基于修正粒子滤波的MEMS传感器飞行器姿态解算

针对单一采用 MEMS传感器解算飞行器姿态无法克服系统非线性噪声干扰的问题,提出了一种基于修正粒子滤波的 MEMS传感器飞行器姿态解算方法.首先,利用共轭梯度法减小陀螺仪漂移误差,然后,利用加权粒子构造概率密度函数以更新粒子权值,得到优化状态估计值;再将共轭梯度法与修正粒子滤波进行融合,确定加权因子,同时以 STM32与 MEMS传感器为核心设计姿态解算系统.实验结果表明,该方法优化了飞行器静态与动态性能,姿态解算性能良好,系统过渡时间短,跟踪特性较好,且增强了系统的鲁棒性与稳定性.

Aircraft attitude estimation of MEMS sensor based on modified particle filter

The non-linearity problem of aircraft system could not be overcome by using the MEMS sensor only.In order to improve the accuracy of aerial vehicle attitude,an aircraft attitude estimation of the MEMS sensor based on modified particle filter is proposed.The aircraft attitude is optimized by the conjugate gradient method,and the drift error of gyroscope is reduced.Moreover,the particle weight is updated by the observed value to obtain an optimized state estimate.Finally,the conjugate gradient method and the modified particle filter are weightily combined to determine the optimal weighting factor. The attitude estimation is carried out with STM32 and MEMS sensor as the core to design system.The experimental results show that the static and dynamic attitude estimation performances of the aircraft are improved.The performances are well,the attitude data is relatively stable,and the tracking characteristics are better.Moreover,it has better robustness and stability.