Distributed Optimization-Based Joint Task Assignment and Bandwidth Allocation for UAV-Enabled Jammer Swarm

Abstract

Owing to the cost-efficiency, low observability and swarm coordination capability, UAV-enabled swarm jamming is recognized as a significant countermeasure against networked radar systems. To fully exploit the collaborative jamming effectiveness of the swarm, it is critically important to optimize the task assignment among jammers. However, existing jamming task assignment algorithms still exhibit insufficient consideration of non-ideal factors in adversarial scenarios. 1) The frequency agility of radars is frequently overlooked, leading to the rare consideration of bandwidth allocation for jammers. 2) The vulnerability of jammers is often neglected, resulting in insufficient consideration being given to the robustness of task assignment algorithms. To address these issues, a distributed optimization-based joint task assignment and bandwidth allocation method is studied for the UAV-enabled jammer swarm in this paper. Firstly, we design the utility function of joint task assignment and bandwidth allocation, and formulate the optimization problem model. Subsequently, to facilitate the implementation of distributed optimization, a decomposition approach based on coalition formation games (CFG) and alternating direction method of multipliers (ADMM) is proposed for the formulated joint task assignment and bandwidth allocation problem. Finally, a distributed optimization-based joint task assignment and bandwidth allocation algorithm is proposed. Experimental results indicate that the proposed method demonstrates higher optimization efficiency and robustness compared to the centralized optimization.