Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Incoherent detection of man-made objects obscured by foliage in forest area
Blekinge Institute of Technology, Faculty of Engineering, Department of Mathematics and Natural Sciences.ORCID iD: 0000-0002-6643-312x
Blekinge Institute of Technology, Faculty of Engineering, Department of Mathematics and Natural Sciences.
Universidade Federal de Santa Maria, BRA.
Saab Electronic Defense Systems, SWE.
Show others and affiliations
2017 (English)In: International Geoscience and Remote Sensing Symposium (IGARSS), Institute of Electrical and Electronics Engineers Inc. , 2017, p. 1892-1895Conference paper, Published paper (Refereed)
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.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers Inc. , 2017. p. 1892-1895
Series
IEEE International Symposium on Geoscience and Remote Sensing IGARSS, ISSN 2153-6996
Keywords [en]
Change Detection, LRT, Rayleigh, SAR
National Category
Other Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
URN: urn:nbn:se:bth-15923DOI: 10.1109/IGARSS.2017.8127347ISI: 000426954602003Scopus ID: 2-s2.0-85041836105ISBN: 9781509049516 OAI: oai:DiVA.org:bth-15923DiVA, id: diva2:1184808
Conference
37th Annual IEEE International Geoscience and Remote Sensing Symposium, IGARSS, Fort Worth
Available from: 2018-02-22 Created: 2018-02-22 Last updated: 2018-04-12Bibliographically approved

Open Access in DiVA

No full text in DiVA

Other links

Publisher's full textScopus

Authority records BETA

Pettersson, MatsVu, Viet Thuy

Search in DiVA

By author/editor
Pettersson, MatsVu, Viet Thuy
By organisation
Department of Mathematics and Natural Sciences
Other Electrical Engineering, Electronic Engineering, Information Engineering

Search outside of DiVA

GoogleGoogle Scholar

doi
isbn
urn-nbn

Altmetric score

doi
isbn
urn-nbn
Total: 10 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf