摘要
针对地磁定轨系统受地磁偏差影响精度不高的问题,提出了一种基于新息趋势的自适应地磁定轨算法(AKF)。该算法将地磁偏差建模为随机游走模型,使之参与滤波。在滤波器运行过程中,依据新息的变化趋势,实时调整滤波器状态。以Swarm-A卫星的观测数据的实验表明,该算法和传统滤波器相比具有计算量低,收敛速度快,定位精度高等优点。通过改善地磁偏差的估计性能,该算法提升了系统的定位精度,其最大定位误差为6 km。
One of the disadvantages of geomagnetic orbit determination is the poor position accuracy introduced by magnetic bias.An adaptive Kalman filter(AKF)is proposed and the magnetic bias is regarded as a random walk model.The AKF is used to improve the covariance of the system based on the innovation.The filter is evaluated by using the real-flight data of the SWARM-A.The experiment results show that the position error of AKF is 6 km.
作者
陈贵芳
郁丰
王润
Chen Guifang;Yu Feng;Wang Run(Key Laboratory of Space Photoelectric Detection and Perception Nanjing University of Aeronautics and Astronautics,Ministry of Industry and Information Technology,Nanjing 210016 China;Nanjing University of Aeronautics and Astronautics,Nanjing 210016 China)
出处
《航天控制》
CSCD
北大核心
2021年第1期20-25,共6页
Aerospace Control
基金
国家自然科学基金(61673212)。
关键词
地磁场
国际地磁参考场
自适应滤波算法
地磁定轨
地磁偏差
Geomagnetic field
International geomagnetic reference field(IGRF)
Adaptive Kalman filter(AKF)
Geomagnetic orbit determination
Geomagnetic bias
