A class of subspace tracking algorithms based on approximation of the noise-subspace

Author

Gustafsson, Thomas ; MacInnes, C.S.

Author_Institution

Dept. of Signals & Syst., Chalmers Univ. of Technol., Goteborg

Volume

48

Issue

11

fYear

2000

fDate

11/1/2000 12:00:00 AM

Firstpage

3231

Lastpage

3235

Abstract

This correspondence introduces a novel class of so-called subspace tracking algorithms applicable to, for example, sensor array signal processing. The basic idea pursued in this correspondence is to reduce the amount of computations required for an exact SVD update, applying a perturbation-like strategy, which is interpreted as an approximation of a noise subspace. An interesting property of the derived algorithms is that they can be applied to SVD updating of both auto- and cross-covariance matrices

Keywords

approximation theory; array signal processing; covariance matrices; direction-of-arrival estimation; noise; singular value decomposition; tracking; DOA estimation; STAN algorithms; SVD update; array signal processing; auto-covariance matrices; cross-covariance matrices; noise-subspace approximation; perturbation-like strategy; sensor array; subspace tracking algorithms; Antenna arrays; Approximation algorithms; Array signal processing; Autocorrelation; Chromium; Design methodology; Noise reduction; Random processes; Sensor arrays; Signal processing algorithms;

fLanguage

English

Journal_Title

Signal Processing, IEEE Transactions on

Publisher

ieee

ISSN

1053-587X

Type

jour

DOI

10.1109/78.875479

Filename

875479