Case study of principal component inverse and cross spectral metric for low rank interference adaptation

Author

Freburger, B.E. ; Tufts, D.W.

Author_Institution

Dept. of Comput. & Electr. Eng., Rhode Island Univ., Kingston, RI, USA

Volume

4

fYear

1998

fDate

12-15 May 1998

Firstpage

1977

Abstract

This paper presents a review of the principal component inverse (PCI) method of rapid adaptive signal detection and contrasts the use of principal components with the cross spectral metric (CSM) method for the generalized sidelobe canceller. The CSM method is optimal with known statistics and has been shown to outperform the PCI method in many cases of unknown covariance. This paper describes a scenario which represents a class of covariances where the PCI method can be expected to outperform the CSM method. The choice of method is therefore more subtle than previously thought

Keywords

adaptive signal detection; covariance matrices; interference suppression; inverse problems; statistical analysis; CSM method; PCI method; covariance; cross spectral metric; generalized sidelobe canceller; low rank interference adaptation; principal component inverse; rapid adaptive signal detection; review; Computer aided software engineering; Covariance matrix; Detectors; Eigenvalues and eigenfunctions; Integrated circuit noise; Interference cancellation; Signal to noise ratio; Statistical analysis; Statistical distributions; Testing;

fLanguage

English

Publisher

ieee

Conference_Titel

Acoustics, Speech and Signal Processing, 1998. Proceedings of the 1998 IEEE International Conference on

Conference_Location

Seattle, WA

ISSN

1520-6149

Print_ISBN

0-7803-4428-6

Type

conf

DOI

10.1109/ICASSP.1998.681528

Filename

681528