The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. ex. Some numerals are expressed as "XNUMX".
Copyrights notice
The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. Copyrights notice
수색레이더를 이용하여 다수의 표적을 동시에 추적하는 것은 레이더 신호처리 분야의 주요 연구분야 중 하나이다. 이 문제의 가장 큰 어려움은 들어오는 데이터의 노이즈 특성에서 발생합니다. 따라서 다중 표적 추적에서는 표적과 잡음이 있는 측정 간의 정확한 연관성을 얻는 것이 중요합니다. 우리는 MAP 접근법을 기반으로 최적의 데이터 연관을 위한 새로운 방식을 도입하고 이를 통해 효율적인 에너지 함수를 도출합니다. 이전 접근 방식과 달리 목표와 측정 간의 새로운 제약 조건을 통해 목표 누락 및 잘못된 경보 사례를 관리할 수 있습니다. 현재 대부분의 알고리즘에는 매개변수의 경험적 조정이 필요합니다. 대신 본 논문에서는 자동화된 방식으로 매개변수를 결정하는 메커니즘을 제안합니다. PDA와 NNF를 포함한 실험 결과, 제안하는 방법은 NNF에 비해 교차 궤적의 위치 오차를 평균 32.8% 감소시키는 것으로 나타났다.
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부
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
부
@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},}
부
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 -