Study on Mars Autonomous Navigation System Design and the Parameter Optimization
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摘要:
当前火星探测器环绕段的导航信息主要依赖地面深空探测网提供，基于光学成像的导航方式尚不能提供较高的导航精度。因此提出一种应用相对测量的探测器实现火星环绕段的自主导航。两颗编队飞行的探测器进行相对测量，观测信息为探测器之间的相对视线矢量（LOS）。同时利用主星的星敏感器确定星体在惯性空间的姿态，将观测信息转换至惯性系下获得简化的观测方程，使用扩展卡尔曼滤波器（EKF）对卫星的轨道进行确定。介绍了具体导航方案的实现方法和技术细节，使用粒子群优化方法（PSO）对模型设计的相关参数进行优化，导航精度得到明显提高。实现位置确定精度10 m，速度确定精度0.01 m/s。为设计最优的编队导航系统参数提供了有效思路。
Abstract:The navigation on Mars mainly depends on the assistance of the earth-based deep space exploration network,and the accuracy of optical imaging autonomous navigation technology is unsatisfactory. One method based on formation flying satellites(FFS)to autonomously determine the position and velocity is proposed in this paper. The measurement information includes the inter-satellite position and the absolute attitude. As the measurements are combined with the dynamics of formation satellites,the Extended Kalman filter(EKF)is used to optimally estimate the states. Relevant system parameters are optimized with intelligent optimization methods. The results show that the position accuracy can reach 10 m and the velocity accuracy can reach 0.01 m/s.
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