Complete MATLAB Algorithm for Pose Estimation

This article presents a complete MATLAB algorithm designed for pose estimation applications. The algorithm incorporates robust mathematical modeling for position and orientation tracking, utilizing techniques such as quaternion operations, Kalman filtering for sensor fusion, and coordinate system transformations. Following extensive research and validation, we have secured copyright protection to maintain its proprietary nature. While we encourage knowledge sharing within the technical community, any unauthorized publication or redistribution is strictly prohibited. We take copyright infringement seriously and will pursue legal action against violations. This implementation guide demonstrates how to process inertial measurement unit (IMU) data, calculate Euler angles, and implement iterative optimization for improved accuracy. The content aims to assist researchers and engineers in understanding pose estimation methodologies while providing practical implementation insights for related fields.