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Passive air defense threat detection and location for UAV swarms based on dynamic Bayesian networks

  • Northwestern Polytechnical University Xian

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Scopus citations

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.

Original languageEnglish
Title of host publication2011 International Conference on System Science, Engineering Design and Manufacturing Informatization, ICSEM 2011
Pages167-171
Number of pages5
DOIs
StatePublished - 2011
Event2011 International Conference on System Science, Engineering Design and Manufacturing Informatization, ICSEM 2011 - Guiyang, China
Duration: 22 Oct 201123 Oct 2011

Publication series

Name2011 International Conference on System Science, Engineering Design and Manufacturing Informatization, ICSEM 2011
Volume2

Conference

Conference2011 International Conference on System Science, Engineering Design and Manufacturing Informatization, ICSEM 2011
Country/TerritoryChina
CityGuiyang
Period22/10/1123/10/11

Keywords

  • DBN
  • UAV
  • air defense
  • classification
  • communication
  • detection
  • dynamic Bayesian network
  • inference
  • location
  • swarm
  • unmanned aerial vehicles

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