The research on sea-bottom terrain tracking by AUV based on Least Squares Method and Extended Kalman Filter

This paper studies the problem of undersea bottom-following through using the Autonomous Underwater Vehicle(AUV) equipped with Altimeter and Depth gauge. We can improve the ability of AUV to perceive the information of the seabed by using the Extended Kalman Filter(EKF) to complete the information fusion of data comes from Altimeter and Depth gauge. The seabed terrain slope is estimated by the least square method and then the trend of the seabed terrain can be predicted, which improve the ability of the AUV to track the seabed terrain. In the end, the seabed terrain tracking algorithm was verified by Matlab simulation, and the experimental results showed that the proposed method was effective.