IEICE TRANSACTIONS on Fundamentals
A Multiple-Target Tracking Filter Using Data Association Based on a MAP Approach
Summary :
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.
- Publication
- IEICE TRANSACTIONS on Fundamentals Vol.E83-A No.6 pp.1203-1210
- Publication Date
- 2000/06/25
- Publicized
- Online ISSN
- DOI
- Type of Manuscript
- PAPER
- Category
- Systems and Control
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Hong JEONG, Jeong-Ho PARK, "A Multiple-Target Tracking Filter Using Data Association Based on a MAP Approach" in IEICE TRANSACTIONS on Fundamentals,
vol. E83-A, no. 6, pp. 1203-1210, June 2000, doi: .
Abstract: 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.
URL: https://global.ieice.org/en_transactions/fundamentals/10.1587/e83-a_6_1203/_p
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@ARTICLE{e83-a_6_1203,
author={Hong JEONG, Jeong-Ho PARK, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={A Multiple-Target Tracking Filter Using Data Association Based on a MAP Approach},
year={2000},
volume={E83-A},
number={6},
pages={1203-1210},
abstract={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.},
keywords={},
doi={},
ISSN={},
month={June},}
Copy
TY - JOUR
TI - A Multiple-Target Tracking Filter Using Data Association Based on a MAP Approach
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 1203
EP - 1210
AU - Hong JEONG
AU - Jeong-Ho PARK
PY - 2000
DO -
JO - IEICE TRANSACTIONS on Fundamentals
SN -
VL - E83-A
IS - 6
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - June 2000
AB - 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.
ER -
English
