Multi-UAV cooperative MUSIC localization and PLW power allocation for radar jamming

Abstract In modern communication and electronic systems, unmanned aerial vehicle (UAV) swarm networks have emerged as a critical component due to their distributed collaboration capabilities, yet dynamic network characteristics pose significant challenges in real-time resource allocation and spatial perception. Traditional methods for collaborative positioning and jamming power distribution often suffer from discrete execution modes, high computational complexity, limiting the effectiveness in complex electromagnetic environments. To address these limitations, this paper proposes a collaborative optimization framework that integrates multiple signal classification (MUSIC) localization with a path loss-aware weighted (PLW) allocation algorithm, aiming to enhance radar jamming effectiveness in contested electromagnetic environments. By leveraging MUSIC-based azimuth angle estimation and triangular geometric relationships, the system dynamically computes jammer-radar distances and azimuth angles, which are fed into the PLW algorithm that enforces minimum power constraints. Simulation results demonstrate that the proposed method achieves 3-5 dB gains in the interference suppression coefficient (J/S) and significant enhancements in suppression probability. These advancements provide a scalable solution for multi-UAV adversarial missions by offering novel technical pathways for real-time target protection in contested spectral environments, and enhancing the generalization ability of multi-UAV strategies.