MA Wen-gang, WANG Xiao-peng, ZHANG Yong-fang, CHENG Dong-liang
（School of Electronic and Information Engineering, Lanzhou Jiaotong University, Lanzhou 730070, China）
Abstract： 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.
Key words： aircraft attitude estimation; modified particle filter; MEMS sensor conjugate gradient method; weighted fusion
CLD number： TP212 Document code： A
Article ID： 1674-8042（2018）02-0180-08 doi： 10.3969/j.issn.1674-8042.2018.02.013
References
［1］Duan Z S, Han C Z, Tao T F. Multi-sensor parameter estimation data fusion based on least squares criterion. Computer Engineering and Applications, 2004, 40 (15): 1-3.
［2］Ye Z F, Feng E X. Study on stabilization of two-wheel vehicle based on quaternion and kalman filter. Journal of Sensors and Telecommunications, 2012, 25(4): 524-528.
［3］Guo X H, Yang Z, Chen Z, et al. Application of EFF and complementary filters in flight attitude determination. Sensors and Microsystems, 2011, 30(11): 149-152.
［4］Pan Y. Attitude estimation of miniature unmanned helicopter using unscented kalman filter. In: Proceedings of International Conference on Transportation, Mechanical and Electrical Engineering, 2011: 1548-1551.
［5］Wang F, Zhu S h, Lei H J. Design of digital strapdown attitude and attitude system algorithm based on kalman filter. Journal of Chinese Inertial Technology, 2008, 16(2): 208-211.
［6］Qiao X W, Zhou W D, Ji Y R. Study on aircraft attitude estimation algorithm based on quaternion particle filter. Journal of Ordnance, 2012, 33(9): 1070-1075.
［7］Zhang L, Qin H C, Wang W B, et al. Intelligent wheelchair location method based on ultrasonic and trajectory estimation. Journal of Electronics Measurement and Instrumentation, 2014, 28(2): 62-68.
［8］Feng Y B, Li X S, Zhang X J. An adaptive compensation method of electronic magnetic compass direction error error. Journal of Instrumentation, 2014, 35(11): 2607-2614.
［9］Hong D, Liu G B, Chen H M, et al. Application of EKF for missile attitude estimation based on SINS/CNS integrated guidance system. In: Proceedings of Systems and Control in Aeronautics and Astronautics, 2010: 1101-1104.
［10］Fernando H C T E, De Silva A T A, De Zoysa M D C, et al. Modelling, simulation and implementation of a quadrotor UAV. In: Proceedings of IEEE International Conference on Industrial and Information Systems, 2013: 207-212.
［11］Ruan X G, Song K K. An adaptive extended kalman filterfor attitude estimation of self-balancing two-wheeled robot. In: Proceedings of International Conference on Electric Information and Control Enginee, 2011: 4760-4763.
［12］Jung K L, Edward J P, Stephen N R. Estimation of attitude and external acceleration using inertial sensor measurement during various dynamic conditions. IEEE Transactions on Instrumentation and Measurement, 2012, 61(8): 2262-2273.
基于修正粒子滤波的MEMS传感器飞行器姿态解算
麻文刚， 王小鹏， 张永芳， 程东亮
（兰州交通大学 电子与信息工程学院, 甘肃 兰州 730070）
摘要: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。
关键词:飞行器姿态解算； 修正粒子滤波； MEMS传感器共轭梯度法； 加权融合
引用格式： MA Wen-gang, WANG Xiao-peng, ZHANG Yong-fang, et al. Aircraft attitude estimation of MEMS sensor based on modified particle filter. Journal of Measurement Science and Instrumentation, 2018, 9(2)： 180-187. ［doi： 10.3969／j.issn.1674-8042.2018.02.013］
[full text view]
