A robust MUSIC estimator for polynomial phase signals in α-stable noise

In this paper, we address the problem of estimation of the parameters of mono and multicomponent polynomial phase signals (PPS) affected by alpha-stable noise using subspace methods. We propose two new estimators: a modified multiple signal classification MUSIC for PPS affected by Gaussian noise, and a modified robust MUSIC algorithm for PPS based on fractional lower-order statistics (FLOS). Simulation results show that the robust MUSIC estimator is able to estimate the values of the phase parameters in impulsive environment hence outperforming the standard estimators.