Abstract
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.
Highlights
Automatic underwater vehicles (AUVs) are widely used in missions of science, military, and commerce, such as survey of ocean resources and cable tracking
The forming mechanism of cross-noise in Strapdown inertial navigation system (SINS)/Doppler velocity log (DVL) is studied in detail, a Kalman filter for cross-noise is introduced to deal with this problem; in this filter, cross-noise is added to the standard Kalman filter; and the need for processing this cross-noise is verified by simulation
The cross-noise problem in the integration of SINS/DVL is studied in this paper
Summary
Automatic underwater vehicles (AUVs) are widely used in missions of science, military, and commerce, such as survey of ocean resources and cable tracking. As a navigation method based on integration operation, navigation errors will accumulate with time due to the existence of inertial sensor biases and initial misalignment angles in SINS [3,4,5]. Without other aided navigation systems, the accuracy of SINS/DVL integration with certain sensor precision for long time and long distance mission is mainly determined by data fusion algorithm [4,5,6]. The cross-problem caused by the projection from process noise to measurement noise in SINS/DVL will be analyzed in detail
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