Radiation intensity Gaussian mixture PHD filter for close target tracking

doi:10.1016/j.sigpro.2021.108196

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	Radiation intensity Gaussian mixture PHD filter for close target tracking
	M. Ma; D. Wang; H. Sun and T. Zhang
	2021
发表期刊	Signal Processing
ISSN	1651684
卷号	188
摘要	The Gaussian mixture probability hypothesis density (GM-PHD) filter has recently been devised as a suboptimal Bayesian solution for multiple target tracking. However, the performance of standard GM-PHD degrades seriously in close targets tracking. Although the renormalization scheme is proposed to improve the estimation results, the identification problem of measurements generated by different targets and clutter is still unresolved. To this end, this paper develops a radiation intensity PHD filter (RIGM-PHD). First, the Gaussian distribution with signal-to-noise (SNR) information is proposed to model the radiation intensity and describe the relationship between the target radiation intensity and clutter level. Then, in order to circumvent the issue that the real target SNR can't be obtained precisely, we construct a likelihood function of radiation intensity for unknown target SNR and derive new PHD recursion equations. Second, a labeling update scheme is also provided to prevent the incorrect propagation of identities of close targets. Finally, comprehensive Monte Carlo simulations in terms of various detection probabilities and clutter rates for parallel and crossing targets are performed to investigate the effectiveness of the proposed filter. 2021
DOI	10.1016/j.sigpro.2021.108196
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收录类别	SCI ; EI
引用统计
文献类型	期刊论文
条目标识符	http://ir.ciomp.ac.cn/handle/181722/65568
专题	中国科学院长春光学精密机械与物理研究所
推荐引用方式 GB/T 7714	M. Ma,D. Wang,H. Sun and T. Zhang. Radiation intensity Gaussian mixture PHD filter for close target tracking[J]. Signal Processing,2021,188.
APA	M. Ma,D. Wang,&H. Sun and T. Zhang.(2021).Radiation intensity Gaussian mixture PHD filter for close target tracking.Signal Processing,188.
MLA	M. Ma,et al."Radiation intensity Gaussian mixture PHD filter for close target tracking".Signal Processing 188(2021).

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