Evaluation of GPS Data for Navigational Solution and Error Reduction Using Kalman Filter

Now a day navigation system has been receiving a high demand for numerous applications. Among these systems global positioning system (GPS) is more popular which is frequently using for the aircraft for navigation and autonomous navigation purposes. However GPS suffers because of continuity and reliability problems in many applications. In this proposed model a novel architecture of Kalman filter has been selected to integrate with GPS to overcome above problem. A software defined radio (SDR) is used for the GPS data extraction which is nothing but an analog to digital converter. The integrated GPS with Kalman filter system can be able reduce velocity, position and attitude errors compared to the many conventional algorithms. To verify this technique a real time model is created using Simulink/Matlab. The simulated outcomes confirm the advantages of assimilated system in both urban and open areas and suitable for real time implementations.