IoT Based Optimal UAV Tracking Method Considering Noise and Cyber Attacks

This paper proposes an optimal signal processing based UAV tracking algorithm considering noise and cyber attacks in sensory measurements. After representing the UAV dynamics into a state-space form, the UAV embedded IoT sensors and IoT gateways are used to obtain measurements at the control center. The prediction and correction based optimal Kalman filtering algorithm is proposed to know the UAV states such as velocity and pitch angle. Extensive numerical results show that the proposed algorithm can properly track the UAV states within 0.9-0.45 sec.