Métodos tensoriais para estimação cega de assinaturas espaciais

Abstract

In this dissertation the problem of spatial signature and direction of arrival estimation in Linear 2L-Shape and Planar arrays is investigated Methods based on tensor decompositions are proposed to treat the problem of estimating blind spatial signatures disregarding the use of training sequences and knowledge of the covariance structure of the sources By assuming that the power of the sources varies between successive time blocks decompositions for tensors of third and fourth orders obtained from spatial and spatio-temporal covariance of the received data in the array are proposed from which iterative algorithms are formulated to estimate spatial signatures of the sources Then greater spatial diversity is achieved by using the Spatial Smoothing in the 2L-Shape and Planar arrays In that case the estimation of the direction of arrival of the sources can not be obtained directly from the formulated algorithms The factorization of the Khatri-Rao product is then incorporated into these algorithms making it possible extracting estimates for the azimuth and elevation angles from matrices obtained using this method A distinguishing feature of the proposed tensor methods is their efficiency to treat the cases where the covariance matrix of the sources is non-diagonal and unknown which generally happens when working with sample data covariances computed from a reduced number of snapshots