摘要
探讨了利用推广卡尔曼滤波估计非线性系统状态时存在的问题,从而介绍了目前广泛使用的分步逼近的卡尔曼滤波(UKF,Unscented Kalman Filter).为了提高导航的可靠性和准确性,在星敏感器导航系统中引入雷达高度计作为一个新的测量设备,提出了一种基于星上雷达测高仪及星敏感器联合进行卫星自主定轨的算法.建立了比较复杂的地球海平面模型,并考虑了其中风生重力波的影响.利用雷达测高仪的测量结果和地球形状模型,计算地心矢量在卫星本体中坐标系的方向.利用UKF滤波定轨算法,明显提高了自主定轨的精度.数值仿真结果表明,UKF定轨精度要远优于推广卡尔曼滤波.
The existing problem in using the extended Kalman filter（EKF） to estimate the state of one nonlinear system was discussed. And the unscented Kalman filter（UKF） was introduced, which is widely used today. The radar altimeter as a new measure instrument was introduced in the satellite orbit navigation based on star sensor. A algorithm was presented about the autonomous orbit determination with radar altimeter and star sensor. The complicated sea level model was established, and the influence of the gravity waves caused by wind was considered. Using the measure data recurring to radio altimeter and model of earth＇s shape, the direction of earth-satellite vector in satellite orbit frame was calculated. Based on UKF the precision of autonomous navigation was improved obviously. The simulations demonstrate that the precision of the UKF is much higher than the EKF.
出处
《北京航空航天大学学报》
EI
CAS
CSCD
北大核心
2006年第8期889-893,共5页
Journal of Beijing University of Aeronautics and Astronautics
关键词
卫星
导航
卡尔曼滤波
雷达高度计
satellite
navigation
Kalman filter
radio altimeter
