{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,5,14]],"date-time":"2025-05-14T02:45:31Z","timestamp":1747190731569,"version":"3.40.5"},"reference-count":15,"publisher":"Wiley","license":[{"start":{"date-parts":[[2022,2,16]],"date-time":"2022-02-16T00:00:00Z","timestamp":1644969600000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Soft Science Research Program of Henan Province","award":["202400410097","192102210254","20B510001","19A413006","21A413002","61976080","61771006"],"award-info":[{"award-number":["202400410097","192102210254","20B510001","19A413006","21A413002","61976080","61771006"]}]},{"name":"Programs for Science and Technology Development of Henan Province","award":["202400410097","192102210254","20B510001","19A413006","21A413002","61976080","61771006"],"award-info":[{"award-number":["202400410097","192102210254","20B510001","19A413006","21A413002","61976080","61771006"]}]},{"name":"Key Research Projects of University in Henan Province","award":["202400410097","192102210254","20B510001","19A413006","21A413002","61976080","61771006"],"award-info":[{"award-number":["202400410097","192102210254","20B510001","19A413006","21A413002","61976080","61771006"]}]},{"name":"National Science Foundation Council of China","award":["202400410097","192102210254","20B510001","19A413006","21A413002","61976080","61771006"],"award-info":[{"award-number":["202400410097","192102210254","20B510001","19A413006","21A413002","61976080","61771006"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Journal of Sensors"],"published-print":{"date-parts":[[2022,2,16]]},"abstract":"<jats:p>In multisensor cooperative detection network, some random disturbances, energy carried by sensor, distance between target and sensor node, and so on all affect the sensor selection scheme. To effectively select some sensors for detecting the target, a novel sensor selection method considering uncertainty disturbance is proposed under constraints of estimation accuracy and energy consumption. Firstly, the sensor selection problem is modeled as a binary form optimization problem with a penalty term to minimize the number of sensors. Secondly, some factors (precision, energy, and distance, etc.) affecting the sensor selection scheme are analyzed and quantified, and energy consumption matrix and estimation precision threshold are given by matrix tra\u2018nsformation. Finally, the problem of minimizing sensor number after relaxation is solved by convex optimization method, obtaining sensor selection scheme by discretization and legitimization of the suboptimal solution after convex relaxation. Simulation results show that the proposed algorithm can ensure the minimum number of sensors, improving accuracy of state estimation and saving network energy.<\/jats:p>","DOI":"10.1155\/2022\/2488907","type":"journal-article","created":{"date-parts":[[2022,2,17]],"date-time":"2022-02-17T00:05:38Z","timestamp":1645056338000},"page":"1-11","source":"Crossref","is-referenced-by-count":2,"title":["Sensor Selection Scheme considering Uncertainty Disturbance"],"prefix":"10.1155","volume":"2022","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-0847-9701","authenticated-orcid":true,"given":"Shi","family":"Wentao","sequence":"first","affiliation":[{"name":"School of Marine Science and Technology, Northwestern Polytechnical University, Xi\u2019an 710072, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Chen","family":"Dong","sequence":"additional","affiliation":[{"name":"School of Marine Science and Technology, Northwestern Polytechnical University, Xi\u2019an 710072, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2700-834X","authenticated-orcid":true,"given":"Zhou","family":"Lin","sequence":"additional","affiliation":[{"name":"School of Artificial Intelligence, Henan University, Zhengzhou 450046, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Bai","family":"Ke","sequence":"additional","affiliation":[{"name":"School of Artificial Intelligence, Henan University, Zhengzhou 450046, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9325-5966","authenticated-orcid":true,"given":"Jin","family":"Yong","sequence":"additional","affiliation":[{"name":"School of Artificial Intelligence, Henan University, Zhengzhou 450046, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"311","reference":[{"key":"1","doi-asserted-by":"publisher","DOI":"10.1109\/TWC.2016.2518689"},{"key":"2","doi-asserted-by":"publisher","DOI":"10.1016\/j.sigpro.2016.05.011"},{"key":"3","doi-asserted-by":"publisher","DOI":"10.1109\/LCOMM.2021.3067898"},{"key":"4","doi-asserted-by":"publisher","DOI":"10.1109\/LCSYS.2020.3047729"},{"key":"5","doi-asserted-by":"publisher","DOI":"10.1109\/LSP.2013.2297419"},{"key":"6","doi-asserted-by":"publisher","DOI":"10.1109\/TSP.2014.2299518"},{"key":"7","doi-asserted-by":"publisher","DOI":"10.1109\/TSP.2016.2573767"},{"key":"8","doi-asserted-by":"publisher","DOI":"10.1109\/TSP.2019.2903017"},{"key":"9","doi-asserted-by":"publisher","DOI":"10.1109\/TCOMM.2004.826349"},{"key":"10","doi-asserted-by":"publisher","DOI":"10.1109\/TSP.2008.2007095"},{"key":"11","doi-asserted-by":"publisher","DOI":"10.1109\/TSP.2017.2773429"},{"issue":"4","key":"12","first-page":"465","article-title":"Fundamentals of statistical signal processing: estimation theory","volume":"37","author":"S. 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