Dim moving target tracking algorithm based on particle discriminative sparse representation

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	Dim moving target tracking algorithm based on particle discriminative sparse representation
	Li, Zhengzhou 1,2; Li, Jianing 1; Ge, Fengzeng 1; Shao, Wanxing 1; Liu, Bing 1; Jin, Gang 2,3
刊名	INFRARED PHYSICS & TECHNOLOGY
	2016-03-01
卷号	75 页码:100-106
关键词	Dim target tracking Particle weight estimation Discriminative sparse representation Posteriori probability distribution estimation
ISSN号	1350-4495
英文摘要	The small dim moving target usually submerged in strong noise, and its motion observability is debased by numerous false alarms for low signal-to-noise ratio (SNR). A target tracking algorithm based on particle filter and discriminative sparse representation is proposed in this paper to cope with the uncertainty of dim moving target tracking. The weight of every particle is the crucial factor to ensuring the accuracy of dim target tracking for particle filter (PF) that can achieve excellent performance even under the situation of non-linear and non-Gaussian motion. In discriminative over-complete dictionary constructed according to image sequence, the target dictionary describes target signal and the background dictionary embeds background clutter. The difference between target particle and background particle is enhanced to a great extent, and the weight of every particle is then measured by means of the residual after reconstruction using the prescribed number of target atoms and their corresponding coefficients. The movement state of dim moving target is then estimated and finally tracked by these weighted particles. Meanwhile, the subspace of over-complete dictionary is updated online by the stochastic estimation algorithm. Some experiments are induced and the experimental results show the proposed algorithm could improve the performance of moving target tracking by enhancing the consistency between the posteriori probability distribution and the moving target state. (C) 2016 Elsevier B.V. All rights reserved.
WOS标题词	Science & Technology ; Technology ; Physical Sciences
类目[WOS]	Instruments & Instrumentation ; Optics ; Physics, Applied
研究领域[WOS]	Instruments & Instrumentation ; Optics ; Physics
关键词[WOS]	RECOVERY ; PERFORMANCE ; PURSUIT ; CLUTTER ; ONLINE ; FILTER
收录类别	SCI
语种	英语
WOS记录号	WOS:000371555800015
内容类型	期刊论文
源URL	[http://ir.ioe.ac.cn/handle/181551/3854]
专题	光电技术研究所_光电技术研究所被WoS收录文章
作者单位	1.Chongqing Univ, Commun Engn Coll, Chongqing 400044, Peoples R China 2.Chinese Acad Sci, Key Lab Beam Control, Chengdu 610209, Peoples R China 3.China Aerodynam Res & Dev Ctr, Mianyang 621000, Peoples R China
推荐引用方式 GB/T 7714	Li, Zhengzhou,Li, Jianing,Ge, Fengzeng,et al. Dim moving target tracking algorithm based on particle discriminative sparse representation[J]. INFRARED PHYSICS & TECHNOLOGY,2016,75:100-106.
APA	Li, Zhengzhou,Li, Jianing,Ge, Fengzeng,Shao, Wanxing,Liu, Bing,&Jin, Gang.(2016).Dim moving target tracking algorithm based on particle discriminative sparse representation.INFRARED PHYSICS & TECHNOLOGY,75,100-106.
MLA	Li, Zhengzhou,et al."Dim moving target tracking algorithm based on particle discriminative sparse representation".INFRARED PHYSICS & TECHNOLOGY 75(2016):100-106.