脉冲星非实时平差的火星探测自主导航模型

针对基于X射线脉冲星观测的火星探测器自主导航,研究了几种不同的实时自适应方法,包括:扩展卡尔曼滤波(EKF),自适应扩展卡尔曼滤波(AEKF)和鲁棒自适应扩展滤波(RAEKF)。首先根据脉冲星导航原理,模拟了观测值:脉冲到达时刻;接着,分别利用扩展卡尔曼滤波,自适应扩展卡尔曼滤波和鲁棒自适应扩展滤波方法估算出探测器的位置和速度;最后,上述几种滤波轨道与STK模拟的标称轨道较差,然后比较它们的滤波精度发现:AEKF和RAEKF的精度相对较高,AEKF的三个轴向滤波位置精度达到:X轴优于100m、Y和Z轴优于30m,优于VLBI技术的km量级,和Doppler技术的精度相当。

Modeling on Autonomous Navigation of Mars Probe with Pulsars and Nonreal-Time Adjustment Methods

To investigate the autonomous navigation of probe orbiting the Mars orbit X-ray pulsars, different real-time adjustment methods are applied in this paper, including the extended Kalman filter (EKF), adaptive extended Kalman filter (AEKF) and robust adaptive extended Kalman filter (RAEKF). Firstly, the observation data, i.e., time of arrival, is simulated according to the principles of pulsars navigation. Secondly, extended Kalman filter (EKF), adaptive extended Kalman filter (AEKF) and robust adaptive extended Kalman filter (RAEKF) are used to get the position and velocity of the probe. Thirdly, the adjustment results are compared with the orbit generated by STK, the results show AEKF and RAEKF performs better than EKF, the result of AEKF is better than the km level of VLBI and can reach the precision level of triple pass Doppler, leveling at 94.1 m in X-axis, 19.5 m in Y-axis and 22.3 m in Z-axis.