Abstract
This paper presents implementations based on an extended Kalman filter (EKF) and an unscented Kalman filter (UKF) for navigation of an autonomous underwater vehicle (AUV). Maintaining an accurate localization of an AUV is difficult because radio frequency signals, such as the global position system (GPS) signals, are highly attenuated by water. To address this problem, this paper proposes a new navigation method based on an inertial navigation system (INS) aided by a Doppler velocity log (DVL) and a short baseline (SBL). The presented EKF and UKF fuse the information from sensors to produce an accurate estimate of positions. Results from simulations yield that EKF and UKF based navigation methods have the similar performance and navigation accuracy. The proposed navigation method has been experimentally validated using the navigation data acquired from simulations and water tests.
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