High accuracy Navigation System using GPS and INS system integration strategy

This paper proposes a position and attitude observer based on INS and GPS. Design and test results of an adaptive dual-rate Extended Kalman Filter(EKF) estimator for fusing data from Global Positioning Systems (GPS) and an Inertial Navigation System (INS) in order to estimate the position, velocity, and attitude. The dual-rate EKF consists of a high-speed filter and a low-speed filter, the high-speed filter fuses data from Real-Time Kinematic (RTK) GPS and INS, the low-speed filter fuses data from pseudorange GPS and INS. This solution designed to isolate the noise from pseudorange and realize the complementary of real-time performance and high precision. The solution yields exponential convergence of the attitude and position estimates. The implementation results show that the proposed method resolves an integer vector identical to that of the original method and achieves state estimation with centimeter global positioning accuracy.