深空探测器的导航精度可提高至10km以内。
In order to improve the autonomous navigation system performance of deep space probe, a pulsar / CNS integrated navigation method based on improved dynamic and static filtering is proposed. Pulsar observations and celestial horn information are fused through improved dynamic and static filters. Among them, dynamic filtering uses UKF to process star-angle measurement with fast sampling rate and nonlinear measurement equation. Static filter uses EKF to process pulsar with slow sampling rate and linear measurement of measurement equation. Its running period can be dynamic filtering Several times. By using the improved dynamic and static filtering for integrated navigation, the problem that the fusion filtering result does not have the optimality due to the same state equation of each local filter can be avoided in the federal filter. Simulation analysis shows that, based on the proposed integrated navigation system, navigation accuracy of deep space probes can be increased to within 10km.