Data association for infrared search and track system

  • Chen Li
  • , Chongzhao Han
  • , Hongyan Zhu

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

3 Scopus citations

Abstract

Data association is one of the key techniques on bearing-only tracking with Infrared Search and Track (IRST) system. A new data association algorithm based on information fusion is proposed in this paper. Firstly, by considering the special feature ofIRST system, the new method constructs several kinds of evidences that are based on the multi-type information, such as angular measurement, intensity level and so on. And then all results from different aspects are fused by utilizing Dempster combination rule. Finally, the association decision is obtained by maximizing the final mass function. The simulation results show that the proposed approach has better performance than the traditional ones. As observation conditions deteriorate, the advantage of new method becomes obvious. For uncertain data, this new data association algorithm based on evidence theory is excellent by utilizing reasonably the measurements.

Original languageEnglish
Title of host publication2006 9th International Conference on Information Fusion, FUSION
DOIs
StatePublished - 2006
Event2006 9th International Conference on Information Fusion, FUSION - Florence, Italy
Duration: 10 Jul 200613 Jul 2006

Publication series

Name2006 9th International Conference on Information Fusion, FUSION

Conference

Conference2006 9th International Conference on Information Fusion, FUSION
Country/TerritoryItaly
CityFlorence
Period10/07/0613/07/06

Keywords

  • Data association
  • Evidence theory
  • IRST
  • Information fusion

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