Robust navigation based on bistatic radar and BiSensors for unmanned air systems (UASs) using integration of multiple sensors fusion architecture

Unmanned aerial vehicles (UAVs) have become one of the most popular and promising means for both military and civilian posts and academic research areas. Localization of the UAVs and persistent tracking of a UAV have vital importance to provide a UAV with navigation information and help to cope with getting lost permanently. Indeed, inertial navigation system (INS) and global positioning system (GPS) seem to be adequate for navigation of UAVs. However, an alternative augmented navigation system for UAVs should be taken into consideration since INS has accumulated errors and GPS always has the possibility of jamming and satellite signal loss. Unmanned air systems (UASs) are playing increasingly prominent roles in defense programs and strategy around the world. For many of 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 this paper the fusion between the data derived from the magnetometer, rate-gyro, accelerometer, pitot tube, pressure and the 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 UAV to enhance its performances. The proposed system introduces a robust navigation based on bistatic radar and bi-sensor for UAVs flight dynamics with decreases the faults in operational environment.