摘要
针对基于微小卫星姿态确定系统精度低和噪声存在非高斯分布的情况,研究了适用于该定姿系统的Unscented粒子滤波(UPF,Unscented Particle Filter)算法.UPF方法结合了Unscented卡尔曼滤波(UKF,Unscented Kalman Filter)与粒子滤波(PF,Particle Filter)的特点,用UKF得到PF的重要采样函数,从而克服了PF没有考虑最新量测信息、扩展卡尔曼滤波(EKF,Extended Kalman Filter)和UKF只能应用到噪声为高斯分布的不足.以MEMS(Mi-cro Electronic Mechanical System)陀螺和CMOS APS(Complementary Metal Oxide Semiconductor Active Pixel Sensors)星敏感器为姿态敏感器件,将UPF与基于误差四元数的卫星姿态运动学方程结合,构建了UPF定姿滤波器,并用MEMS陀螺采集的随机噪声数据进行了半物理仿真,对其特性进行了分析与比较.仿真比较结果表明:在敏感器精度较差并且系统噪声非高斯分布的情况下,这种基于UPF的姿态估计方法在计算粒子数目相对于PF较少的情况下,可以取得比UKF更好的滤波精度,从而有效地提高了定姿性能.
To solve the problem of low precision characters and non-Gaussian distribution noise of the micro-satellite attitude determination system, UPF（Unscented particle filter） was proposed. Based on the different characters between the UKF（ Unscented Kalman filter） and PF（ particle filter） , UPF uses the UKF to generate sophisticated proposal distributions. UPF can not only avoid the limitation of the EKF（ extended Kalman filter） and the UKF which only apply to Gaussian distributions but also avoid the limitation of the standard PF which can not include the new measurements. The MEMS （micro electronic mechanical system） gyros and CMOS APS（complementary metal oxide semiconductor active pixel sensors） star sensor were applied as attitude sensors, the method of attitude determination used the error quaternion as the attitude parameter, presented a UPF attitude estimator. The attitude determination filter was constructed and the stochastic noise was adopted from the MEMS gyro. Then the UPF characters were analyzed. The simulation results showed that the suggested method can improve the system performance. The determination accuracy was higher than the UKF while the number of the particle was lesser than standard PF.
出处
《北京航空航天大学学报》
EI
CAS
CSCD
北大核心
2007年第5期552-556,共5页
Journal of Beijing University of Aeronautics and Astronautics
基金
新世纪优秀人才支持计划资助项目(NCET-04-0162)
国家863计划资助项目(2005AA738011)
