Robust recursive spectral estimation based on AR model excited by a t-distribution process

Abstract

In this paper a new robust spectral estimation method based on an AR model is proposed. The optimal coefficient is selected by assuming that the excitation signal is t-distribution t(/spl alpha/) with /spl alpha/ degrees of freedom. The calculation is done by using a recursive algorithm. When /spl alpha/=/spl infin/, we get the RLS method. Simulation results show that the obtained estimates using the proposed method with small /spl alpha/ are more efficient, the standard deviation (SD) of the estimation results are smaller, and more accurate than that with large /spl alpha/. The proposed estimator with small /spl alpha/ is more efficient and more accurate then the recursive method based on Huber's M-estimate.<>