Research on an improved dead reckoning for AUV navigation

It is difficult for Autonomous Underwater Vehicle (AUV) to satisfy the demand of long time navigation because of the installation angle´s deviation error as well as the measurement error. The data collected by GPS were filtered using Extended Kalman Filter (EKF) prior to being utilized in the paper. Besides, the installation angle´s deviation error of DVL was compensated. The paper does some deep research on the improved dead reckoning method, and the performance is evaluated using real data collected by an AUV. The presented experimental results verify that the improved dead reckoning method can significantly enhance the accuracy of navigation, which for the vehicle position was estimated to be less than 0.5% both in north and east.