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Title: Classification of subsurface objects using singular values derived from signal frames

Abstract

The classification system represents a detected object with a feature vector derived from the return signals acquired by an array of N transceivers operating in multistatic mode. The classification system generates the feature vector by transforming the real-valued return signals into complex-valued spectra, using, for example, a Fast Fourier Transform. The classification system then generates a feature vector of singular values for each user-designated spectral sub-band by applying a singular value decomposition (SVD) to the N.times.N square complex-valued matrix formed from sub-band samples associated with all possible transmitter-receiver pairs. The resulting feature vector of singular values may be transformed into a feature vector of singular value likelihoods and then subjected to a multi-category linear or neural network classifier for object classification.

Inventors:
;
Issue Date:
Research Org.:
LLNL (Lawrence Livermore National Laboratory (LLNL), Livermore, CA (United States))
Sponsoring Org.:
USDOE
OSTI Identifier:
1130522
Patent Number(s):
8,717,223
Application Number:
13/219,435
Assignee:
Lawrence Livermore National Security, LLC (Livermore, CA)
DOE Contract Number:  
AC52-07NA27344
Resource Type:
Patent
Country of Publication:
United States
Language:
English
Subject:
97 MATHEMATICS AND COMPUTING

Citation Formats

Chambers, David H, and Paglieroni, David W. Classification of subsurface objects using singular values derived from signal frames. United States: N. p., 2014. Web.
Chambers, David H, & Paglieroni, David W. Classification of subsurface objects using singular values derived from signal frames. United States.
Chambers, David H, and Paglieroni, David W. Tue . "Classification of subsurface objects using singular values derived from signal frames". United States. https://www.osti.gov/servlets/purl/1130522.
@article{osti_1130522,
title = {Classification of subsurface objects using singular values derived from signal frames},
author = {Chambers, David H and Paglieroni, David W},
abstractNote = {The classification system represents a detected object with a feature vector derived from the return signals acquired by an array of N transceivers operating in multistatic mode. The classification system generates the feature vector by transforming the real-valued return signals into complex-valued spectra, using, for example, a Fast Fourier Transform. The classification system then generates a feature vector of singular values for each user-designated spectral sub-band by applying a singular value decomposition (SVD) to the N.times.N square complex-valued matrix formed from sub-band samples associated with all possible transmitter-receiver pairs. The resulting feature vector of singular values may be transformed into a feature vector of singular value likelihoods and then subjected to a multi-category linear or neural network classifier for object classification.},
doi = {},
journal = {},
number = ,
volume = ,
place = {United States},
year = {2014},
month = {5}
}

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