Cheap joint probabilistic data association with adaptive neuro-fuzzy inference system state filter for tracking multiple targets in cluttered environment


Turkmen I. , Guney K.

AEU-INTERNATIONAL JOURNAL OF ELECTRONICS AND COMMUNICATIONS, vol.58, no.5, pp.349-357, 2004 (Journal Indexed in SCI) identifier identifier

  • Publication Type: Article / Article
  • Volume: 58 Issue: 5
  • Publication Date: 2004
  • Doi Number: 10.1078/1434-8411-54100254
  • Title of Journal : AEU-INTERNATIONAL JOURNAL OF ELECTRONICS AND COMMUNICATIONS
  • Page Numbers: pp.349-357

Abstract

The cheap joint probabilistic data association (CJPDA) with the adaptive neuro-fuzzy inference system state filter (ANFISSF) is presented for tracking multiple targets in the presence of low and high cluttered environments. The state update step of the CJPDA filter (CJPDAF) is realized with the ANFISSF instead of Kalman filter. The adaptive neuro-fuzzy inference system (ANFIS) has the advantages of expert knowledge of fuzzy inference system and learning capability of neural networks. A hybrid learning algorithm, which combines the least square method and the backpropagation algorithm, is used to identify the parameters of ANFIS. The tracks estimated by using the method proposed in this paper for different tracking scenarios are in very good agreement with the original tracks.