Details
Originalsprache | Englisch |
---|---|
Titel des Sammelwerks | 2018 15th European Radar Conference, EuRAD 2018 |
Herausgeber (Verlag) | Institute of Electrical and Electronics Engineers Inc. |
Seiten | 146-149 |
Seitenumfang | 4 |
ISBN (elektronisch) | 9782874870538 |
Publikationsstatus | Veröffentlicht - 26 Nov. 2018 |
Veranstaltung | 15th European Radar Conference, EuRAD 2018 - Madrid, Spanien Dauer: 26 Sept. 2018 → 28 Sept. 2018 |
Abstract
In this paper, we present a backprojection autofocus method to image moving ships in high resolution very precisely. This technique might make an automatic ship classification based on Synthetic Aperture Radar (SAR) images without using additional information from the Automated Identification System (AIS) possible. We use a Constant False Alarm Rate (CFAR) detector to estimate the coarse position of a ship in a preview SAR image. A second high resolution image of the ship is generated by the proposed backprojection autofocus algorithm. Our autofocus estimates the time depending distance between the sensor and every pixel in the SAR image, which includes the rotation and the translation of the ship. This estimated relative distance is used to compute a high quality autofocused SAR image of the considered moving ship.
ASJC Scopus Sachgebiete
- Informatik (insg.)
- Signalverarbeitung
- Ingenieurwesen (insg.)
- Sicherheit, Risiko, Zuverlässigkeit und Qualität
- Physik und Astronomie (insg.)
- Instrumentierung
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2018 15th European Radar Conference, EuRAD 2018. Institute of Electrical and Electronics Engineers Inc., 2018. S. 146-149 8546561.
Publikation: Beitrag in Buch/Bericht/Sammelwerk/Konferenzband › Aufsatz in Konferenzband › Forschung › Peer-Review
}
TY - GEN
T1 - Backprojection Autofocus of Moving Ships for Synthetic Aperture Radar
AU - Sommer, Aron
AU - Ostermann, Jörn
PY - 2018/11/26
Y1 - 2018/11/26
N2 - In this paper, we present a backprojection autofocus method to image moving ships in high resolution very precisely. This technique might make an automatic ship classification based on Synthetic Aperture Radar (SAR) images without using additional information from the Automated Identification System (AIS) possible. We use a Constant False Alarm Rate (CFAR) detector to estimate the coarse position of a ship in a preview SAR image. A second high resolution image of the ship is generated by the proposed backprojection autofocus algorithm. Our autofocus estimates the time depending distance between the sensor and every pixel in the SAR image, which includes the rotation and the translation of the ship. This estimated relative distance is used to compute a high quality autofocused SAR image of the considered moving ship.
AB - In this paper, we present a backprojection autofocus method to image moving ships in high resolution very precisely. This technique might make an automatic ship classification based on Synthetic Aperture Radar (SAR) images without using additional information from the Automated Identification System (AIS) possible. We use a Constant False Alarm Rate (CFAR) detector to estimate the coarse position of a ship in a preview SAR image. A second high resolution image of the ship is generated by the proposed backprojection autofocus algorithm. Our autofocus estimates the time depending distance between the sensor and every pixel in the SAR image, which includes the rotation and the translation of the ship. This estimated relative distance is used to compute a high quality autofocused SAR image of the considered moving ship.
KW - airborne radar
KW - autofocus
KW - inverse synthetic aperture radar
KW - radar detection
KW - radar imaging
KW - Synthetic aperture radar
UR - http://www.scopus.com/inward/record.url?scp=85060402866&partnerID=8YFLogxK
U2 - 10.23919/eurad.2018.8546561
DO - 10.23919/eurad.2018.8546561
M3 - Conference contribution
AN - SCOPUS:85060402866
SP - 146
EP - 149
BT - 2018 15th European Radar Conference, EuRAD 2018
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 15th European Radar Conference, EuRAD 2018
Y2 - 26 September 2018 through 28 September 2018
ER -