Attitude Estimation Based on Multi-Frequency Motion Modeling and Complementary Filtering Using Inertial Sensor Data
Hoang Van Ngoi1*
Abstract
This paper presents a method for estimating the Euler angles (roll, pitch, yaw) of a ship through simulation of data from a multi-frequency wave model and processing by a complementary filter. The multi-frequency wave model is employed to reconstruct the actual oscillatory trajectory of the ship at sea, combined with simulated inertial measurement unit (IMU) data including accelerometers and gyroscopes, taking into account random noise and systematic errors. The Euler angles are estimated by integrating gyro data and by a complementary filter that combines gyroscope and accelerometer measurements. Simulation results show that the complementary filter reduces estimation errors compared with the gyro-only method, while enhancing the stability of the angle signals under sensor noise conditions. The proposed method can be applied in ship navigation and control systems operating in rough sea environments.
Keywords:
Euler angle estimation; IMU; ship; multi-frequency wave model; complementary filter; inertial sensors; signal filtering
