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Penalty Dynamic Programming Algorithm for Dim Targets Detection in Sensor Systems
School of Information Science & Engineering, East China University of Science & Technology, Shanghai 200237, China
Institute of Information and Control, Hangzhou Dianzi University, Hangzhou 310018, China
* Author to whom correspondence should be addressed.
Received: 12 March 2012; in revised form: 20 March 2012 / Accepted: 10 April 2012 / Published: 18 April 2012
Abstract: 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.
Keywords: track-before-detect; sensor systems; signal-to-noise-ratio; dynamic programming; maneuvering; multi-target tracking; feedback
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MDPI and ACS Style
Huang, D.; Xue, A.; Guo, Y. Penalty Dynamic Programming Algorithm for Dim Targets Detection in Sensor Systems. Sensors 2012, 12, 5028-5046.
Huang D, Xue A, Guo Y. Penalty Dynamic Programming Algorithm for Dim Targets Detection in Sensor Systems. Sensors. 2012; 12(4):5028-5046.
Huang, Dayu; Xue, Anke; Guo, Yunfei. 2012. "Penalty Dynamic Programming Algorithm for Dim Targets Detection in Sensor Systems." Sensors 12, no. 4: 5028-5046.