Adaptive line enhancement via subspace tracking

Author

Hayward, S.D. ; Sprigings, C.J.

Author_Institution

DERA, Malvern, UK

Volume

2

fYear

2000

fDate

Oct. 29 2000-Nov. 1 2000

Firstpage

1872

Abstract

We propose a new algorithm for adaptive line enhancement. The objective is to improve the signal-to-noise ratio of narrowband signals in additive white noise by adaptive filtering. By recursively updating an estimate of a rank I signal subspace we develop a fast algorithm having the same computational complexity as LMS i.e. O(m), where m is the filter length. We demonstrate the superiority of this approach over LMS in terms of the rate of convergence and the ability to track LFM signals.

Keywords

AWGN; adaptive filters; adaptive signal processing; band-pass filters; computational complexity; convergence of numerical methods; covariance matrices; eigenvalues and eigenfunctions; filtering theory; frequency modulation; least mean squares methods; prediction theory; signal reconstruction; tracking filters; AWGN; LFM signal tracking; LMS predictor; SNR; adaptive bandpass filter; adaptive filtering; adaptive line enhancement; additive white Gaussian noise; algorithm; computational complexity; convergence rate; covariance matrix; eigenvector; fast algorithm; filter length; power method; recursive estimate updating; signal enhancement; signal reconstruction; signal subspace; signal-to-noise ratio; subspace tracking; Additive white noise; Band pass filters; Convergence; Finite impulse response filter; Frequency estimation; Least squares approximation; Narrowband; Radar detection; Radar tracking; Signal processing;

fLanguage

English

Publisher

ieee

Conference_Titel

Signals, Systems and Computers, 2000. Conference Record of the Thirty-Fourth Asilomar Conference on

Conference_Location

Pacific Grove, CA, USA

ISSN

1058-6393

Print_ISBN

0-7803-6514-3

Type

conf

DOI

10.1109/ACSSC.2000.911312

Filename

911312