Metodos tensoriais para estimação cega de assinaturas espaciais em arranjos multidimensionais de sensores.

Abstract

Spatial signatures and spatial frequencies estimation problem has an important role in array signal processing that culminates in practical applications such as radar, sonar and wireless communication. In this paper, this problem is generalized to the case in which a multidimensional (R-D) sensor array is used in the receiver. Initially, covariance tensors are formulated to sources with different covariance structures and two iterative algorithms for blind spatial signatures estimation are derived. The first tensor-based proposed algorithm is a generalization for the R-D case where the source’s covariance matrix is non-diagonal and unknown, while the second tensor-based proposed algorithm is formulated for the case in which the sources are uncorrelated and exploits the dual-symmetry of the covariance tensor. Simulation results show that our proposed schemes outperform the state-of-the-art matrix-based and tensor-based ESPRIT.