摘要
星敏感器/陀螺组合定姿系统利用扩展卡尔曼滤波进行数据融合,但在轨运行时星敏感器的量测噪声模型不断变化,由于扩展卡尔曼滤波不能自适应调整,导致滤波器无法正常工作;基于模糊逻辑提出了一种指数加权卡尔曼滤波算法,实时监测系统滤波残差,利用模糊逻辑计算指数因子,自适应更新滤波器的量测噪声模型,从而有效地抑制了滤波器发散,提高了滤波精度;通过以TMS320C6713为处理器的DSP系统进行的半物理仿真实验,验证了指数加权卡尔曼滤波算法的有效性。
Integrated attitude determination system of star sensor/gyroscope completes data fusion with Extended Kalman filter. Measurement noise model on--orbit of star sensor is variable. Extended Kalman filter is unadaptable so that the filter is out of order. This paper presents Kalman filter with weighted index based on fuzzy logic. The algorithm monitors residuals real time, exports index factor by fuzzy logic and then adjusts measurement noise model in order to restrain diffusion and improve precision. The semi--physical simulation results based on DSP system with TMS320C6713 processor validate availability of the algorithm.
出处
《计算机测量与控制》
2016年第4期133-136,共4页
Computer Measurement &Control
关键词
卡尔曼滤波
指数加权
模糊逻辑
量测噪声
半物理仿真
Kalman filter
weighted index
fuzzy logic
measurement noise
semi--physical simulation
