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

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(α) with α degrees of freedom. The calculation is done by using a recursive algorithm. When α=∞, we get the RLS method. Simulation results show that the obtained estimates using the proposed method with small α are more efficient, the standard deviation (SD) of the estimation results are smaller, and more accurate than that with large α. The proposed estimator with small α is more efficient and more accurate then the recursive method based on Huber´s M-estimate