Modelling and Simulation of Robust Navigation for Unmanned Air Systems (UASs) Based on Integration of Multiple Sensors Fusion Architecture

Unmanned air systems (UASs) are playing increasingly prominent roles in defense programs and defense strategy around the world. Technology advancements have enabled the development of large UASs and the creation of smaller, increasingly capable UASs. As recent conflicts have demonstrated, there are numerous military applications for UASs including reconnaissance, surveillance, battle damage assessment, and communications relays. Civil and commercial applications are not as well developed, although potential applications are extremely broad in scope. Possible applications for UAS technology include environmental monitoring, forest fire monitoring, homeland security, border patrol, drug interdiction, aerial surveillance and mapping, traffic monitoring, precision agriculture, disaster relief, ad-hoc communications networks, and rural search and rescue. For many of these applications to develop into maturity, the reliability of UASs will need to increase, their capabilities will need to be extended further, their ease of use will need to be improved, and their cost will have to come down. In addition to these technical and economic challenges, the regulatory challenge of integrating UASs into the national and international air space needs to be overcome. In this paper the fusion between the data derived from the magnetometer, rate-gyro, accelerometer, pitot tube, pressure and the global positioning system (GPS) is integrated in one system using an extended kalman filter (EKF) which uses a linear error model to estimate the errors in the states for unmanned aerial vehicle (UAV) to enhance its performances. The proposed system introduces a robust navigation for UAVs flight dynamics with decrease the faults in operational environment.