Inertial Navigation + GPS Integrated Navigation System

This article explores the integrated navigation system combining Inertial Navigation and GPS - a classical algorithm approach that deserves attention. Inertial Navigation System (INS) operates using inertial components like mechanical gyroscopes and accelerometers, applying Newton's second law to calculate navigation information through velocity and position integration. In practical implementation, INS algorithms typically involve numerical integration methods like Runge-Kutta for motion equations and Kalman filters for state estimation. The GPS-INS integrated navigation combines GPS-provided position data with INS-derived velocity and attitude information, creating a complementary system that enhances both accuracy and reliability. This fusion is commonly implemented using Kalman filter algorithms where the prediction step utilizes INS data while the correction step incorporates GPS measurements. Key functions in such systems include sensor data preprocessing, coordinate transformation matrices, and error state estimation routines. This integrated navigation technology finds extensive applications in aviation, marine navigation, and autonomous systems, attracting significant research interest from scientists and engineers worldwide. We strongly recommend mastering this classical algorithm for its practical implementation value in modern navigation systems.