{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,6]],"date-time":"2026-04-06T11:53:50Z","timestamp":1775476430337,"version":"3.50.1"},"reference-count":39,"publisher":"MDPI AG","issue":"7","license":[{"start":{"date-parts":[[2021,4,5]],"date-time":"2021-04-05T00:00:00Z","timestamp":1617580800000},"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":["61901233"],"award-info":[{"award-number":["61901233"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100006606","name":"Natural Science Foundation of Tianjin City","doi-asserted-by":"publisher","award":["19JCQNJC00900"],"award-info":[{"award-number":["19JCQNJC00900"]}],"id":[{"id":"10.13039\/501100006606","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>The direct-sequence spread-spectrum (DSSS) technique has been widely used in wireless secure communications. In this technique, the baseband signal is spread over a wider bandwidth using pseudo-random sequences to avoid interference or interception. In this paper, the authors propose methods to adaptively detect the DSSS signals based on knowledge-enhanced compressive measurements and artificial neural networks. Compared with the conventional non-compressive detection system, the compressive detection framework can achieve a reasonable balance between detection performance and sampling hardware cost. In contrast to the existing compressive sampling techniques, the proposed methods are shown to enable adaptive measurement kernel design with high efficiency. Through the theoretical analysis and the simulation results, the proposed adaptive compressive detection methods are also demonstrated to provide significantly enhanced detection performance efficiently, compared to their counterpart with the conventional random measurement kernels.<\/jats:p>","DOI":"10.3390\/s21072538","type":"journal-article","created":{"date-parts":[[2021,4,5]],"date-time":"2021-04-05T11:48:29Z","timestamp":1617623309000},"page":"2538","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["Adaptive Detection of Direct-Sequence Spread-Spectrum Signals Based on Knowledge-Enhanced Compressive Measurements and Artificial Neural Networks"],"prefix":"10.3390","volume":"21","author":[{"given":"Shuang","family":"Zhang","sequence":"first","affiliation":[{"name":"College of Electronic Information and Optical Engineering, Nankai University, Tianjin 300350, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3110-8498","authenticated-orcid":false,"given":"Feng","family":"Liu","sequence":"additional","affiliation":[{"name":"College of Electronic Information and Optical Engineering, Nankai University, Tianjin 300350, China"},{"name":"Tianjin Key Laboratory of Optoelectronic Sensor and Sensing Network Technology, Nankai University, Tianjin 300350, China"}]},{"given":"Yuang","family":"Huang","sequence":"additional","affiliation":[{"name":"College of Electronic Information and Optical Engineering, Nankai University, Tianjin 300350, China"}]},{"given":"Xuedong","family":"Meng","sequence":"additional","affiliation":[{"name":"College of Electronic Information and Optical Engineering, Nankai University, Tianjin 300350, China"}]}],"member":"1968","published-online":{"date-parts":[[2021,4,5]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"8","DOI":"10.1109\/MCOM.1983.1091346","article-title":"An introduction to spread spectrum","volume":"21","author":"Cook","year":"1983","journal-title":"IEEE Commun. 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