MATLAB Implementation of Inertial Navigation Simulation

This document discusses a MATLAB program for inertial navigation simulation, which includes trajectory generation capabilities. The implementation typically involves creating motion profiles using mathematical models that simulate vehicle dynamics. Key functions may include waypoint-based trajectory generation, acceleration/deceleration profiles, and coordinate system transformations. For performance optimization, developers can implement numerical integration methods like Runge-Kutta algorithms for motion equations and employ quaternion-based orientation calculations to avoid gimbal lock issues. The program structure usually consists of sensor error modeling (gyroscope drift, accelerometer bias), navigation algorithm implementation (strapdown inertial navigation system), and position/velocity updating loops. Practical applications span autonomous vehicle testing, drone navigation simulation, and military system development. Further research directions include integrating GPS/INS fusion using Kalman filters, enhancing simulation fidelity with environmental factors, and implementing real-time hardware-in-the-loop testing capabilities. This domain offers significant opportunities for advancing navigation system accuracy and developing robust simulation frameworks.