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Azimuth Correlation Models for Radar Imaging
Michael D. DeVore
, Joseph A. O'Sullivan
, Lee J. Montagnino
Department of Electrical & Systems Engineering
McKelvey School of Engineering
Research output
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Contribution to journal
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Conference article
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peer-review
1
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Scopus citations
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Keyphrases
Target Recognition
100%
Expectation Maximization
100%
Maximum Likelihood Estimation
100%
Probabilistic Model
100%
Estimation Method
100%
Correlation Model
100%
Process Data
100%
Covariance
100%
Image Formation
100%
Linear Combination
100%
Radar Data
100%
Automatic Target Recognition
100%
Electromagnetic Model
100%
Circular Domain
100%
Autocovariance
100%
Synthetic Aperture Radar Image
100%
Computational Electromagnetics
100%
SAR Image
100%
Image Dataset
100%
Complex Dependencies
100%
Radar Imaging
100%
Nonstationary Process
100%
Engineering
Maximum Likelihood
100%
Image Data
100%
Measured Data
100%
Collected Data
100%
Maximization
100%
Maximum Likelihood Estimation
100%
Basis Function
100%
Linear Combination
100%
Radar Data
100%
Target Recognition
100%
Correlation Model
100%
Nonstationary Process
100%
Image Formation
100%
Synthetic Aperture Radar
100%
Automatic Target Recognition
100%
Synthetic Aperture Radar Images
100%
Base Address
100%
Autocovariance
100%
Earth and Planetary Sciences
Synthetic Aperture Radar
100%
Radar Imaging
100%
Covariance
50%
Radar Data
50%
Estimation Method
50%
Electromagnetism
50%