{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,5,14]],"date-time":"2025-05-14T03:48:58Z","timestamp":1747194538664,"version":"3.40.5"},"reference-count":35,"publisher":"SAGE Publications","issue":"6","license":[{"start":{"date-parts":[[2019,6,1]],"date-time":"2019-06-01T00:00:00Z","timestamp":1559347200000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/journals.sagepub.com\/page\/policies\/text-and-data-mining-license"}],"funder":[{"name":"Postdoctoral Research Foundation of Hei-longjiang Province","award":["LBH-Q15121"],"award-info":[{"award-number":["LBH-Q15121"]}]},{"DOI":"10.13039\/501100001809","name":"national natural science foundation of china","doi-asserted-by":"publisher","award":["61771186"],"award-info":[{"award-number":["61771186"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Distinguished Young Scholars Fund of Heilongjiang University"},{"name":"University Nursing Program for Young Scholars with Creative Talents in Heilongjiang Province","award":["UNPYSCT-2017125"],"award-info":[{"award-number":["UNPYSCT-2017125"]}]}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["International Journal of Distributed Sensor Networks"],"published-print":{"date-parts":[[2019,6]]},"abstract":"<jats:p> With the continuous expansion of the market of device-free localization in smart cities, the requirements of device-free localization technology are becoming higher and higher. The large amount of high-dimensional data generated by the existing device-free localization technology will improve the positioning accuracy as well as increase the positioning time and complexity. The positions required from single target to multi-targets become a further increasing difficulty for device-free localization. In order to satisfy the practical localizing application in smart city, an efficient multi-target device-free localization method is proposed based on a sparse coding model. To accelerate the positioning as well as improve the localization accuracy, a sparse coding-based iterative shrinkage threshold algorithm (SC-IA) is proposed and a subspace sparse coding-based iterative shrinkage threshold algorithm (SSC-IA) is presented for different practical application requirements. Experiments with practical dataset are performed for single-target and multi-targets localization, respectively. Compared with three typical machine learning algorithms: deep learning based on auto encoder, K-nearest neighbor, and orthogonal matching pursuit, experimental results show that the proposed sparse coding-based iterative shrinkage threshold algorithm and subspace sparse coding-based iterative shrinkage threshold algorithm can achieve high localization accuracy and low time cost simultaneously, so as to be more practical and applicable for the development of smart city. <\/jats:p>","DOI":"10.1177\/1550147719858229","type":"journal-article","created":{"date-parts":[[2019,6,20]],"date-time":"2019-06-20T08:29:48Z","timestamp":1561019388000},"page":"155014771985822","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":2,"title":["Multi-targets device-free localization based on sparse coding in smart city"],"prefix":"10.1177","volume":"15","author":[{"given":"Min","family":"Zhao","sequence":"first","affiliation":[{"name":"Heilongjiang University, Harbin, P.R. 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