Tabu search tracker with adaptive neuro-fuzzy inference system for multiple target tracking

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Turkmen I. , Guney K.

PROGRESS IN ELECTROMAGNETICS RESEARCH-PIER, vol.65, pp.169-185, 2006 (Journal Indexed in SCI) identifier identifier

  • Publication Type: Article / Article
  • Volume: 65
  • Publication Date: 2006
  • Doi Number: 10.2528/pier06090601
  • Page Numbers: pp.169-185


In this paper, a tabu search tracker with adaptive neurofuzzy inference system (TST-ANFIS) is presented for multiple target tracking (MTT). First, the data association problem, formulated as an N-dimensional assignment problem, is solved using the tabu search algorithm (TSA), and then the inaccuracies in the estimation are corrected by the adaptive neuro-fuzzy inference system (ANFIS). The performances of the TST-ANFIS, the joint probabilistic data association filter (JPDAF), the tabu search tracker (TST), Lagrangian relaxation algorithm (LRA), and cheap joint probabilistic data association with adaptive neuro-fuzzy inference system state filter (CJPDA-ANFISSF) are compared with each other for six different tracking scenarios. It was shown that the tracks estimated by using proposed TST-ANFIS agree better with the true tracks than the tracks predicted by the JPDAF, the TST, the LRA, and the CJPDA-ANFISSF.