{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,12]],"date-time":"2025-10-12T03:33:20Z","timestamp":1760240000410,"version":"build-2065373602"},"reference-count":36,"publisher":"MDPI AG","issue":"2","license":[{"start":{"date-parts":[[2019,1,17]],"date-time":"2019-01-17T00:00:00Z","timestamp":1547683200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61703128;61871166;61703129"],"award-info":[{"award-number":["61703128;61871166;61703129"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Science and Technology on Near-Surface Detection Laboratory Foundation","award":["614241404030717"],"award-info":[{"award-number":["614241404030717"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>In this paper, we study the multi-sensor multi-target tracking problem in the formulation of random finite sets. The Gaussian Mixture probability hypothesis density (GM-PHD) method is employed to formulate the sequential fusing multi-sensor GM-PHD (SFMGM-PHD) algorithm. First, the GM-PHD is applied to multiple sensors to get the posterior GM estimations in a parallel way. Second, we propose the SFMGM-PHD algorithm to fuse the multi-sensor GM estimations in a sequential way. Third, the unbalanced weighted fusing and adaptive sequence ordering methods are further proposed for two improved SFMGM-PHD algorithms. At last, we analyze the proposed algorithms in four different multi-sensor multi-target tracking scenes, and the results demonstrate the efficiency.<\/jats:p>","DOI":"10.3390\/s19020366","type":"journal-article","created":{"date-parts":[[2019,1,17]],"date-time":"2019-01-17T11:30:27Z","timestamp":1547724627000},"page":"366","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["An Unbalanced Weighted Sequential Fusing Multi-Sensor GM-PHD Algorithm"],"prefix":"10.3390","volume":"19","author":[{"given":"Han","family":"Shen-Tu","sequence":"first","affiliation":[{"name":"Institution of Information and Control, Hangzhou Dianzi University, Hangzhou 310018, China"},{"name":"Science and Technology on Near-surface Detection Laboratory, Wuxi 214035, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7012-5384","authenticated-orcid":false,"given":"Hanming","family":"Qian","sequence":"additional","affiliation":[{"name":"Science and Technology on Near-surface Detection Laboratory, Wuxi 214035, China"}]},{"given":"Dongliang","family":"Peng","sequence":"additional","affiliation":[{"name":"Institution of Information and Control, Hangzhou Dianzi University, Hangzhou 310018, China"}]},{"given":"Yunfei","family":"Guo","sequence":"additional","affiliation":[{"name":"Institution of Information and Control, Hangzhou Dianzi University, Hangzhou 310018, China"}]},{"given":"Ji-An","family":"Luo","sequence":"additional","affiliation":[{"name":"Institution of Information and Control, Hangzhou Dianzi University, Hangzhou 310018, China"}]}],"member":"1968","published-online":{"date-parts":[[2019,1,17]]},"reference":[{"key":"ref_1","unstructured":"Bar-Shalom, Y., and Fortmann, T.E. 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