GFMIMU/GPS组合导航系统信息融合技术研究

GFMIMU/GPS(Gyroscope Free Micro Inertial Measurement Unit/Global Positioning System)组合导航系统具有抗高g值冲击、低成本、长寿命、较高精度等优点,在低成本精确制导武器和微小型无人机具有广阔的应用前景。针对工程应用中信息融合的精度和实时性两方面的要求,运用基于模型误差预测的扩展卡尔曼滤波MEP-EKF(Extended Kalman Filter base on Model Error Predictive)方法,将MEMS(Micro Electromechanical Systems)加速度计的误差作为模型误差来考虑,对GFMIMU/GPS组合导航系统进行建模仿真,将其与EKF和UKF(Unscented Kalman Filter)方法进行了仿真比较,在方位误差角的估计上取得了比他们精度高的仿真结果,而且MEP-EKF所需时间是UKF的10%.

GFMIMU/GPS Integrated Navigation System Data Fusion

The gyroscope free micro inertial measurement unit/global positioning system(GFMIMU/GPS)Integrated navigation system has many advantages compared with the traditional MIMU/GPS Integrated navigation system,such as high dynamic rang,light weight,low cost and little power consumption.Undoubtedly,it will have wider applications in military and commercial fields.Aiming at the requirement of high estimation precision and real time in the real application,a method of extended Kalman filter based on model error predictive(MEP-EKF)was used for GFMIMU/GPS Integrated navigation system data fusion.The simulation results show that this method has better precision of the azimuth than that of EKF and unscented Kalman filter(UKF).Furthermore,MEP-EKF needs less computation time than UKF,only 10 percent of UKF.