Frequency Adaptability and Waveform Design for OFDM Radar SpaceTime Adaptive Processing
Abstract
We propose an adaptive waveform design technique for an orthogonal frequency division multiplexing (OFDM) radar signal employing a spacetime adaptive processing (STAP) technique. We observe that there are inherent variabilities of the target and interference responses in the frequency domain. Therefore, the use of an OFDM signal can not only increase the frequency diversity of our system, but also improve the target detectability by adaptively modifying the OFDM coefficients in order to exploit the frequencyvariabilities of the scenario. First, we formulate a realistic OFDMSTAP measurement model considering the sparse nature of the target and interference spectra in the spatiotemporal domain. Then, we show that the optimal STAPfilter weightvector is equal to the generalized eigenvector corresponding to the minimum generalized eigenvalue of the interference and target covariance matrices. With numerical examples we demonstrate that the resultant OFDMSTAP filterweights are adaptable to the frequencyvariabilities of the target and interference responses, in addition to the spatiotemporal variabilities. Hence, by better utilizing the frequency variabilities, we propose an adaptive OFDMwaveform design technique, and consequently gain a significant amount of STAPperformance improvement.
 Authors:
 ORNL
 Publication Date:
 Research Org.:
 Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
 Sponsoring Org.:
 USDOE Laboratory Directed Research and Development (LDRD) Program
 OSTI Identifier:
 1040747
 DOE Contract Number:
 DEAC0500OR22725
 Resource Type:
 Conference
 Resource Relation:
 Conference: IEEE Radar Conference, Atlanta, GA, USA, 20120507, 20120511
 Country of Publication:
 United States
 Language:
 English
 Subject:
 99 GENERAL AND MISCELLANEOUS//MATHEMATICS, COMPUTING, AND INFORMATION SCIENCE; DESIGN; EIGENVALUES; EIGENVECTORS; MATRICES; PROCESSING; RADAR; SPACETIME; SPECTRA; TARGETS; WAVE FORMS
Citation Formats
Sen, Satyabrata, and Glover, Charles Wayne. Frequency Adaptability and Waveform Design for OFDM Radar SpaceTime Adaptive Processing. United States: N. p., 2012.
Web.
Sen, Satyabrata, & Glover, Charles Wayne. Frequency Adaptability and Waveform Design for OFDM Radar SpaceTime Adaptive Processing. United States.
Sen, Satyabrata, and Glover, Charles Wayne. Sun .
"Frequency Adaptability and Waveform Design for OFDM Radar SpaceTime Adaptive Processing". United States.
doi:.
@article{osti_1040747,
title = {Frequency Adaptability and Waveform Design for OFDM Radar SpaceTime Adaptive Processing},
author = {Sen, Satyabrata and Glover, Charles Wayne},
abstractNote = {We propose an adaptive waveform design technique for an orthogonal frequency division multiplexing (OFDM) radar signal employing a spacetime adaptive processing (STAP) technique. We observe that there are inherent variabilities of the target and interference responses in the frequency domain. Therefore, the use of an OFDM signal can not only increase the frequency diversity of our system, but also improve the target detectability by adaptively modifying the OFDM coefficients in order to exploit the frequencyvariabilities of the scenario. First, we formulate a realistic OFDMSTAP measurement model considering the sparse nature of the target and interference spectra in the spatiotemporal domain. Then, we show that the optimal STAPfilter weightvector is equal to the generalized eigenvector corresponding to the minimum generalized eigenvalue of the interference and target covariance matrices. With numerical examples we demonstrate that the resultant OFDMSTAP filterweights are adaptable to the frequencyvariabilities of the target and interference responses, in addition to the spatiotemporal variabilities. Hence, by better utilizing the frequency variabilities, we propose an adaptive OFDMwaveform design technique, and consequently gain a significant amount of STAPperformance improvement.},
doi = {},
journal = {},
number = ,
volume = ,
place = {United States},
year = {Sun Jan 01 00:00:00 EST 2012},
month = {Sun Jan 01 00:00:00 EST 2012}
}

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