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Quickly planning TF/TA2 trajectory by artificial immune algorithm

  • Lifeng Liu
  • , Fei Yang
  • , Shuqing Zhang*
  • , Weihua Kong
  • , Yinxing Wang
  • *Corresponding author for this work
  • Shandong University of Technology
  • CAS - Institute of Geographical Sciences and Natural Resources Research
  • CAS - Northeast Institute of Geography and Agricultural Ecology

Research output: Contribution to journalArticlepeer-review

Abstract

Flight path planning by artificial immune algorithm approach met the requirements of aircraft's flyability and operation is proposed for the problem of single and double TF/TA2 flight path planning. Punishment function (affinity function) with comprehensive 3D threat information is designed. A comprehensive threat model is formed including dynamic and static threats and no-fly-zone. Accordingly, single and dual flight paths are planned by AIA, which have been compared with the paths by GA. The results show that, GA's planned a quick and longer path compared under simple threat environment; in complex environments, GA has high failure rate (greater than 95%) for single aircraft, but it is failed for double aircrafts. For the single and double aircrafts, AIA can provides one optimal and more candidate optimal flight paths.

Original languageEnglish
Pages (from-to)462-470
Number of pages9
JournalCehui Xuebao/Acta Geodaetica et Cartographica Sinica
Volume44
Issue number4
DOIs
StatePublished - 1 Apr 2015
Externally publishedYes

Keywords

  • Artificial immune algorithm
  • GA
  • Path planning
  • TF/TA

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