Title of Paper:A robust correntropy based subspace tracking algorithm in impulsive noise environments

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Date of Publication:2017-03-01

Journal:DIGITAL SIGNAL PROCESSING

Included Journals:SCIE、EI

Volume:62

Page Number:168-175

ISSN No.:1051-2004

Key Words:Impulsive noise; Maximum correntropy criterion; Projection approximation subspace tracking; Variable forgetting factor

Abstract:The maximum correntropy criterion (MCC) demonstrates the inherent robustness to outliers in adaptive filtering. By employing the MCC based cost function in projection approximation subspace tracking (PAST) algorithm, the MCC-PAST algorithm is deduced and utilized for the subspace tracking under impulsive noise environments. To handle the fast varying subspaces circumstances, the variable forgetting factor (VFF) technique is developed and incorporated into the MCC-PAST algorithm. To assess the robustness of the proposed MCC-PAST with VFF algorithm, S alpha S processes are employed to comprehensively model different scenarios of impulsive noises. The simulation results show the proposed MCC-PAST algorithm with VFF performs better than the other two PAST algorithms developed for subspace tracking in impulsive noise environments, namely, the robust PAST algorithm and the robust Kalman filter based algorithm with variable number of measurements (KFVNM), especially when the noise is extremely impulsive or the GSNR (generalized signal to noise ratio) is relatively low. (C) 2016 Elsevier Inc. All rights reserved.