{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,16]],"date-time":"2026-01-16T01:14:24Z","timestamp":1768526064266,"version":"3.49.0"},"reference-count":23,"publisher":"MDPI AG","issue":"1","license":[{"start":{"date-parts":[[2018,12,22]],"date-time":"2018-12-22T00:00:00Z","timestamp":1545436800000},"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":["61473039"],"award-info":[{"award-number":["61473039"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>As a structural interference, spoofing is difficult to detect by the target receiver while the advent of a repeater makes the implementation of spoofing much easier. Most existing anti-spoofing methods are merely capable of detecting the spoofing, i.e., they cannot effectively remove counterfeit signals. Therefore, based on the similarities between multipath and spoofing, the feasibility of applying multipath mitigation methods to anti-spoofing is first analyzed in this paper. We then propose a novel algorithm based on maximum likelihood (ML) estimation to resolve this problem. The tracking channels with multi-correlators are constructed and a set of corresponding steps of detecting and removing the counterfeit signals is designed to ensure that the receiver locks the authentic signals in the presence of spoofing. Finally, the spoofing is successfully executed with a software receiver and the saved intermediate frequency (IF) signals, on this basis, the effectiveness of the proposed algorithm is verified by experiments.<\/jats:p>","DOI":"10.3390\/s19010037","type":"journal-article","created":{"date-parts":[[2018,12,24]],"date-time":"2018-12-24T10:37:49Z","timestamp":1545647869000},"page":"37","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":20,"title":["Spoofing Detection and Mitigation in a Multi-correlator GPS Receiver Based on the Maximum Likelihood Principle"],"prefix":"10.3390","volume":"19","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-0178-8472","authenticated-orcid":false,"given":"Yanbing","family":"Guo","sequence":"first","affiliation":[{"name":"School of Automation, Beijing Institute of Technology (BIT), Beijing 100081, China"}]},{"given":"Lingjuan","family":"Miao","sequence":"additional","affiliation":[{"name":"School of Automation, Beijing Institute of Technology (BIT), Beijing 100081, China"}]},{"given":"Xi","family":"Zhang","sequence":"additional","affiliation":[{"name":"School of Automation, Beijing Institute of Technology (BIT), Beijing 100081, China"}]}],"member":"1968","published-online":{"date-parts":[[2018,12,22]]},"reference":[{"key":"ref_1","unstructured":"Humphreys, T.E., Ledvina, B.M., Psiaki, M.L., O\u2019Hanlon, B.W., and Kintner, P.M. 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