[CDS18a] Third-Order Volterra MVDR Beamforming for Non-Gaussian and Potentially Non-Circular Interference Cancellation

Revue Internationale avec comité de lecture : Journal IEEE Transactions on Signal Procesing, vol. 66(18), pp. 4766-4781, 2018, (doi:10.1109/TSP.2018.2860551)

Mots clés: Non-linear, non-Gaussian, non-circular, widely linear, third-order Volterra, interference, MVDR, beamforming, spectrum monitoring, passive listening

Résumé: Linear beamformers are optimal, in a mean square(MS) sense, when the signal of interest (SOI) and observationsare jointly Gaussian and circular. Otherwise, linear beamformers become suboptimal. When the SOI and observations are zeromean, jointly Gaussian and noncircular, optimal beamformers become widely linear (WL). They become nonlinear with a structure depending on the unknown joint probability distribution of the SOI and observations when the latter are jointly nonGaussian,assumption which is very common in radiocommunications. In this context, the paper aims at introducing, for small-scale systems, third-order Volterra minimum variance distortionless response(MVDR) beamformers, for the reception of an SOI, whose waveform is unknown but whose steering vector is known, corrupted by nonGaussian and potentially noncircular interference, omnipresent in practical situations. Properties, performance, complexity,and adaptive implementation of these beamformers in the presence of nonGaussian and potentially noncircular interference are analyzed in this paper. These new beamformers are shown to always improve, in the steady state, the performance of Capon beamformer for nonGaussian/circular interference, whereas some of them improve the performance of the WL MVDR beamformer for nonGaussian/noncircular interference. These new beamformers open new perspectives for spectrummonitoring of nonGaussian signals and for radiocommunication networks using such signals.



@article {
title="{Third-Order Volterra MVDR Beamforming for Non-Gaussian and Potentially Non-Circular Interference Cancellation}",
author="P. Chevalier and J. Delmas and M. Sadok",
journal="IEEE Transactions on Signal Procesing",