Strapdown Inertial Navigation System and GPS Integrated Navigation

This document discusses the integration of Strapdown Inertial Navigation System (SINS) and GPS navigation technologies. The combination of these two navigation methods enhances both accuracy and reliability of the navigation system. For system optimization, we implemented the integrated navigation system using MATLAB, where key functions include sensor data acquisition, coordinate transformation, and Kalman filter implementation. By incorporating adaptive algorithms, particularly an adaptive Kalman filtering approach that automatically adjusts noise covariance matrices based on real-time measurement innovations, we successfully improved navigation performance with remarkable results. This implementation involved MATLAB's Signal Processing Toolbox for algorithm development and System Identification Toolbox for parameter tuning. The achievement is crucial for advancing navigation technology development while providing new methodologies and perspectives for future research in related domains. The code structure typically includes modules for inertial measurement unit (IMU) data preprocessing, GPS data decoding, navigation solution computation, and adaptive filter tuning loops.