Volume 7 Number 12 (Dec. 2012)
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JCP 2012 Vol.7(12): 2861-2867 ISSN: 1796-203X
doi: 10.4304/jcp.7.12.2861-2867

Dual-Module Data Fusion of Infrared and Radar for Track before Detect

Anfu Zhu1, Yunfei Li2, Lingling Lv3, Hongtao Zhang3
1North China University of Water Resources and Electric Power Unversity,Zhengzhou, P.R.China
2Weinan Normal University, Weinan,P.R.China
3North China University of Water Resources and Electric Power Unversity, Zhengzhou, P.R. China


Abstract—A track before detect method based on data fusion of infrared and radar is proposed to increase the probability of correct track initiation and shorten initiation time. Track before detect is a new technique for dim target detection and tracking which is useful when the signal-tonoise ratio of target is low. Particle filter and dynamic programming for track before detect are currently proposed for detecting and tracking dim targets in low signal-to-noise ratio background. In this paper, we apply them in dual-module data fusion of infrared and radar. Particle Filter is applied to process the acquired data from radar. Dynamic programming is applied to process the acquired data from Infrared. Sensor receives data and generates the first stage decision. The decisions are subsequently transmitted to the fusion center where they are combined into a final decision on distributed fusion architectures. The proposed method is applied to simulate track before detect in dual module system of infrared and radar. The simulation results show that the proposed method increase the probability of correct track initiation and shorten initiation time.

Index Terms—Track before detect, data fusion, particle filter, dynamic programming, probability of detection.

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Cite: Anfu Zhu, Yunfei Li, Lingling Lv Hongtao Zhang, "Dual-Module Data Fusion of Infrared and Radar for Track before Detect," Journal of Computers vol. 7, no. 12, pp. 2861-2867, 2012.

General Information

ISSN: 1796-203X
Abbreviated Title: J.Comput.
Frequency: Bimonthly
Editor-in-Chief: Prof. Liansheng Tan
Executive Editor: Ms. Nina Lee
Abstracting/ Indexing: DBLP, EBSCO,  ProQuest, INSPEC, ULRICH's Periodicals Directory, WorldCat, CNKI,etc
E-mail: jcp@iap.org
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