Tensor-based methods for blind spatial signature estimation in multidimensional sensor arrays

Gomes PR, De Almeida AL, Da Costa JPC, Mota JC, Valle De Lima D, Del Galdo G (2017)

Publication Type: Journal article

Publication year: 2017

Journal

International Journal of Antennas and Propagation Hindawi Publishing Corporation

Book Volume: 2017

Article Number: 1615962

DOI: 10.1155/2017/1615962

Abstract

The estimation of spatial signatures and spatial frequencies is crucial for several practical applications such as radar, sonar, and wireless communications. In this paper, we propose two generalized iterative estimation algorithms to the case in which a multidimensional (R-D) sensor array is used at the receiver. The first tensor-based algorithm is an R-D blind spatial signature estimator that operates in scenarios where the source's covariance matrix is nondiagonal and unknown. The second tensor-based algorithm is formulated for the case in which the sources are uncorrelated and exploits the dual-symmetry of the covariance tensor. Additionally, a new tensor-based formulation is proposed for an L-shaped array configuration. Simulation results show that our proposed schemes outperform the state-of-the-art matrix-based and tensor-based techniques.

Involved external institutions

Universidade Federal do Ceará (UCF) BR Brazil (BR) Universidade de Brasília BR Brazil (BR) Technische Universität Ilmenau DE Germany (DE)

How to cite

APA:

Gomes, P.R., De Almeida, A.L., Da Costa, J.P.C., Mota, J.C., Valle De Lima, D., & Del Galdo, G. (2017). Tensor-based methods for blind spatial signature estimation in multidimensional sensor arrays. International Journal of Antennas and Propagation, 2017. https://doi.org/10.1155/2017/1615962

MLA:

Gomes, Paulo R.B., et al. "Tensor-based methods for blind spatial signature estimation in multidimensional sensor arrays." International Journal of Antennas and Propagation 2017 (2017).

BibTeX: Download