&lt;title&gt;Automatic classification of targets in synthetic aperture radar imagery using topographic features&lt;/title&gt;

Meth, Reuven; Chellappa, Rama

doi:10.1117/12.242047

Cited by 11 publications

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“…In SAR target recognition (TR), azimuth feature information plays a key role which would be used to match the specific targets in a given target database [1]. Then Find the maximum matching value and classify the targets analyzed.…”

Section: Introductionmentioning

confidence: 99%

Feature extraction of a generic SAR target using an improved data model

Wang

Liu

2013

2013 IEEE International Geoscience and Remote Sensing Symposium - IGARSS

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Here feature extraction of a generic SAR target is studied. We apply a new data model to target feature extraction and improve SAR image quality. The data model we construct contains (1) envelope, (2) location of the target. The envelope shape can be controlled by four parameters, and location information is indicated by frequency pair in both range and cross-range. These parameters would be estimated by nonlinear least squares (NLS) and 1-D Cramer-Rao Bounds (CRB) for these parameters have also been analyzed. Numerical examples show this method can achieve CRB at high SNR and its computational complexity is acceptable.

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Section: Introductionmentioning

confidence: 99%

Feature extraction of a generic SAR target using an improved data model

Wang

Liu

2013

2013 IEEE International Geoscience and Remote Sensing Symposium - IGARSS

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“…The detection theory [4,5], pattern recognition [13,16,17] and neural network [7,18] approaches to SAR recognition all tend to use global features that are optimized for standard, nonarticulated, nonoccluded configurations. Approaches that rely on global features are not appropriate for recognizing occluded (or articulated) objects because occlusion (or articulation) changes global features like the object outline and major axis [20].…”

Section: Introductionmentioning

confidence: 99%

Recognizing occluded objects in SAR images

Jones

Bhanu

2001

IEEE Trans. Aerosp. Electron. Syst.

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Recognizing occluded vehicle targets in synthetic aperture radar (SAR) images is addressed. Recognition algorithms, based on local features, are presented that successfully recognize highly occluded objects in both XPATCH synthetic SAR signatures and real SAR images of actual vehicles from the MSTAR data. Extensive experimental results are presented for a basic recognition algorithm, using SAR scattering center relative locations as features with the XPATCH data and for an improvedManuscript

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Methods for Improving the Performance of an SAR Recognition System

Bhanu

Jones

2005

Computer Vision Beyond the Visible Spectrum

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<title>Automatic classification of targets in synthetic aperture radar imagery using topographic features</title>

Cited by 11 publications

References 0 publications

Feature extraction of a generic SAR target using an improved data model

Feature extraction of a generic SAR target using an improved data model

Recognizing occluded objects in SAR images

Methods for Improving the Performance of an SAR Recognition System

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