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Incoherent detection of man-made objects obscured by foliage in forest area
Blekinge Tekniska Högskola, Fakulteten för teknikvetenskaper, Institutionen för matematik och naturvetenskap.ORCID-id: 0000-0002-6643-312x
Blekinge Tekniska Högskola, Fakulteten för teknikvetenskaper, Institutionen för matematik och naturvetenskap.
Universidade Federal de Santa Maria, BRA.
Saab Electronic Defense Systems, SWE.
Vise andre og tillknytning
2017 (engelsk)Inngår i: International Geoscience and Remote Sensing Symposium (IGARSS), Institute of Electrical and Electronics Engineers Inc. , 2017, s. 1892-1895Konferansepaper, Publicerat paper (Fagfellevurdert)
Abstract [en]

The paper introduces a new likelihood ratio test (LRT) for incoherent detection of man-made objects obscured by foliage in forest area. The test is performed to detect changes between a reference image and a surveillance image. The method is developed for change detection in high resolution Synthetic Aperture Radar (SAR). For simplicity and lack of more appropriate models, the new LRT is still based on simple and efficient models. If there is no man-made object, the statistical model for clutter and noise of two images will be a bivariate Rayleigh distribution. In contrary, a joint distribution of Rayleigh and uniform is used to model for target, clutter, and noise. The proposed LRT is evaluated using radar data acquired by CARABAS in northern Sweden. The probability of detection is up to 96% with much less than one false alarm per square kilometer. © 2017 IEEE.

sted, utgiver, år, opplag, sider
Institute of Electrical and Electronics Engineers Inc. , 2017. s. 1892-1895
Serie
IEEE International Symposium on Geoscience and Remote Sensing IGARSS, ISSN 2153-6996
Emneord [en]
Change Detection, LRT, Rayleigh, SAR
HSV kategori
Identifikatorer
URN: urn:nbn:se:bth-15923DOI: 10.1109/IGARSS.2017.8127347ISI: 000426954602003Scopus ID: 2-s2.0-85041836105ISBN: 9781509049516 (tryckt)OAI: oai:DiVA.org:bth-15923DiVA, id: diva2:1184808
Konferanse
37th Annual IEEE International Geoscience and Remote Sensing Symposium, IGARSS, Fort Worth
Tilgjengelig fra: 2018-02-22 Laget: 2018-02-22 Sist oppdatert: 2018-04-12bibliografisk kontrollert

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