A MIMU/GPS/magnetometer integrated alignment method based on sequential robust estimation

Abstract

For a micro-electro-mechanical system inertial measurement unit (MEMS-IMU), Global Positioning System (GPS) and magnetometer integrated navigation system, the procedure of initial alignment is a necessity. However, both magnetometer and GPS receiver are susceptible to external complex environment. Outliers in the observations of the two devices are inevitable. In order to reduce the influence of the outliers and improve the initial alignment accuracy, a sequential robust Kalman filter (SRKF) algorithm based on the square dimension of the innovation vector is proposed. The proposed SRKF algorithm can reasonably decrease the contribution of outlier affected elements of the observation vector in an element-wise way. Robust factor, used to suppress the influence of outliers, is constructed according to the Mahalanobis distance and the Chi-square distribution significance level. The results of different simulations and field tests all indicate the feasibility and the effectiveness of the proposed method.