Kalman Filter for Cross-Noise in the Integration of SINS and DVL

The integration of strapdown inertial navigation system and Doppler velocity log (SINS/DVL) is widely used for navigation in automatic underwater vehicles (AUVs). In the integration of SINS/DVL, the velocity measured by DVL in body frame should be projected into navigation frame with the help of attitude matrix calculated by SINS to participate in data fusion. In the process of data fusion based on standard Kalman filter, the errors in calculated attitude matrix are characterized by state variance and process noise while the errors in measurement vector from DVL are by measurement noise. But the above projection will bring process noise into measurement noise, and thus the assumption of the independence between process noise and measurement noise will not stand. In this paper, the forming mechanism of cross-noise in SINS/DVL is studied in detail and Kalman filter for cross-noise is introduced to deal with this problem. Simulation results indicate that navigation accuracy, especially the position accuracy, can be improved when the cross-noise is processed in Kalman filter.