KAGE: a new fast RLS algorithm

Author

Skidmore, I.D. ; Proudler, I.K.

Author_Institution

DERA, Malvern, UK

Volume

6

fYear

2001

fDate

2001

Firstpage

3773

Abstract

A new fast recursive least squares (RLS) algorithm is introduced. By making use of RLS interpolation as well prediction, the algorithm generates the transversal filter weights without suffering the poor numerical attributes of the FTF algorithm. The Kalman gain vector is generated at each time step in terms of interpolation residuals. The interpolation residuals are calculated in an order recursive manner. For an Nth order problem the procedure requires O(NlogN) operations. This is achieved via a divide and conquer approach. Computer simulations suggest the new algorithm is numerically robust, running successfully for many millions of iterations

Keywords

Kalman filters; divide and conquer methods; interpolation; least squares approximations; recursive filters; KAGE; Kalman gain vector; RLS algorithm; computer simulations; divide and conquer approach; interpolation residuals; numerical robustness; order recursive manner; prediction; recursive least squares; transversal filter weights; Adaptive filters; Equations; Filtering algorithms; Interpolation; Kalman filters; Lattices; Least squares methods; Resonance light scattering; Robustness; Transversal filters;

fLanguage

English

Publisher

ieee

Conference_Titel

Acoustics, Speech, and Signal Processing, 2001. Proceedings. (ICASSP '01). 2001 IEEE International Conference on

Conference_Location

Salt Lake City, UT

ISSN

1520-6149

Print_ISBN

0-7803-7041-4

Type

conf

DOI

10.1109/ICASSP.2001.940664

Filename

940664