Distributed UAV Swarm Placement Optimization for Compressive Sensing based Target Localization

Cooperative target localization using unmanned aerial vehicles (UAVs) swarm is gaining popularity in many applications such as disaster detection, crowd surveillance, and rescue operation. In this paper, a UAV swarm, featuring a single antenna RF transceiver per UAV, is considered and regarded as a distributed MIMO radar system for a problem of target localization. To reduce the number of measurements and computational complexity, the compressive sensing based (CS-based) algorithm is applied. In most of the existing works in radar community, the assumption of fixed radar positions is adopted. Here, by exploiting the mobility of the UAV swarm, we propose two UAV placement optimization algorithms to improve the performance of CS-based target localization. Simulation results show that compared to the random UAV placement, the mutual coherence of the measurement matrix is reduced and the localization root mean square error (RMSE) is significantly improved under the proposed UAV placement. Moreover, the RMSE performance can be further improved by increasing the number of UAVs.