An algorithm for tracking a random walk with unknown drift

Author

Le Calvez, Jean Luc ; Delyon, Bernard ; Juditsky, Anatoli

Author_Institution

IRISA, Rennes, France

Volume

4

fYear

1998

fDate

12-15 May 1998

Firstpage

2177

Abstract

We study the problem of tracking a random walk observed with noise when the variance of the walk increment is unknown. We describe a sequence of estimators of the random walk and we design an algorithm to choose the best estimator among all the sequence. We give also a bound for the mean square error of this estimator. Finally some simulations are presented and we compare our algorithm with the Kalman filter when the variance of the walk increment is estimated

Keywords

least mean squares methods; noise; parameter estimation; random processes; signal processing; tracking; Kalman filter; mean square error bound; noisy observations; random walk estimators; sequence; signal processing; simulations; stochastic system; system identification; tracking algorithm; unknown drift; walk increment variance; Adaptive signal processing; Algorithm design and analysis; Covariance matrix; Filters; Mean square error methods; Signal processing algorithms; Stochastic systems; System identification; Time varying systems; White noise;

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.1998.681578

Filename

681578