A Low-Cost Dead Reckoning Navigation System for an AUV Using a Robust AHRS: Design and Experimental Analysis

• Published in: IEEE journal of oceanic engineering 2018-10, Vol.43 (4), p.927-939
• Main Authors: Sabet, Mohammad Taghi, Mohammadi Daniali, Hamidreza, Fathi, Alireza, Alizadeh, Ebrahim
• Format: Article
• Language: English
• Subjects: Algorithms; Attitude indicators; Attitudes; Autonomous navigation; Autonomous underwater vehicle (AUV); Autonomous underwater vehicles; Dead reckoning; Dynamic models; Extended Kalman filter; external disturbances; Frameworks; Global Positioning System; Global positioning systems; GPS; Inertial sensing devices; Kalman filters; Low cost; Magnetic disturbances; Magnetic sensors; Magnetometers; Microelectromechanical systems; model-aided dead reckoning (DR) navigation; Modelling; Motion control; Navigation; Navigation systems; Pitch (inclination); Positioning systems; Reference systems; robust attitude and heading reference system (AHRS); Rolling motion; Satellite navigation systems; Sensors; Underwater vehicles
• ISSN: 0364-9059; 1558-1691
• DOI: 10.1109/JOE.2017.2769838

In navigation and motion control of an autonomous vehicle, estimation of attitude and heading is an important issue, especially when the localization sensors such as global positioning system (GPS) are not available and the vehicle is navigated by the dead reckoning (DR) strategies. In this paper, based on a new modeling framework, an extended Kalman filter (EKF) is utilized for estimation of attitude, heading, and gyroscope sensor bias using a low-cost microelectromechanical system (MEMS) inertial sensor. The algorithm is developed for accurate estimation of attitude and heading in the presence of external disturbances including external body accelerations and magnetic disturbances. In this study, using the proposed attitude and heading reference system (AHRS) and an identified surge dynamic model of an autonomous underwater vehicle, a low-cost model-aided DR navigation system has been designed for an AUV. The proposed algorithm application is evaluated by experimental tests in different acceleration bound and existence of external magnetic disturbances for an AUV. The results indicate that the roll, pitch, and heading are estimated by mean value errors about 0.35°, 0.29°, and 1.27°, respectively. Moreover, they indicate that a relative navigation error about 8% of the traveling distance can be achieved using the developed approach in during GPS outages.