An Algorithm of GPS Navigation Based on Robust Self-Tuning Kalman Filtering

In order to avoid estimating the noise statistics in navigation, self-tuning Kalman filtering is introduced. When the system contains outliers in navigation, the estimated state vector by self-tuning Kalman filtering is influenced. To get a reliable result, an equivalent weight based on robust M-estimator is applied in the process of self-tuning Kalman filtering; robust self-tuning Kalman filtering is then proposed in this paper. A real kinematic system is tested. It is shown by real calculation that the robust self-tuning Kalman filtering is not only adaptively estimate the state vector, but also guarantee the reliability of the kinematic state estimates.