A Novel Method for Tracking and Recognizing Infrared Dim and Small Moving Target Based on Modified Probabilistic Data Associating Filter

Li Zheng-zhou; Jin Gang; Dong Neng-li

doi:10.3724/SP.J.1146.2006.01597

Volume 30 Issue 4

Dec. 2010

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Li Zheng-zhou, Jin Gang, Dong Neng-li. A Novel Method for Tracking and Recognizing Infrared Dim and Small Moving Target Based on Modified Probabilistic Data Associating Filter[J]. Journal of Electronics & Information Technology, 2008, 30(4): 953-956. doi: 10.3724/SP.J.1146.2006.01597

Citation:

Li Zheng-zhou, Jin Gang, Dong Neng-li. A Novel Method for Tracking and Recognizing Infrared Dim and Small Moving Target Based on Modified Probabilistic Data Associating Filter[J]. Journal of Electronics & Information Technology, 2008, 30(4): 953-956. doi: 10.3724/SP.J.1146.2006.01597

Citation:

Li Zheng-zhou, Jin Gang, Dong Neng-li. A Novel Method for Tracking and Recognizing Infrared Dim and Small Moving Target Based on Modified Probabilistic Data Associating Filter[J]. Journal of Electronics & Information Technology, 2008, 30(4): 953-956. doi: 10.3724/SP.J.1146.2006.01597

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A Novel Method for Tracking and Recognizing Infrared Dim and Small Moving Target Based on Modified Probabilistic Data Associating Filter

doi: 10.3724/SP.J.1146.2006.01597

Li Zheng-zhou^{①②;金钢},
Jin Gang,
Dong Neng-li

Received Date: 2006-10-19
Rev Recd Date: 2007-04-09
Publish Date: 2008-04-19

Abstract

Abstract

During tracking dim and small moving targets in the electrooptical detecting system, many false alarms extracted in the tracking window for low signal-to-noise ratio and high false alarm ratio debase seriously the performance of target recognition and tracking. To solve this problem, the target characters of the infrared imaging tracking system are analyzed, and based on the idea of the probabilistic data association filter, a modified method, which integrates the continuity and consistency of targets amplitude and motion, is proposed. The emphases are laid on the comparison of the target recognition and tracking performances between the original maximum likehood-probabilistic data associated filter and the proposed method. Some experimental results are included and the performance of target recognition and tracking target is improved greatly.

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References

牛秩峰, 沈林成. 基于变形模板的多目标识别与定位[J].电子与信息学报.2006, 28(6):1026-1030浏览[2]程建, 杨杰. 一种基于均值偏移的红外目标跟踪新方法[J]. 红外与毫米波学报, 2005, 24(3): 231-235.Cheng Jian and Yang Jie. Novel infrared object trackingmethod based on mean shift [J]. Journal of InfraredMillimeter Waves, 2005, 24(3): 231-235.[3]张坤华, 王敬儒, 张起衡. 基于边界不变矩的扩展目标识别方法[J]. 光电工程, 2005, 32(8): 1-5.Zhang Kun-hua, Wang Jin-ru, and Zhang Qi-heng. Methodfor recognizing extended target based on boundary invariants[J]. Opto-Electronic Engineering, 2005, 32(8): 1-5.[4]强勇, 焦李成, 保铮. 动态规划算法进行弱目标检测的机理研究[J].电子与信息学报.2003, 25(6):721-727浏览[5]Succcary R and Cohen A, et al.. A dynamic programmingalgorithm for point target detection: practical parameters forDPA [J]. Signal and Data Processing of Small Targets 2001,Proceeding of SPIE Vol.4473: 96-100.[6]Kirubarajan T and Bar-Shalom Y. Low observable targetmotion analysis using amplitude information [J].IEEE Trans.on Aerospace and Electron System.1996, 32(4):1367-1384[7]Chummun M R, Kirubarajan T, and Bar-Shalom Y. Anadaptive early-detection ML/PDA estimator for LO targetswith EO sensors [C]. 2000 IEEE on Aerospace ConferenceProceedings, 18-25 March 2000, Vol.3: 449-464.[8]Kirubarajan T and Bar-Shalom Y. Probabilistic dataassociation techniques for target tracking in clutter [J].Proc.IEEE.2004, 92(3):536-557[9]周宏仁, 敬忠良, 王培德. 机动目标跟踪[M]. 北京: 国防工业出版社, 1991: 221-224, 268-270.Zhou Hong-ren, Jing Zhong-liang, and Wang Pei-de. Trackingof maneuvering targets[M]. Beijing: National DefenceIndustry Press, 1991: 221-224, 268-270.

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