Penalty Dynamic Programming Algorithm for Dim Targets Detection in Sensor Systems

被引:14
|
作者
Huang, Dayu [1 ,2 ]
Xue, Anke [1 ,2 ]
Guo, Yunfei [2 ]
机构
[1] E China Univ Sci & Technol, Sch Informat Sci & Engn, Shanghai 200237, Peoples R China
[2] Hangzhou Dianzi Univ, Inst Informat & Control, Hangzhou 310018, Peoples R China
关键词
track-before-detect; sensor systems; signal-to-noise-ratio; dynamic programming; maneuvering; multi-target tracking; feedback; PARTICLE FILTER; TRACKING; PERFORMANCE;
D O I
10.3390/s120405028
中图分类号
O65 [分析化学];
学科分类号
070302 ; 081704 ;
摘要
In order to detect and track multiple maneuvering dim targets in sensor systems, an improved dynamic programming track-before-detect algorithm (DP-TBD) called penalty DP-TBD (PDP-TBD) is proposed. The performances of tracking techniques are used as a feedback to the detection part. The feedback is constructed by a penalty term in the merit function, and the penalty term is a function of the possible target state estimation, which can be obtained by the tracking methods. With this feedback, the algorithm combines traditional tracking techniques with DP-TBD and it can be applied to simultaneously detect and track maneuvering dim targets. Meanwhile, a reasonable constraint that a sensor measurement can originate from one target or clutter is proposed to minimize track separation. Thus, the algorithm can be used in the multi-target situation with unknown target numbers. The efficiency and advantages of PDP-TBD compared with two existing methods are demonstrated by several simulations.
引用
收藏
页码:5028 / 5046
页数:19
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