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A Multiple-Target Tracking Filter Using Data Association Based on a MAP Approach
Hong JEONG Jeong-Ho PARK
IEICE TRANSACTIONS on Fundamentals of Electronics, Communications and Computer Sciences
Publication Date: 2000/06/25
Print ISSN: 0916-8508
Type of Manuscript: PAPER
Category: Systems and Control
multiple-target tracking, data association, Kalman filter,
Full Text: PDF(578.9KB)>>
Tracking many targets simultaneously using a search radar has been one of the major research areas in radar signal processing. The primary difficulty in this problem arises from the noise characteristics of the incoming data. Hence it is crucial to obtain an accurate association between targets and noisy measurements in multi-target tracking. We introduce a new scheme for optimal data association, based on a MAP approach, and thereby derive an efficient energy function. Unlike the previous approaches, the new constraints between targets and measurements can manage the cases of target missing and false alarm. Presently, most algorithms need heuristic adjustments of the parameters. Instead, this paper suggests a mechanism that determines the parameters in an automated manner. Experimental results, including PDA and NNF, show that the proposed method reduces position errors in crossing trajectories by 32.8% on the average compared to NNF.