{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,7]],"date-time":"2026-01-07T07:52:16Z","timestamp":1767772336789,"version":"build-2065373602"},"reference-count":29,"publisher":"MDPI AG","issue":"4","license":[{"start":{"date-parts":[[2012,4,18]],"date-time":"2012-04-18T00:00:00Z","timestamp":1334707200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/3.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>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.<\/jats:p>","DOI":"10.3390\/s120405028","type":"journal-article","created":{"date-parts":[[2012,4,18]],"date-time":"2012-04-18T11:04:18Z","timestamp":1334747058000},"page":"5028-5046","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":14,"title":["Penalty Dynamic Programming Algorithm for Dim Targets Detection in Sensor Systems"],"prefix":"10.3390","volume":"12","author":[{"given":"Dayu","family":"Huang","sequence":"first","affiliation":[{"name":"School of Information Science & Engineering, East China University of Science & Technology, Shanghai 200237, China"},{"name":"Institute of Information and Control, Hangzhou Dianzi University, Hangzhou 310018, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Anke","family":"Xue","sequence":"additional","affiliation":[{"name":"School of Information Science & Engineering, East China University of Science & Technology, Shanghai 200237, China"},{"name":"Institute of Information and Control, Hangzhou Dianzi University, Hangzhou 310018, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yunfei","family":"Guo","sequence":"additional","affiliation":[{"name":"Institute of Information and Control, Hangzhou Dianzi University, Hangzhou 310018, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2012,4,18]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"144","DOI":"10.3390\/s7010144","article-title":"An improved particle filter for target tracking in sensor systems","volume":"7","author":"Wang","year":"2007","journal-title":"Sensors"},{"key":"ref_2","first-page":"1","article-title":"A comparison of detection performance for several track-before-detect algorithms","volume":"2008","author":"Davey","year":"2008","journal-title":"EURASIP J. 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