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Ship detection using the surface scattering similarity and scattering power
Shanghai Jiao Tong Univ, Shanghai Key Lab Intelligent Sensing & Recognit, Shanghai 200240, Peoples R China..
Jiangxi Sci & Technol Normal Univ, Nanchang 330013, Jiangxi, Peoples R China..
Nanjing Univ Finance & Econ, Jiangsu Key Lab Grain Big Data Min & Applicat, Coll Informat Engn, Nanjing 210023, Peoples R China..
Tsinghua Univ, Dept Elect Engn, Beijing 100084, Peoples R China..
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2019 (English)In: 2019 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS 2019), IEEE , 2019, p. 1264-1267Conference paper, Published paper (Refereed)
Abstract [en]

Sea surface and ship have different backscattering mechanisms, in which surface scattering is predominant for sea surface in the low sea state case. Based on this fact, many ship detectors have been developed by suppressing the surface scattering resulted from sea surface. Actually, small ship may also have strong surface scattering sometimes. In such a case, the methods of avoiding using surface scattering features may easily miss the detection of small ships. To verify this point, in this paper, we first analyze the shortcomings of An's method which is based on surface scattering similarity and the power maximization synthesis detector (PMS), and then improve it for detecting small ships more effectively. In order to demonstrate the performance of the proposed method, AIRSAR L-Band Polarimetric SAR dataset is exploited. Comparing to other methods, the new method shows a better ship detection performance.

Place, publisher, year, edition, pages
IEEE , 2019. p. 1264-1267
Series
IEEE International Symposium on Geoscience and Remote Sensing IGARSS, ISSN 2153-6996
Keywords [en]
Backscattering, surface scattering, small ship, surface scattering similarity, PMS, ship detection
National Category
Mechanical Engineering
Identifiers
URN: urn:nbn:se:kth:diva-271967DOI: 10.1109/igarss.2019.8899821ISI: 000519270601130Scopus ID: 2-s2.0-85077725344ISBN: 978-1-5386-9154-0 (print)OAI: oai:DiVA.org:kth-271967DiVA, id: diva2:1423570
Conference
IEEE International Geoscience and Remote Sensing Symposium (IGARSS), JUL 28-AUG 02, 2019, Yokohama, JAPAN
Note

QC 20200415

Available from: 2020-04-15 Created: 2020-04-15 Last updated: 2020-05-11Bibliographically approved

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Ban, Yifang

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