Title :
Principal components, covariance matrix tapers, and the subspace leakage problem
Author :
Guerci, J.R. ; Bergin, J.S.
Author_Institution :
Special Projects Office, Defense Adv. Res. Projects Agency, Arlington, VA, USA
fDate :
1/1/2002 12:00:00 AM
Abstract :
A new class of robust space-time adaptive beamforming techniques is introduced to address a broad range of subspace leakage phenomena that arise in many sensor array applications. When present, these leakage phenomena can significantly increase the effective rank of the dominant colored noise interference spectrum, thereby reducing the appeal of techniques that exploit low-rank dominant interference (such as principal components (PC) or diagonal loading) to reduce sample support (training) requirements. By combining the covariance matrix taper (CMT) approach with either PC or diagonal loading, the minimal sample support properties of these techniques can be preserved
Keywords :
Karhunen-Loeve transforms; airborne radar; array signal processing; covariance matrices; decorrelation; eigenvalues and eigenfunctions; principal component analysis; radar clutter; radar interference; radar signal processing; space-time adaptive processing; Karhunen-Loeve representation; clutter; colored noise interference spectrum; covariance matrix taper; diagonal loading; effective rank; eigenspectrum modulation; minimal support properties; moving target indicator radar; principal components; robust techniques; sensor array applications; side-looking airborne array; space-time adaptive beamforming; spatial decorrelation; subspace leakage phenomena; temporal decorrelation; Array signal processing; Clutter; Colored noise; Covariance matrix; Information systems; Interference; Jamming; Narrowband; Sensor arrays; White noise;
Journal_Title :
Aerospace and Electronic Systems, IEEE Transactions on