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A Cognitive SAR Concept for Ship Detection using Support Vector Machines

Meyer, Jan und Glatting, Kay und Huber, Sigurd und Krieger, Gerhard (2024) A Cognitive SAR Concept for Ship Detection using Support Vector Machines. In: Proceedings of the European Conference on Synthetic Aperture Radar, EUSAR, Seiten 537-442. European Conference on Synthetic Aperture Radar (EUSAR), 2024-04-23 - 2024-04-26, Munich, Germany. ISSN 2197-4403.

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Kurzfassung

Cognitive radar is a new acquisition technique that forms a closed loop between radar receiver, radar transmitter and environment, similar to the perception-action cycle in human cognition. The continuous adaptation of the acquisition parameters based on previously acquired information also harbours great potential for future SAR missions. As an example, this paper presents a spaceborne cognitive SAR concept for ship detection. The concept foresees a two-stage process to improve the overall ship detection probability compared to conventional approaches. First, a wide-swath mode with coarse resolution is utilized to cover a large maritime area. From these SAR data, the positions of potential ships shall be detected, however, due to the low signal-to-clutter ratio, with a high false alarm rate. In the second step, a high-gain mode with fine resolution is used to look at the presumed ship positions and either confirm or reject the presence of ships with high fidelity. This radar concept could be realized on a single platform using a hybrid mode. In the context of this investigation, the cognitive functionality is distributed on two separate SAR satellites operated in a convoy configuration, where the leading satellite performs the first coarse-detection step and the companion satellite implements the high-fidelity detection step including intelligent digital beamforming of one or more spotlight beams accessible via phased array antennas.

elib-URL des Eintrags:https://elib.dlr.de/203395/
Dokumentart:Konferenzbeitrag (Vortrag, Poster)
Titel:A Cognitive SAR Concept for Ship Detection using Support Vector Machines
Autoren:
AutorenInstitution oder E-Mail-AdresseAutoren-ORCID-iDORCID Put Code
Meyer, Janjan.meyer (at) dlr.dehttps://orcid.org/0009-0002-8248-4469159665092
Glatting, KayKay.Glatting (at) dlr.dehttps://orcid.org/0009-0006-7388-8233159665094
Huber, SigurdSigurd.Huber (at) dlr.dehttps://orcid.org/0000-0001-7097-5127NICHT SPEZIFIZIERT
Krieger, GerhardGerhard.Krieger (at) dlr.dehttps://orcid.org/0000-0002-4548-0285NICHT SPEZIFIZIERT
Datum:April 2024
Erschienen in:Proceedings of the European Conference on Synthetic Aperture Radar, EUSAR
Referierte Publikation:Ja
Open Access:Ja
Gold Open Access:Nein
In SCOPUS:Ja
In ISI Web of Science:Nein
Seitenbereich:Seiten 537-442
ISSN:2197-4403
Status:veröffentlicht
Stichwörter:Cognitive Radar, SAR
Veranstaltungstitel:European Conference on Synthetic Aperture Radar (EUSAR)
Veranstaltungsort:Munich, Germany
Veranstaltungsart:internationale Konferenz
Veranstaltungsbeginn:23 April 2024
Veranstaltungsende:26 April 2024
Veranstalter :VDE
HGF - Forschungsbereich:keine Zuordnung
HGF - Programm:keine Zuordnung
HGF - Programmthema:keine Zuordnung
DLR - Schwerpunkt:Quantencomputing-Initiative
DLR - Forschungsgebiet:QC AW - Anwendungen
DLR - Teilgebiet (Projekt, Vorhaben):QC - QUA-SAR
Standort: Oberpfaffenhofen
Institute & Einrichtungen:Institut für Hochfrequenztechnik und Radarsysteme
Hinterlegt von: Meyer, Jan
Hinterlegt am:15 Mai 2024 17:01
Letzte Änderung:15 Mai 2024 17:01

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