Attitude estimation of an unmanned surface vehicle using MEMS-AHRS and GNSS

This paper presents an attitude estimation method used for navigation of an unmanned surface vehicle. The method utilizes measurements by global navigation satellite system (GNSS) as well as microelectromechanical systems-attitude heading reference system (MEMS-AHRS). Since magnetic field measurement by the MEMS-AHRS is vulnerable to internal and external disturbances, the magnetic field measurement is corrected using GNSS measurement. While some of the previous methods use single axis fiber optic gyro (FOG) for the improvement of the attitude estimation, the proposed method uses GNSS, which is less expensive than single axis FOG. Some of the MEMS-AHRS already includes GNSS, and in that case, use of GNSS is a practical approach. This paper focuses on use of GNSS for improvement of attitude estimation. The method uses Kalman filter approach to incorporate the GNSS data and MEMS-AHRS measurements. The results show improvements over Kalman filter or nonlinear explicit complementary filter (NECF) which uses only MEMS-AHRS.