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2006-10-22

Tabu Search Tracker with Adaptive Neuro-Fuzzy Inference System for Multiple Target Tracking

By Ilke Turkmen and Kerim Guney
Progress In Electromagnetics Research, Vol. 65, 169-185, 2006
doi:10.2528/PIER06090601

Abstract

In this paper, a tabusearc h 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 tabusearc h 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 CJPDAANFISSF.

Citation

 (See works that cites this article)
Ilke Turkmen and Kerim Guney, "Tabu Search Tracker with Adaptive Neuro-Fuzzy Inference System for Multiple Target Tracking," Progress In Electromagnetics Research, Vol. 65, 169-185, 2006.
doi:10.2528/PIER06090601
http://jpier.org/PIER/pier.php?paper=06090601

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