Spectral-domain covariance estimation with a priori knowledge

A knowledge-aided spectral-domain approach to estimating the interference covariance matrix used in space-time adaptive processing (STAP) is proposed. Prior knowledge of the range-Doppler clutter scene is used to identify geographic regions with homogeneous scattering statistics. Then, minimum-varia...

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Bibliographic Details
Published in:IEEE transactions on aerospace and electronic systems 2006-07, Vol.42 (3), p.1010-1020
Main Authors: Gurram, P.R., Goodman, N.A.
Format: Article
Language:English
Subjects:
Clutter
Covariance matrix
Estimates
Estimating
Interference
Layout
Maximum likelihood detection
Maximum likelihood estimation
Performance degradation
Radar scattering
Scattering
Signal detection
Signal processing
Spectra
Statistics
Training data
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Summary:A knowledge-aided spectral-domain approach to estimating the interference covariance matrix used in space-time adaptive processing (STAP) is proposed. Prior knowledge of the range-Doppler clutter scene is used to identify geographic regions with homogeneous scattering statistics. Then, minimum-variance spectral estimation is used to arrive at a spectral-domain clutter estimate. Finally, space-time steering vectors are used to transform the spectral-domain estimate into a data-domain estimate of the clutter covariance matrix. The proposed technique is compared with ideal performance and to the fast maximum likelihood technique using simulated results. An investigation of the performance degradation that can occur due to various inaccurate knowledge assumptions is also presented
ISSN:0018-9251
1557-9603
DOI:10.1109/TAES.2006.248209