SWARM
Passive air defense threat detection and location for UAV swarms based on dynamic Bayesian networks
Viacheslav Zotov, Xiaoguang Gao
- Year
- 2011
- Citations
- 2
Abstract
This article introduces an algorithm for passive detection and location of air defense threats, based on dynamic Bayesian networks. The algorithm can be applied to mobile robot swarms and uses data on the loss of communication with a UAV for the detection and location of passive enemy air defense threats. The article describes the algorithm and illustrates its work by example.
Keywords
Computer scienceAdversaryMobile robotRobotBayesian probabilityDynamic Bayesian networkArtificial intelligenceReal-time computingComputer security
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