Please use this identifier to cite or link to this item: http://localhost/handle/Hannan/194482
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dc.contributor.authorJun Zhangen_US
dc.contributor.authorTian Jinen_US
dc.contributor.authorYuan Heen_US
dc.contributor.authorLei Qiuen_US
dc.contributor.authorZhimin Zhouen_US
dc.date.accessioned2013en_US
dc.date.accessioned2020-04-06T07:42:54Z-
dc.date.available2020-04-06T07:42:54Z-
dc.date.issued2017en_US
dc.identifier.other10.1049/iet-rsn.2016.0140en_US
dc.identifier.urihttp://localhost/handle/Hannan/194482-
dc.description.abstractHuman target detection and tracking have great potential in surveillance, rescue and security applications. Traditional human detection and tracking are performed on the range profile. If targets are close or overlapped in range, it is difficult to distinguish these targets. As velocity provides another aspect to distinguish targets, a novel framework is proposed for human tracking using both range and velocity information. The tracking framework consists of six steps, including clutter reduction, range-Doppler (RD) calculation, target detection, measurement estimation, target localisation and target tracking. Primary attention is devoted to the middle four steps. The calculation process of the RD image is described in detail. The ordered statistics constant false alarm rate detector is extended to a two-dimensional scenario for the RD target detection. An efficient approach is given for automatic measurement estimation. A minimum root-mean-square error pruning algorithm is proposed for multi-target localisation. As the algorithm combines both range and velocity information for measurement association, it clearly shows a lower wrong association probability than the method using range information only. The effectiveness of the proposed tracking framework is evaluated by the experimental data in the foliage-penetration environment.en_US
dc.format.extent193,en_US
dc.format.extent203en_US
dc.publisherIETen_US
dc.relation.haspart7843575.pdfen_US
dc.titleRange–Doppler-based centralised framework for human target tracking in multistatic radaren_US
dc.typeArticleen_US
dc.journal.volume11en_US
dc.journal.issue1en_US
Appears in Collections:2017

Files in This Item:
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7843575.pdf4.96 MBAdobe PDF
Full metadata record
DC FieldValueLanguage
dc.contributor.authorJun Zhangen_US
dc.contributor.authorTian Jinen_US
dc.contributor.authorYuan Heen_US
dc.contributor.authorLei Qiuen_US
dc.contributor.authorZhimin Zhouen_US
dc.date.accessioned2013en_US
dc.date.accessioned2020-04-06T07:42:54Z-
dc.date.available2020-04-06T07:42:54Z-
dc.date.issued2017en_US
dc.identifier.other10.1049/iet-rsn.2016.0140en_US
dc.identifier.urihttp://localhost/handle/Hannan/194482-
dc.description.abstractHuman target detection and tracking have great potential in surveillance, rescue and security applications. Traditional human detection and tracking are performed on the range profile. If targets are close or overlapped in range, it is difficult to distinguish these targets. As velocity provides another aspect to distinguish targets, a novel framework is proposed for human tracking using both range and velocity information. The tracking framework consists of six steps, including clutter reduction, range-Doppler (RD) calculation, target detection, measurement estimation, target localisation and target tracking. Primary attention is devoted to the middle four steps. The calculation process of the RD image is described in detail. The ordered statistics constant false alarm rate detector is extended to a two-dimensional scenario for the RD target detection. An efficient approach is given for automatic measurement estimation. A minimum root-mean-square error pruning algorithm is proposed for multi-target localisation. As the algorithm combines both range and velocity information for measurement association, it clearly shows a lower wrong association probability than the method using range information only. The effectiveness of the proposed tracking framework is evaluated by the experimental data in the foliage-penetration environment.en_US
dc.format.extent193,en_US
dc.format.extent203en_US
dc.publisherIETen_US
dc.relation.haspart7843575.pdfen_US
dc.titleRange–Doppler-based centralised framework for human target tracking in multistatic radaren_US
dc.typeArticleen_US
dc.journal.volume11en_US
dc.journal.issue1en_US
Appears in Collections:2017

Files in This Item:
File SizeFormat 
7843575.pdf4.96 MBAdobe PDF
Full metadata record
DC FieldValueLanguage
dc.contributor.authorJun Zhangen_US
dc.contributor.authorTian Jinen_US
dc.contributor.authorYuan Heen_US
dc.contributor.authorLei Qiuen_US
dc.contributor.authorZhimin Zhouen_US
dc.date.accessioned2013en_US
dc.date.accessioned2020-04-06T07:42:54Z-
dc.date.available2020-04-06T07:42:54Z-
dc.date.issued2017en_US
dc.identifier.other10.1049/iet-rsn.2016.0140en_US
dc.identifier.urihttp://localhost/handle/Hannan/194482-
dc.description.abstractHuman target detection and tracking have great potential in surveillance, rescue and security applications. Traditional human detection and tracking are performed on the range profile. If targets are close or overlapped in range, it is difficult to distinguish these targets. As velocity provides another aspect to distinguish targets, a novel framework is proposed for human tracking using both range and velocity information. The tracking framework consists of six steps, including clutter reduction, range-Doppler (RD) calculation, target detection, measurement estimation, target localisation and target tracking. Primary attention is devoted to the middle four steps. The calculation process of the RD image is described in detail. The ordered statistics constant false alarm rate detector is extended to a two-dimensional scenario for the RD target detection. An efficient approach is given for automatic measurement estimation. A minimum root-mean-square error pruning algorithm is proposed for multi-target localisation. As the algorithm combines both range and velocity information for measurement association, it clearly shows a lower wrong association probability than the method using range information only. The effectiveness of the proposed tracking framework is evaluated by the experimental data in the foliage-penetration environment.en_US
dc.format.extent193,en_US
dc.format.extent203en_US
dc.publisherIETen_US
dc.relation.haspart7843575.pdfen_US
dc.titleRange–Doppler-based centralised framework for human target tracking in multistatic radaren_US
dc.typeArticleen_US
dc.journal.volume11en_US
dc.journal.issue1en_US
Appears in Collections:2017

Files in This Item:
File SizeFormat 
7843575.pdf4.96 MBAdobe PDF