Iterative approach to estimate the parameters of a TVAR process corrupted by a MA noise. Ijima, H., Diversi, R., & Grivel, E. In 2014 22nd European Signal Processing Conference (EUSIPCO), pages 456-460, Sep., 2014.
Iterative approach to estimate the parameters of a TVAR process corrupted by a MA noise [pdf]Paper  abstract   bibtex   
A great deal of interest has been paid to the time-varying autoregressive (TVAR) parameter tracking, but few papers deal with this issue when noisy observations are available. Recently, this problem was addressed for a TVAR process disturbed by an additive zero-mean white noise, by using deterministic regression methods. In this paper, we focus our attention on the case of an additive colored measurement noise modeled by a moving average process. More particularly, we propose to estimate the TVAR parameters by using a variant of the improved least-squares (ILS) methods, initially introduced by Zheng to estimate the AR parameters from a signal embedded in a white noise. Simulation studies illustrate the advantages and the limits of the approach.

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