基于最小偏度采样的卫星自主导航SRUKF算法  

Square Root Unscented Kalman Filter for Satellite Autonomous Navigation System Based on Minimal Skew Simplex Transformation

作　　者：李丹[1] 刘建业[1] 熊智[1] 熊剑[1] 

机构地区：[1]南京航空航天大学自动化学院,南京210016

出　　处：《南京航空航天大学学报》2009年第1期54-58,共5页Journal of Nanjing University of Aeronautics & Astronautics

基　　金：国家高技术研究发展计划"863计划"(2006AA704312)资助项目

摘　　要：针对航天器自主导航系统对可靠性、精确性和实时性的要求,将最小偏度采样策略和平方根Unscented卡尔曼滤波(SRUKF)算法相结合,提出了一种改进型SRUKF算法,该算法在保证滤波精度和标准Unscented卡尔曼滤波(UKF)算法相当的条件下,通过引入最小偏度采样减少了采样点数,提高了计算速度,以协方差阵的平方根代替协方差阵参加递推运算,减少了计算机舍入误差。将该算法应用于磁强计/雷达高度计组合导航系统中,仿真结果表明:该算法保证了估计精度,较大地减轻了计算负担,具有算法简单、计算效率较高的特点,能够满足卫星自主导航系统的要求。A modified square root Unscented Kalman filter （SRUKF） is presented for the satellite autonomous navigation system to satisfy the reliability, accuracy and real time requirements of the system. The filter uses the minimal skew simplex transformation to reduce the number of the sigma points, so it can improve the calculating speed. The covariance matrix is replaced by its root form to decrease the rounding off error. The algorithm is used in the integrated navigation system composed of magnetometers and radar altimeter. Simulation results verifiy that the algorithm is simple, the accuracy is ensured and the computational efficiency is improved. It can meet the requirments of the satellite autonomous navigation systems.

关 键 词：自主导航 轨道确定 非线性滤波 平方根UKF 

分 类 号：V448.22[航空宇航科学与技术—飞行器设计]