Filip, Alexandra und Shutin, Dmitriy und O'Hagan, Daniel (2017) Sparse Bayesian Learning for Long Coherent Integration Time in Passive Radar Systems. IET International Conference on Radar Systems, 2017-10-23 - 2017-10-26, Belfast, UK. doi: 10.1049/cp.2017.0421.
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Kurzfassung
Maximising the radar coherent integration time is crucial when performing detection and parameter estimation on weak target echoes. The integration time is limited however by the migration of a target of interest out of a range and Doppler cell. To account for the range migration it is proposed to build here upon a Keystone transform and develop a joint sparse super-resolution target parameter estimation and target detection method using a super-resolution sparse Bayesian learning framework. The estimation scheme uses a variational version of the space-alternating generalized expectation maximization (VB-SAGE) algorithm, which permits reducing the numerical complexity of the scheme. Moreover, since the search space is not discretized, the parameter estimates are not restricted by the system resolution. Our simulation experiments demonstrate the effectiveness of the algorithm.
elib-URL des Eintrags: | https://elib.dlr.de/112862/ | ||||||||||||||||
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Dokumentart: | Konferenzbeitrag (Vortrag) | ||||||||||||||||
Titel: | Sparse Bayesian Learning for Long Coherent Integration Time in Passive Radar Systems | ||||||||||||||||
Autoren: |
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Datum: | 2017 | ||||||||||||||||
Referierte Publikation: | Ja | ||||||||||||||||
Open Access: | Nein | ||||||||||||||||
Gold Open Access: | Nein | ||||||||||||||||
In SCOPUS: | Nein | ||||||||||||||||
In ISI Web of Science: | Nein | ||||||||||||||||
DOI: | 10.1049/cp.2017.0421 | ||||||||||||||||
Status: | veröffentlicht | ||||||||||||||||
Stichwörter: | passive radar, coherent integration time, range migration, Keystone transform, super-resolution sparse Bayesian learning | ||||||||||||||||
Veranstaltungstitel: | IET International Conference on Radar Systems | ||||||||||||||||
Veranstaltungsort: | Belfast, UK | ||||||||||||||||
Veranstaltungsart: | internationale Konferenz | ||||||||||||||||
Veranstaltungsbeginn: | 23 Oktober 2017 | ||||||||||||||||
Veranstaltungsende: | 26 Oktober 2017 | ||||||||||||||||
HGF - Forschungsbereich: | Luftfahrt, Raumfahrt und Verkehr | ||||||||||||||||
HGF - Programm: | Luftfahrt | ||||||||||||||||
HGF - Programmthema: | Luftverkehrsmanagement und Flugbetrieb | ||||||||||||||||
DLR - Schwerpunkt: | Luftfahrt | ||||||||||||||||
DLR - Forschungsgebiet: | L AO - Air Traffic Management and Operation | ||||||||||||||||
DLR - Teilgebiet (Projekt, Vorhaben): | L - Kommunikation, Navigation und Überwachung (alt) | ||||||||||||||||
Standort: | Oberpfaffenhofen | ||||||||||||||||
Institute & Einrichtungen: | Institut für Kommunikation und Navigation > Nachrichtensysteme | ||||||||||||||||
Hinterlegt von: | Filip-Dhaubhadel, Dr. Alexandra | ||||||||||||||||
Hinterlegt am: | 01 Dez 2017 10:38 | ||||||||||||||||
Letzte Änderung: | 24 Apr 2024 20:17 |
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