基于信息质量的脉冲星导航自适应滤波算法

Pulsar navigation adaptive filtering algorithm based on information quality

针对脉冲星导航过程中观测脉冲星的可见性问题,提出了一种基于信息质量的自适应滤波算法。通过分析观测脉冲星的数目及信息质量,确定观测矩阵维数,实时生成观测矩阵,设计了适应观测信息变化的改进型Kalman滤波器。对观测信息质量重新做了定义,并据此构造滤波方程提高了脉冲星导航的精度及适应性;运用四阶龙格库塔方法对带有J2摄动的二体动力学方程进行线性离散化,提高了滤波器状态方程的线性离散化精度。进行了仿真实验,对改进型Kalman滤波算法进行了验证。结果显示,对初始偏差校正后,在10 000s内观测一颗或两颗脉冲星,导航位置精度可达40m,速度精度可达0.019m/s。得到的结果验证了提出算法的有效性和可行性。

An adaptive filtering algorithm based on the quality of information was proposed aiming at the visibility of pulsars in pulsar navigation.According to the analysis of the number of pulsars observed and the quality of information received,the dimension of observation matrix was determined,and an improved Kalman filter was designed to be adaptable to the observation of the information changes.The observed information quality was defined,then filtering equation was constructed according to the definition of pulsar navigation to improve the accuracy and the adaptability of the pulsar.In order to improve the precision of linearization and discretization,Runge Kutta method was used to solve the two body dynamics equation with J2 perturbation.A simulation experiment was performed to verify the improved Kalman filtering algorithm.The experimental results show that after the initial error is corrected,the position precision is 40 mand the velocity precision is 0.019m/s when one or two pulsars are observed for navigation within 10 000 s.The simulation results show that this filtering algorithm is effective and feasible.