An improved estimator using multiple sensor data fusion for radar maneuvering target tracking systems

Yi Nung Chung, Hsin Ta Chen, Pao Hua Chou, Maw Rong Yang

Research output: Contribution to journalArticle

Abstract

An algorithm for tracking multiple maneuvering targets using multiple sensor data fusion is developed in this paper. In order to solve a complicated situation due to the multiple maneuvering tracking environment, a tracking filter and a multiple-sensor data-fusion algorithm are applied in this study. In addition, in order to solve the data association and target maneuvering situations, a computational logic, including 1-step conditional maximum likelihood and a variable structure model as an adaptive maneuvering compensator, is applied to solve both data association and target maneuvering problems simultaneously. The advantage of this approach is that the sensors can be installed in either fixed or moving systems, thereby improving the tracking accuracy and the reliability of the radar surveillance. In order to verify this approach, simulations of multi-target tracking problems are conducted. Computer simulation results indicate that this approach successfully tracks multiple targets and has good performance.

Original languageEnglish
Pages (from-to)203-210
Number of pages8
JournalJournal of the Chinese Institute of Engineers, Transactions of the Chinese Institute of Engineers,Series A/Chung-kuo Kung Ch'eng Hsuch K'an
Volume30
Issue number2
DOIs
Publication statusPublished - 2007 Jan 1

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Sensor data fusion
Target tracking
Radar
Surveillance radar
Model structures
Maximum likelihood
Sensors
Computer simulation

All Science Journal Classification (ASJC) codes

  • Engineering(all)

Cite this

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abstract = "An algorithm for tracking multiple maneuvering targets using multiple sensor data fusion is developed in this paper. In order to solve a complicated situation due to the multiple maneuvering tracking environment, a tracking filter and a multiple-sensor data-fusion algorithm are applied in this study. In addition, in order to solve the data association and target maneuvering situations, a computational logic, including 1-step conditional maximum likelihood and a variable structure model as an adaptive maneuvering compensator, is applied to solve both data association and target maneuvering problems simultaneously. The advantage of this approach is that the sensors can be installed in either fixed or moving systems, thereby improving the tracking accuracy and the reliability of the radar surveillance. In order to verify this approach, simulations of multi-target tracking problems are conducted. Computer simulation results indicate that this approach successfully tracks multiple targets and has good performance.",
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AB - An algorithm for tracking multiple maneuvering targets using multiple sensor data fusion is developed in this paper. In order to solve a complicated situation due to the multiple maneuvering tracking environment, a tracking filter and a multiple-sensor data-fusion algorithm are applied in this study. In addition, in order to solve the data association and target maneuvering situations, a computational logic, including 1-step conditional maximum likelihood and a variable structure model as an adaptive maneuvering compensator, is applied to solve both data association and target maneuvering problems simultaneously. The advantage of this approach is that the sensors can be installed in either fixed or moving systems, thereby improving the tracking accuracy and the reliability of the radar surveillance. In order to verify this approach, simulations of multi-target tracking problems are conducted. Computer simulation results indicate that this approach successfully tracks multiple targets and has good performance.

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