Fusion of sensor signals for navigation on an unmanned land vehicle prototype

In this study, IMU (inertial measurement unit) using the principle of dead reckoning and instead of GPS (global positioning system), a digital compass and encoder signals were blended by using a Kalman filter. Firstly, a mathematical model was established. After that, the mathematical model was turned into software via MATLAB-Simulink. In order to mount the sensors, an unmanned land vehicle prototype was manufactured and integrated with the real time data acquisition system. To test the sensor fusion algorithm, the output of the algorithm is compared with real position data.