Robust Bounding Ellipsoidal Adaptive Constrained least-squares algorithm and its performance analysis

Abstract

In this paper, the robust Bounding Ellipsoidal Adaptive Constrained least-squares (BEACON) algorithm based on new set-membership error bounds is proposed to improve robustness and steady-state misalignment in impulsive noise environments. The expressions for the steady-state excess mean square error (EMSE) of the proposed robust BEACON are obtained. Simulations on system identification and double-talk scenarios show that the robust BEACON algorithm considerably outperforms the traditional BEACON algorithm in the presence of impulsive noise and the theoretical predictions are in good agreement with simulation results.