IMM fuzzy probabilistic data association algorithm for tracking maneuvering target

Authors:
Ilke Turkmen
Affiliations:
Erciyes University, Civil Aviation School, Department of Aircraft Electrical and Electronics, 38039 Kayseri, Turkey
Venue:
Expert Systems with Applications: An International Journal
Year:
2008

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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.