基于UKF的低成本SINS/GPS组合导航系统滤波算法

针对MIMU的精度不高,会带来较大的初始对准误差角,如果继续采用传统的小干扰线性方程就会给滤波带来很大误差,甚至发散。针对这个问题,对低成本SINS/GPS组合导航系统建立了基于四元数误差模型的非线性滤波方程,并采用了UKF非线性滤波方法。针对四元数误差模型单纯使用UKF方法无法估计加计零偏和陀螺漂移的问题,提出将UKF和EKF相结合的算法,仿真结果表明,比起扩展卡尔曼滤波以及采用传统小干扰线性方程的卡尔曼滤波,这种方法能够提高姿态误差角特别是方位误差角的估计精度。

Nonlinear algorithm based on UKF for low-cost SINS/GPS integrated navigation system

Aimed at a low-cost scheme of SINS/GPS integrated navigation system using low precision inertial sensors(MIMU),the precise error equations is basic for filter.The psi-angle model has been widely used.However,the model is not effective for a system with large attitude errors because the neglected error terms in the model degrade the performance of a designed filter.This paper establishes nonlinear mathematics model based on quaternion error equations.For essential nonlinear systems,the unscented Kalman filter(UKF) has some advantages such as high estimation precision,fast convergence,and so on.In order to deal with the problem that the inertial sensors errors can not be estimated using UKF method,an improved algorithm combining UKF and extended Kalman filters is proposed.The simulation results show that this method has better precision of all misalignment angles especially the azimuth one than that of extended Kalman filters.