Identifying an autoregressive process disturbed by a moving-average noise using inner-outer factorization

Date
2015-08-02
Authors
Abdou, Ahmad
Turcu, Flavius
Diversi, Roberto
Ferre, Guillaume
Grivel, Eric
Journal Title
Journal ISSN
Volume Title
Publisher
Springer-Verlag London 2015
Abstract
This paper deals with the identification of an autoregressive (AR) process disturbed by an additivemovingaverage (MA) noise. Our approach operates as follows: Firstly, the AR parameters are estimated by using the overdetermined high-order Yule–Walker equations. The variance of the AR process driving process can be deduced by means of an orthogonal projection between two types of estimates of AR process correlation vectors. Then, the correlation sequence of the MA noise is estimated. Secondly, the MA parameters are obtained by using inner–outer factorization. To study the relevance of the resulting method, we compare it with existing algorithms, and we analyze the identifiability limits. The identification approach is then combined with Kalman filtering for channel estimation in mobile communication systems.
Description
Keywords
Autoregressive process (AR), Moving-avergae process (MA), Inner–outer factorization, Overdetermined high-order Yule–Walker equations
Citation