Strapdown Attitude Determination for MEMS IMU Data Using Fourth-Order Runge-Kutta Algorithm

In this study, we investigate a novel approach for strapdown attitude determination of MEMS IMU data based on the fourth-order Runge-Kutta algorithm. This method leverages advanced mathematical techniques to enhance the accuracy and stability of attitude calculation through rigorous analysis of sensor data. The implementation involves quaternion integration using the Runge-Kutta method (RK4) with a typical code structure that includes gyroscope data preprocessing, quaternion propagation, and normalization steps. Key functions handle angular rate integration with adaptive step size control and incorporate correction mechanisms for sensor errors. Our research demonstrates significant improvements in solution accuracy compared to traditional methods, along with superior performance across various application scenarios. The algorithm's robustness makes it particularly suitable for real-time embedded systems where computational efficiency and precision are critical. We believe this approach will play a vital role in future MEMS IMU data processing, providing substantial support for research and applications in related fields.