UAV-Based Target Tracking: Integrating Sensing into Communication Signals

Abstract

Due to the high mobility and deployment on-demand, unmanned aerial vehicle (UAV) is becoming more popular in future wireless communications as well as sensing systems. In this paper, we study a UAV-enabled network for the ground user tracking, which can be regarded as a “free lunch” as the purpose of UAV s is to carry out some specific communications tasks. Relying on the integrated sensing and communication (ISAC) technology, the UAVs are capable of extracting the time-delay and Doppler measurements. In particular, to exploit the temporal correlation of the user location for accurate tracking, we propose an extended Kalman filtering (EKF)-based framework. Moreover, we utilize the geometrical relationship of multiple measurements to estimate the velocity, which can overcome high error velocity estimation by single base station (BS). Numerical results show that with the aid of UAV ISAC signals, our proposed algorithm significantly outperforms the benchmark scheme using a single BS for target tracking.