Genetic tracker with neural network for single and multiple target tracking


Turkmen I., Guney K., Karaboga D.

NEUROCOMPUTING, vol.69, pp.2309-2319, 2006 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 69
  • Publication Date: 2006
  • Doi Number: 10.1016/j.neucom.2005.04.014
  • Journal Name: NEUROCOMPUTING
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Page Numbers: pp.2309-2319
  • Erciyes University Affiliated: Yes

Abstract

In this paper, a genetic tracker (GT) with neural network (NN) (GT-NN) is presented for single and multiple target tracking. The data association problem formulated as an N-dimensional assignment problem is solved using genetic algorithm. The incorporation of a NN into the GT is then proposed to increase its tracking performance. Performance evaluations of the GT, the GT-NN, the probabilistic data association filter, and the joint probabilistic data association filter are presented using simulation studies. Nine different tracking scenarios are considered for this evaluation. It has been observed that the estimation results of the GT-NN are better than those of the GT, the probabilistic data association filter, and the joint probabilistic data association filter. (c) 2005 Elsevier B.V. All rights reserved.