Response of accelerated fast RLS adaptive filters to linear chirps

Author

Gilloire, Andre

Author_Institution

CNET, Lannion, France

fYear

1991

fDate

14-17 Apr 1991

Firstpage

1873

Abstract

The author considers the problem of tracking a linearly chirped sinusoid with additive noise with an accelerated fast recursive least squares (FRLS) adaptive filtering algorithm, which was proven to be as efficient as the least mean square (LMS) algorithm for the identification of time-varying filters. It is shown both theoretically and experimentally that the accelerated fast RLS algorithm has the same performance as the standard fast RLS (which is inferior to the LMS performance). Thus, the acceleration method does not improve the performance in the chirp tracking context; however, the choice of the forgetting factor is made more flexible

Keywords

adaptive filters; digital filters; least squares approximations; tracking; LMS algorithm; accelerated fast RLS algorithm; adaptive filtering algorithm; additive noise; chirp tracking; fast recursive least squares; forgetting factor; identification; least mean square; linearly chirped sinusoid; time-varying filters; Acceleration; Adaptive filters; Additive noise; Chirp; Context; Filtering algorithms; Least squares approximation; Line enhancers; Radar tracking; Resonance light scattering;

fLanguage

English

Publisher

ieee

Conference_Titel

Acoustics, Speech, and Signal Processing, 1991. ICASSP-91., 1991 International Conference on

Conference_Location

Toronto, Ont.

ISSN

1520-6149

Print_ISBN

0-7803-0003-3

Type

conf

DOI

10.1109/ICASSP.1991.150734

Filename

150734