Passive Detection of Moving Aerial Target Based on Multiple Collaborative GPS Satellites

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dc.contributor.authorLiu, Mingqianen
dc.contributor.authorGao, Zhiyangen
dc.contributor.authorChen, Yunfeien
dc.contributor.authorSong, Haoen
dc.contributor.authorLi, Yutingen
dc.contributor.authorGong, Fengkuien
dc.contributor.departmentElectrical and Computer Engineeringen
dc.date.accessioned2020-01-24T17:15:03Zen
dc.date.available2020-01-24T17:15:03Zen
dc.date.issued2020-01-12en
dc.date.updated2020-01-23T22:01:04Zen
dc.description.abstractPassive localization is an important part of intelligent surveillance in security and emergency applications. Nowadays, Global Navigation Satellite Systems (GNSSs) have been widely deployed. As a result, the satellite signal receiver may receive multiple GPS signals simultaneously, incurring echo signal detection failure. Therefore, in this paper, a passive method leveraging signals from multiple GPS satellites is proposed for moving aerial target detection. In passive detection, the first challenge is the interference caused by multiple GPS signals transmitted upon the same spectrum resources. To address this issue, successive interference cancellation (SIC) is utilized to separate and reconstruct multiple GPS signals on the reference channel. Moreover, on the monitoring channel, direct wave and multi-path interference are eliminated by extensive cancellation algorithm (ECA). After interference from multiple GPS signals is suppressed, the cycle cross ambiguity function (CCAF) of the signal on the monitoring channel is calculated and coordinate transformation method is adopted to map multiple groups of different time delay-Doppler spectrum into the distance–velocity spectrum. The detection statistics are calculated by the superposition of multiple groups of distance-velocity spectrum. Finally, the echo signal is detected based on a properly defined adaptive detection threshold. Simulation results demonstrate the effectiveness of our proposed method. They show that the detection probability of our proposed method can reach 99%, when the echo signal signal-to-noise ratio (SNR) is only −64 dB. Moreover, our proposed method can achieve 5 dB improvement over the detection method using a single GPS satellite.en
dc.description.versionPublished versionen
dc.format.mimetypeapplication/pdfen
dc.identifier.citationLiu, M.; Gao, Z.; Chen, Y.; Song, H.; Li, Y.; Gong, F. Passive Detection of Moving Aerial Target Based on Multiple Collaborative GPS Satellites. Remote Sens. 2020, 12, 263.en
dc.identifier.doihttps://doi.org/10.3390/rs12020263en
dc.identifier.urihttp://hdl.handle.net/10919/96573en
dc.language.isoenen
dc.publisherMDPIen
dc.rightsCreative Commons Attribution 4.0 Internationalen
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/en
dc.subjectcyclic cross ambiguity functionen
dc.subjectdata fusionen
dc.subjectGPSen
dc.subjectmultiple satellites collaborationen
dc.subjectpassive detectionen
dc.titlePassive Detection of Moving Aerial Target Based on Multiple Collaborative GPS Satellitesen
dc.title.serialRemote Sensingen
dc.typeArticle - Refereeden
dc.type.dcmitypeTexten

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