DocumentCode :
805918
Title :
Noise subspace techniques in non-gaussian noise using cumulants
Author :
Sadler, Brian M. ; Giannakis, Georgios B. ; Shamsunder, Sanyogita
Author_Institution :
Army Res. Lab, Adelphi, MD, USA
Volume :
31
Issue :
3
fYear :
1995
fDate :
7/1/1995 12:00:00 AM
Firstpage :
1009
Lastpage :
1018
Abstract :
We consider noise subspace methods for narrowband direction-of-arrival or harmonic retrieval in colored linear non-gaussian noise of unknown covariance and unknown distribution. The non-gaussian noise covariance is estimated via higher order cumulants and combined with correlation information to solve a generalized eigenvalue problem. The estimated eigenvectors are used in a variety of noise subspace methods such as multiple signal classification (MUSIC), MVDR and eigenvector. The noise covariance estimates are obtained in the presence of the harmonic signals, obviating the need for noise-only training records. The covariance estimates may be obtained nonparametrically via cumulant projections, or parametrically using autoregressive moving average (ARMA) models. An information theoretic criterion using higher order cumulants is presented which may be used to simultaneously estimate the ARMA model order and parameters. Third- and fourth-order cumulants are employed for asymmetric and symmetric probability density function (pdf) cases, respectively. Simulation results show considerable improvement over conventional methods with no prewhitening. The effects of prewhitening are particularly evident in the dominant eigenvalues, as revealed by singular value decomposition (SVD) analysis
Keywords :
autoregressive moving average processes; correlation methods; direction-of-arrival estimation; eigenvalues and eigenfunctions; harmonic analysis; higher order statistics; probability; random noise; signal detection; ARMA models; MUSIC; MVDR; asymmetric probability density function; autoregressive moving average models; colored linear noise; cumulants; dominant eigenvalues; eigenvector; estimated eigenvectors; generalized eigenvalue problem; harmonic retrieval; harmonic signals; multiple signal classification; narrowband direction-of-arrival; noise covariance estimates; noise subspace; noise-only training records; nongaussian noise; prewhitening; singular value decomposition; symmetric probability density function; Autoregressive processes; Colored noise; Eigenvalues and eigenfunctions; Gaussian noise; Laboratories; Multiple signal classification; Music information retrieval; Narrowband; Signal to noise ratio; State estimation;
fLanguage :
English
Journal_Title :
Aerospace and Electronic Systems, IEEE Transactions on
Publisher :
ieee
ISSN :
0018-9251
Type :
jour
DOI :
10.1109/7.395239
Filename :
395239
Link To Document :
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