MEMS IMU and two-antenna GPS integration navigation system using interval adaptive Kalman filter

For a nonlinear integrated GPS/IMU system with an uncertain dynamic model, the standard extended Kalman filtering algorithm is no longer applicable. In this research, an interval filtering algorithm is applied to the uncertain integrated system. The system parameters uncertainties are described by intervals. The IAKF algorithm is established for the uncertain integrated system. The IAKF algorithm has the same structure as the standard extended Kalman filtering algorithm. The testing results indicate that the IAKF algorithm is effective for the uncertain nonlinear integrated system, and it can be used to test the chosen parameters of an integrated GPS/IMU system. Thus, the IAKF algorithm has good potential in real-time applications for nonlinear integrated systems with parameter and noise uncertainties.