IMM fuzzy probabilistic data association algorithm for tracking maneuvering target

Turkmen I.

EXPERT SYSTEMS WITH APPLICATIONS, cilt.34, sa.2, ss.1243-1249, 2008 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 34 Sayı: 2
  • Basım Tarihi: 2008
  • Doi Numarası: 10.1016/j.eswa.2006.12.007
  • Dergi Adı: EXPERT SYSTEMS WITH APPLICATIONS
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Sayfa Sayıları: ss.1243-1249
  • Erciyes Üniversitesi Adresli: Evet

Özet

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.