V3I6P20

Development of a Comprehensive Complex Error Model for Inertial Measurement Units and Application of Unscented Kalman Filtering for Enhanced Attitude Estimation 

Dao Thanh Bang^1*

Abstract

This paper presents a method for simulating and evaluating a ship orientation system based on a complex Inertial Measurement Unit (IMU) sensor model combined with the Unscented Kalman Filter (UKF). Unlike studies that only consider ideal sensors or simplified models, the sensor model in this study is constructed with consideration of multiple real-world errors such as scale factor, axis misalignment, bias random walk, white noise, and delay. The simulation system generates a reference trajectory with three Euler angles, while producing measurement data from both simple and complex sensor models. The UKF algorithm is implemented to estimate the attitude and is compared with the conventional pure gyro integration method. Results show that UKF combined with the complex sensor model improves orientation accuracy, reduces accumulated error, and enhances robustness against noise. In addition, a comparative analysis between the simple and complex sensor models is conducted to clarify the impact of sensor errors on the quality of attitude estimation.

Keywords:

Orientation system; complex IMU sensor; UKF; sensor error; inertial simulation; gyroscope; accelerometer; Euler angles; signal filtering; navigation system.