INS Simulation for Inertial Navigation Systems

This article discusses a simulation program for inertial navigation systems developed using MATLAB's INS toolbox. In inertial navigation systems, this simulation program serves to model and analyze the behavior of navigation systems under various conditions. The program typically implements core algorithms including attitude calculation through quaternion or direction cosine matrix methods, velocity integration using mechanization equations, and position determination through Earth model integrations. It simulates sensor errors such as gyroscope drift and accelerometer bias to evaluate system performance. The simulation workflow involves initializing sensor parameters, processing inertial measurement unit (IMU) data through navigation equations, and implementing error compensation algorithms. To enhance navigation system accuracy and reliability, the program allows for testing different Kalman filter configurations for sensor fusion and error estimation. Researchers can optimize the simulation by modifying integration methods (e.g., Runge-Kutta algorithms), adjusting noise models, or incorporating GPS/other sensor integration through extended Kalman filter implementations. Furthermore, the program can be extended to integrate with other technologies like SLAM algorithms or multi-sensor fusion frameworks to achieve improved navigation performance and user experience.