{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,27]],"date-time":"2025-03-27T18:40:59Z","timestamp":1743100859621,"version":"3.37.3"},"reference-count":32,"publisher":"MDPI AG","issue":"7","license":[{"start":{"date-parts":[[2018,6,22]],"date-time":"2018-06-22T00:00:00Z","timestamp":1529625600000},"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":["61790550","61671463","91538201","61531020","61471383","61790552"],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"Networked multiple sensors are used to solve the problem of maneuvering target tracking. To avoid the linearization of nonlinear dynamic functions, and to obtain more accurate estimates for maneuvering targets, a novel adaptive information-weighted consensus filter for maneuvering target tracking is proposed. The pseudo measurement matrix is computed with unscented transform to utilize the information form of measurements, which is necessary for consensus iterations. To improve the maneuvering target tracking accuracy and get a unified estimation in each sensor node across the entire network, the adaptive current statistical model is exploited to update the estimate, and the information-weighted consensus protocol is applied among neighboring nodes for each dynamic model. Based on posterior probabilities of multiple models, the final estimate of each sensor is acquired with weighted combination of model-conditioned estimates. Experimental results illustrate the superior performance of the proposed algorithm with respect tracking accuracy and agreement of estimates in the whole network.<\/jats:p>","DOI":"10.3390\/s18072012","type":"journal-article","created":{"date-parts":[[2018,6,22]],"date-time":"2018-06-22T14:56:28Z","timestamp":1529679388000},"page":"2012","source":"Crossref","is-referenced-by-count":15,"title":["Adaptive Interacting Multiple Model Algorithm Based on Information-Weighted Consensus for Maneuvering Target Tracking"],"prefix":"10.3390","volume":"18","author":[{"given":"Ziran","family":"Ding","sequence":"first","affiliation":[{"name":"Research Institute of Information Fusion, Naval Aviation University, Yantai 264001, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5216-3181","authenticated-orcid":false,"given":"Yu","family":"Liu","sequence":"additional","affiliation":[{"name":"Research Institute of Information Fusion, Naval Aviation University, Yantai 264001, China"},{"name":"School of Electronic and Information Engineering, Beihang University, Beijing 100191, China"}]},{"given":"Jun","family":"Liu","sequence":"additional","affiliation":[{"name":"Research Institute of Information Fusion, Naval Aviation University, Yantai 264001, China"}]},{"given":"Kaimin","family":"Yu","sequence":"additional","affiliation":[{"name":"The First Training Base, Naval Aviation University, Huludao 125001, China"}]},{"given":"Yuanyang","family":"You","sequence":"additional","affiliation":[{"name":"The Second Training Base, Naval Aviation University, Changzhi 046000, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9987-6202","authenticated-orcid":false,"given":"Peiliang","family":"Jing","sequence":"additional","affiliation":[{"name":"China Ordnance Test Center, Huayin 714200, China"}]},{"given":"You","family":"He","sequence":"additional","affiliation":[{"name":"Research Institute of Information Fusion, Naval Aviation University, Yantai 264001, China"}]}],"member":"1968","published-online":{"date-parts":[[2018,6,22]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"370","DOI":"10.2514\/1.26750","article-title":"New algorithms for aircraft intent inference and trajectory prediction","volume":"30","author":"Yepes","year":"2007","journal-title":"J. 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