An integrated navigation algorithm for AUV based on Pseudo-range measurements and error estimation

The Long Baseline (LBL) system is very important to precisely localize autonomous underwater vehicles (AUVs) close to the sea bottom in deep water. But the calibration error of the LBL beacons and the pseudo-range measurement caused by the motivation of the AUV, both them dilute the accuracy of LBL acoustic position. This paper proposes a quantitative description of the calibration error of beacons and pseudo-range how they reduce the LBL acoustic position precise. And then this paper proposes an integrated navigation algorithm for AUV, which integrates inertial navigation and LBL acoustic location to reduce the influence of the calibration errors of beacons and pseudo-range by online calibrating the beacon location errors and compensating the motivation of AUV to pseudo-range model. We name this algorithm as Pseudo-range and SLAM of beacons EKF (P-SLAM EKF). Through the sea trials of Qianlong-1, our algorithm proves very reliable and effective.