Long Baseline beacon position estimation

One way to perform Autonomous Underwater Vehicle (AUV) localization is to employ static acoustic beacons to form a Long Baseline system. However, errors in the estimated positions of the beacons will negatively affect vehicle localization. To solve this problem we propose a beacon position estimation technique using an Extended Kalman Filter, and we also investigate how to improve estimation performance. Our solution is able to successfully estimate beacon positions and we show estimation performance by appropriately defining the vehicle trajectory.