Communication-Efficient Coordinated RSS-Based Distributed Passive Localization via Drone Cluster

Multi-UAV passive localization via received signal strength (RSS) is extremely important for wide applications such as rescue and battlefield combat. However, the energy consumption of UAVs is a key issue in this UAVs-enabled application. Usually, the communication overhead plays an important role in the energy consumption. To address this problem, we design two distributed methods for this multi-UAV system with considerable performance under low communication overhead. Firstly, a distributed majorize-minimization (DMM) method is proposed. To accelerate its convergence, a tight upper bound of the objective function from the primary one is derived. Furthermore, a distributed estimation scheme using the Fisher information matrix (DEF) is presented, only requiring one round of communication between edge UAVs and central UAV. Simulation results show that the proposed DMM outperforms the existing distributed iterative methods in terms of root of mean square error (RMSE) under low communication overhead. Moreover, the most communication-effective DEF with local search estimation performs much better than the proposed DMM in terms of RMSE, but has a higher computational complexity.

I. Introduction

Unmanned Aerial Vehicle (UAVs) equipped with wireless communication modules and appropriate sensors have allowed appreciable paradigms in civilian and military applications. The wireless sensor network (WSN) formed by the cooperation between multiple UAVs can be the key support to applications and terrestrial networks, users, and communicating entities [1], [2]. As one of UAV-enabled applications, passive localization through multiple UAVs has been active in wide applications [3]–[6], such as rescue and battlefield combat. Compared to traditional localization paradigms, such as cellular localization and satellite localization, the UAV-enabled localization has distinctive advantages. Rapid deployment, flexible relocation and high chances of experiencing line-of-sight propagation path features have been perceived as promising opportunities to provide difficult service. Besides, the localization uncertainty can be eliminated effectively via corresponding trajectory planning of UAVs [6]. The passive location techniques use the location related measurements of the radio frequency signals from the target. The popular types of techniques are mainly divided into time of arrival (TOA) [7], direction of arrival (DOA) [8] and received signal strength (RSS) [9]. Although less accuracy, the RSS-based localization is cost-effective and can be conveniently implemented, which fit the demands of UAV-enabled application well.