Model-aided inertial navigation for underwater vehicles

Abstract

This paper reports the development and experimental evaluation of a complete model-aided inertial navigation system (INS) for underwater vehicles. The navigation system is novel in that accurate knowledge of the vehicle dynamics is utilized for aiding the INS, and the performance is evaluated using real data collected by an autonomous underwater vehicle (AUV). Together with real-time sea current estimation, the output from a kinetic vehicle model describing the dynamics is integrated in the navigation system. The presented experimental results verify that with merely an addition of software and no added instrumentation, it is possible to significantly improve the accuracy and robustness of an INS by utilizing the physical insight provided by a kinetic vehicle model. To the best of our knowledge, this paper is the first report on the implementation and experimental evaluation of a complete model-aided INS for underwater vehicle navigation. The proposed approach shows promise to improve underwater navigation capabilities both for systems lacking disparate velocity measurements, typically from a Doppler velocity log (DVL), and for systems where the need for redundancy and integrity is important, e.g. during sensor dropouts or failures, or in case of emergency navigation. The reported methodology is applicable to a large group of submersibles, as well as land and aerial crafts and robots.