IMM fuzzy probabilistic data association algorithm for tracking maneuvering target


Turkmen I.

EXPERT SYSTEMS WITH APPLICATIONS, vol.34, no.2, pp.1243-1249, 2008 (Journal Indexed in SCI) identifier identifier

  • Publication Type: Article / Article
  • Volume: 34 Issue: 2
  • Publication Date: 2008
  • Doi Number: 10.1016/j.eswa.2006.12.007
  • Title of Journal : EXPERT SYSTEMS WITH APPLICATIONS
  • Page Numbers: pp.1243-1249

Abstract

In this paper, a new interacting multiple model fuzzy probabilistic data association (IMM-FPDA) algorithm is proposed for tracking maneuvering target. In the proposed tracker, fuzzy logic is incorporated in a conventional IMM-PDA method. In order to determine process noise covariance of the Kalman filter used in IMM-PDA, the prediction error and change of the prediction error in the last prediction are used as fuzzy inputs. To optimize parameters of the fuzzy system, a tabu search algorithm is utilized. The IMM-FPDA tracker combines advantages of the FPDA and IMM algorithms. The performance of the proposed algorithm is compared with those of the IMM and PDA-IMM algorithms using two different maneuvering tracking scenarios. It is shown from simulation results that the IMM-FPDA algorithm greatly outperforms the IMM and IMM-PDA algorithms in terms of tracking error. (C) 2006 Elsevier Ltd. All rights reserved.