Comparison of Attitude Estimation Methods for Underwater Navigation

Nak Yong Ko 1, Seokki Jeong 2, Hyun-Taek Choi 3, and Yong Seon Moon 4
1. Dept. Electronic Engineering, Chosun University, Gwangju, Korea
2. Dept. Control and Instrumentation Engineering, Chosun University, Gwangju, Korea
3. Korea Institute of Ocean Science and Technology, Daejeon, Korea
4. Dept. Electronic Engineering, Sunchon National Univerity, Sunchon, Korea
Abstract—This paper compares methods for attitude estimation which uses MEMS-AHRS (Microelectro-mechanical Systems - Attitude Heading Reference System) for underwater vehicles navigation. Though MEMS-AHRS is cheap in price, light in weight, small in volume, and easy to use instrument for attitude determination, the yaw estimate using the AHRS is not as reliable as the estimates of roll and pitch. This is because the yaw estimation depends primarily on the magnetic field measurement, and the magnetic field measurement of the AHRS is vulnerable to magnetic interference induced by the vehicle and instrument itself and the environment surrounding the vehicle. This paper compares four major approaches: nonlinear explicit complementary filter (NECF), extended Kalman filter (EKF), sine rotation vector (SRV) method and complementary filter (CF). The methods are tested through experiments in a test tank. The results show that the errors in yaw show notable difference between the methods. NECF and SRV show improvement over the EKF and CF. This paper provides a practical comparison of the underwater attitude estimation methods through experiments, and the results can be used as reference to be compared with other methods to be developed. Also, this can help adapt the methods appropriate for a specific underwater application.

Index Terms—Attitude estimation, underwater vehicle, attitude heading reference system, gyro, magnetic field

Cite: Nak Yong Ko, Seokki Jeong, Hyun-Taek Choi, and Yong Seon Moon, "Comparison of Attitude Estimation Methods for Underwater Navigation," International Journal of Mechanical Engineering and Robotics Research, Vol. 7, No. 3, pp. 285-291, May 2018. DOI: 10.18178/ijmerr.7.3.285-291
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