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

Creative Commons License

Turkmen I., Guney K.

PROGRESS IN ELECTROMAGNETICS RESEARCH-PIER, cilt.65, ss.169-185, 2006 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 65
  • Basım Tarihi: 2006
  • Doi Numarası: 10.2528/pier06090601
  • Dergi Adı: PROGRESS IN ELECTROMAGNETICS RESEARCH-PIER
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Sayfa Sayıları: ss.169-185
  • Erciyes Üniversitesi Adresli: Evet

Özet

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.