A robust Kalman filter for SINS/GPS integrated Navigation

Abstract

To solve the problem of errors accumulate over time of strapdown inertial navigation system (SINS), a SINS and Global positioning system (GPS) integrated system is proposed considering their complementary characteristics. We employ loosely-coupled method and Kalman filter (KF) algorithm for data fusion and errors correction to obtain more accurate location information. The process noise and measurement noise in observation process are treated as Gaussian white noise, and their expectations will be given in advance. Compared to SINS, the proposed SINS/GPS integrated system has significantly better navigation accuracy and robustness according to simulation and a field experiment's results.