Generalized cauchy distribution based robust estimation

The generalized Cauchy distribution (GCD) family has the property that its pdf has closed form for the whole family and also has algebraic tails which makes it suitable to model many impulsive processes in real life. In this paper we propose a robust M-type estimator based on the pdf of the GCD family. Robustness and properties of the new statistics are analyzed and it is noticed that this estimator provide desired characteristics in robust signal processing applications involving non-Gaussian heavy-tailed models. Simulations of the filtering method are performed to evaluate and compare the proposed filtering structure performance to other classic and robust estimators.