Joint Optimization of UAV Deployment and Directional Antenna Orientation for Multi-UAV Cooperative Sensing

In this paper, we consider the problem of cooperative sensing via a system of multi-unmanned aerial vehicles (UAVs), where each UAV is equipped with a directional antenna to cooperatively perform detection tasks for several targets of interest. To measure the perception ability of the system, we choose the detection probability as the metric, aiming to maximize the sum detection probability of targets by jointly optimizing UAVs’ deployment and directional antenna orientations. To tackle the inherent nonconvexity of the formulated problem, we first decompose it into two sub-problems, i.e., a slave problem for optimizing the antenna orientations with a given UAVs’ deployment, and a master problem for optimizing the UAVs’ deployment. By virtue of the slave problem structure, an efficient block coordinate descent (BCD) algorithm is developed. Meanwhile, to deal with the lack of the closed expression of the sum detection probability with respect to the UAVs’ deployment, we further develop an iterative algorithm to acquire an efficient solution with the aid of Gibbs Sampling (GS) approach. Extensive simulations demonstrate the efficacy of the proposed algorithm.

I. Introduction

Unmanned aerial vehicles (UAVs) have been widely used across the world for civilian, commercial, as well as military applications [1], [2]. Among applications of UAVs, UAV swarm-based spectrum sensing is gaining ever-increasing popularity due to the highly controllable maneuverability, on-demand coverage and line-of-sight (LoS) links. In such scenario, a group of UAVs equipped with precise receiving antennas and intelligent sensors collaborate to perform sensing tasks to the interested targets. Due to these desirable features, the UAV swarm-based sensing has recently drawn considerable interests from both civil and defense applications [3].