NDLI: SAR canonical feature extraction using molecule dictionaries

Content Provider	IEEE Xplore Digital Library
Author	Hammond, G.B. Jackson, J.A.
Copyright Year	2013
Description	Author affiliation: Dept. of Electr. & Comput. Eng., Air Force Inst. of Technol., Wright-Patterson AFB, OH, USA (Hammond, G.B.; Jackson, J.A.)
Abstract	We apply a molecule dictionary approach to synthetic aperture radar canonical feature extraction. These canonical features capture physically-relevant scattering geometry as a function of shape type, frequency, aspect, and polarization. The extraction problem is a nonlinear nonconvex optimization that includes model order selection, feature classification, and parameter estimation. Previous work used image-based initializations, gradient descent, and a hierarchical classification scheme to extract the features. The dictionary approach shifts much of the computational burden to dictionary formation which can be done offline, prior to feature extraction. We show results for cases when the true feature lies in the dictionary and when it does not. Discussion of the practical challenges of dictionary construction is given in the context of recent sparse recovery literature.
Starting Page	1
Ending Page	6
File Size	1177868
Page Count	6
File Format	PDF
ISBN	9781467357920
ISSN	10975659
e-ISBN	9781467357944
DOI	10.1109/RADAR.2013.6586161
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-04-29
Publisher Place	Canada
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Dictionaries Shape Feature extraction Scattering Synthetic aperture radar Correlation
Content Type	Text
Resource Type	Article
Subject	Electrical and Electronic Engineering

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