Open AccessSource separation and localisation via tensor decomposition for distributed arrays
Author(s) -
Cheng Yuanbing,
He Yapeng
Publication year - 2019
Publication title -
the journal of engineering
Language(s) - English
Resource type - Journals
ISSN - 2051-3305
DOI - 10.1049/joe.2019.0045
Subject(s) - tensor (intrinsic definition) , matrix (chemical analysis) , manifold (fluid mechanics) , signal (programming language) , power (physics) , algorithm , blind signal separation , channel (broadcasting) , source separation , matrix decomposition , computer science , plane (geometry) , time domain , topology (electrical circuits) , mathematics , physics , geometry , materials science , telecommunications , engineering , combinatorics , eigenvalues and eigenvectors , mechanical engineering , quantum mechanics , computer vision , programming language , composite material
This study focuses on the problem of power spectra separation and localisation of multiple sources using distributed arrays. First, the array structure and signal model are discussed. By cross‐correlating the multi‐channel received signals in time‐domain, a third tensor is constructed. Then, utilising the multi‐dimensional characteristic, the tensor is decomposed to separate the array manifold matrix and the power spectra matrix through alternating least square (ALS) method. Finally, the sources are located using the relative x ‐ y plane relationship between the distributed arrays and the direction of arrival (DOA), which can be estimated by spectrum analysis of each column of the array manifold matrix. The effectiveness and superiority of the proposed method is demonstrated by simulation results.