Application of Kalman Filtering in Navigation Solution Computation

This documentation accompanies a compressed file containing materials related to GPS measurement data simulation and inertial navigation solution computation, along with a detailed exploration of Kalman filtering applications in navigation processing. The simulation component enables generation of GPS measurement data under various environmental conditions, while the inertial navigation module computes navigation parameters through numerical integration of motion equations. In practical implementations, Kalman filtering serves as an optimal estimator that fuses GPS and inertial measurement unit (IMU) data using prediction-correction cycles - with state transition matrices modeling system dynamics and measurement matrices handling observation updates. The archive's contents provide comprehensive understanding of these techniques through MATLAB/Python code examples featuring key functions like state prediction, covariance propagation, and measurement update routines. These resources offer valuable insights and methodologies for real-world project applications in navigation system development.