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Drone Swarm Strategy for the Detection and Tracking of Occluded Targets in Complex Environments

Computer Science

Drone Swarm Strategy for the Detection and Tracking of Occluded Targets in Complex Environments

R. J. A. A. Nathan, I. Kurmi, et al.

This innovative research conducted by Rakesh John Amala Arokia Nathan, Indrajit Kurmi, and Oliver Bimber presents an adaptive real-time particle swarm optimization strategy for drone swarms. The study reveals a significant improvement in target detection and tracking within densely forested areas, achieving up to 72% visibility in just 14 seconds, far surpassing traditional methods.

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Playback language: English
Abstract
This paper proposes an adaptive real-time particle swarm optimization (PSO) strategy for autonomous drone swarms to detect and track occluded targets in densely forested areas using synthetic aperture (SA) sensing. Simulation results demonstrate that the approach achieved a maximum target visibility of 72% within 14 seconds, significantly outperforming blind sampling strategies.
Publisher
Communications Engineering
Published On
Aug 02, 2023
Authors
Rakesh John Amala Arokia Nathan, Indrajit Kurmi, Oliver Bimber
Tags
particle swarm optimization
autonomous drones
target detection
occluded targets
synthetic aperture sensing
forest areas
real-time optimization

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