Track correlation algorithm based on D-S theory

Chi Ping Zhang; Ping Yuan Cui; Di Yang

Track correlation algorithm based on D-S theory

Chi Ping Zhang^*
, Ping Yuan Cui
, Di Yang

^*此作品的通讯作者

Harbin Institute of Technology
Harbin Inst. of Technol.

科研成果: 期刊稿件 › 文章 › 同行评审

摘要

Based on D-S theory, the paper gives a new distributed multi-sensor track correlation algorithm (EK-NN) with a new criterion of track correlation, which improves the classical nearest neighbor (NN) and K-nearest neighbor (K-NN) methods. It is then compared with the two classical methods through simulation. The results showed that the performance of the EK-NN algorithm is better than the NN and K-NN algorithms in dense target environments.

源语言	英语
页（从-至）	689-692
页数	4
期刊	Beijing Ligong Daxue Xuebao/Transaction of Beijing Institute of Technology
卷	26
期	8
出版状态	已出版 - 8月 2006
已对外发布	是

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引用此

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title = "Track correlation algorithm based on D-S theory",

abstract = "Based on D-S theory, the paper gives a new distributed multi-sensor track correlation algorithm (EK-NN) with a new criterion of track correlation, which improves the classical nearest neighbor (NN) and K-nearest neighbor (K-NN) methods. It is then compared with the two classical methods through simulation. The results showed that the performance of the EK-NN algorithm is better than the NN and K-NN algorithms in dense target environments.",

keywords = "Evidence theory, Information fusion, Multi-target, Track correlation",

author = "Zhang, \{Chi Ping\} and Cui, \{Ping Yuan\} and Di Yang",

year = "2006",

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language = "English",

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T1 - Track correlation algorithm based on D-S theory

AU - Zhang, Chi Ping

AU - Cui, Ping Yuan

AU - Yang, Di

PY - 2006/8

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N2 - Based on D-S theory, the paper gives a new distributed multi-sensor track correlation algorithm (EK-NN) with a new criterion of track correlation, which improves the classical nearest neighbor (NN) and K-nearest neighbor (K-NN) methods. It is then compared with the two classical methods through simulation. The results showed that the performance of the EK-NN algorithm is better than the NN and K-NN algorithms in dense target environments.

AB - Based on D-S theory, the paper gives a new distributed multi-sensor track correlation algorithm (EK-NN) with a new criterion of track correlation, which improves the classical nearest neighbor (NN) and K-nearest neighbor (K-NN) methods. It is then compared with the two classical methods through simulation. The results showed that the performance of the EK-NN algorithm is better than the NN and K-NN algorithms in dense target environments.

KW - Evidence theory

KW - Information fusion

KW - Multi-target

KW - Track correlation

UR - https://www.scopus.com/pages/publications/33750477030

M3 - Article

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SN - 1001-0645

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JO - Beijing Ligong Daxue Xuebao/Transaction of Beijing Institute of Technology

JF - Beijing Ligong Daxue Xuebao/Transaction of Beijing Institute of Technology

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Track correlation algorithm based on D-S theory

摘要

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