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Particle Swarm Guidance System for Autonomous Unmanned Aerial Vehicles in an Air Defence Role

Published online by Cambridge University Press:  10 December 2007

Alec Banks*
Affiliation:
(Tornado In-service Software Maintenance Team)
Jonathan Vincent
Affiliation:
(Bournemouth University)
Keith Phalp
Affiliation:
(Bournemouth University)
*

Abstract

This work investigates the utilisation of Particle Swarm Optimisation (PSO) for the non-deterministic navigation of Unmanned Aerial Vehicles (UAVs), allowing them to work cooperatively toward the goal of protecting a wide area against airborne attack. To negate the PSO's inherent weakness in dynamic environments, a neighbourhood scheme is proposed that not only enables the efficient interception of targets several times faster than the UAVs but also facilitates the maintenance of effective airspace coverage. Empirical results suggest that these techniques may indeed be of use in autonomous navigation systems for UAVs in air defence roles.

Type
Research Article
Copyright
Copyright © The Royal Institute of Navigation 2007

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References

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