Decentralized UAV Swarms for Ground Target Protection in GPS- and Communication-Denied Environments
With the increasing use of UAVs in military operations, the demand for defense systems against UAV attacks has grown. This paper proposes a method for ground target protection using autonomous UAV swarms in GPS- and communication-denied environments. The approach relies solely on onboard sensors and relative measurements for target tracking and swarm coordination, employing a decentralized encirclement technique that adapts to target motion. Experiments with real robots validated its effectiveness in detecting, encircling, and intercepting hostile UAVs.
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[Submitted on 22 Jul 2026]
Title:Decentralized UAV Swarms for Ground Target Protection in GPS- and Communication-Denied Environments
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Abstract:The presence of UAVs in military operations has recently increased, also increasing the demand for defense systems against UAV attacks. UAVs can also be used as countermeasures. Most available methods rely on UAV-to-UAV communication and global positioning. However, such resources may not be available in modern warfare scenarios. To address these limitations, we propose a pipeline for ground-target protection against UAV attacks that employs autonomous swarms of UAVs. We assume a communication- and GPS-denied environment in which the UAVs use onboard sensors to track the target and coordinate as a swarm. We developed Kalman filters to estimate the states of unknown targets and the positions of UAVs in the swarm using only relative measurements. Also, our strategy is to encircle the target of interest to maximize coverage. To achieve that, we propose a decentralized swarm encirclement technique that adapts to the target's motion. Our approach was extensively validated using real robots, demonstrating its effectiveness in detecting, encircling, and intercepting hostile UAVs.
Comments: Accepted for publication at the 2026 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2026)
Subjects:
Robotics (cs.RO)
Cite as: arXiv:2607.20710 [cs.RO]
(or arXiv:2607.20710v1 [cs.RO] for this version)
https://doi.org/10.48550/arXiv.2607.20710
arXiv-issued DOI via DataCite (pending registration)
Submission history
From: Dimitria Silveria [view email] [v1] Wed, 22 Jul 2026 20:26:07 UTC (34,143 KB)
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