Professor of School of Engineering, Design and Built Environment, Western Sydney University, Australia. His research interests cover Industry 4.0, Additive Manufacturing, Advanced Engineering Materials and Structures (Metals and Composites), Multi-scale Modelling of Materials and Structures, Metal Forming and Metal Surface Treatment.
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.
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