Low-cost and high performance ultra-tightly coupled GPS/INS integrated navigation method

In this paper, a low-cost, high-performance ultra-tightly coupled GPS/INS integrated navigation method is proposed. The measurement of the integration Kalman filter is generated from a moving average filter in the proposed method. A moving average filter is inserted between the signal tracking error estimator and the integration Kalman filter to avoid other measurement noise reduction methods' limitations and the error of the MEMS inertial sensor is modeled as bias repeatability and bias stability in the proposed method. A new integration Kalman filter is derived to compensate the time delay caused by the moving average filter. The proposed method improves signal tracking performance of the GPS receiver and resolves the problem caused by the difference between correlator output rate and integration Kalman filter update rate. In addition to these, the proposed method resolves the performance degradation problem of the MEMS inertial sensors. In order to verify the proposed method, an experimental platform is constructed, which consists of a GPS/IMU signal generator, a GPS SDR S/W module and a GPS/INS S/W module. The results in weak signal environment show that the proposed method gives better navigation performance than other methods without the moving average filter and/or the model of bias stability of MEMS IMU.