Multilinear direction finding for sensor-array with multiple scales of invariance

Author

Miron, Sebastian ; Yang Song ; Brie, David ; Wong, Kainam Thomas

Author_Institution

Centre de Rech. en Autom. de Nancy, Univ. de Lorraine, Vandoeuvre, France

Volume

51

Issue

3

fYear

2015

fDate

7/1/2015 12:00:00 AM

Firstpage

2057

Lastpage

2070

Abstract

In this paper, we introduce a novel direction-finding algorithm for a multiscale sensor array, that is, an array presenting multiple scales of spatial invariance.We show that the collected data can be represented as a Candecomp/Parafac model for which we analyze the identifiability properties. A two-stage algorithm for direction-of-arrival estimation with such an array is also proposed. This approach generalizes the results given in [1] to an array that presents an arbitrary number of spatial invariances.We illustrate, on two particular array geometries, that our method outperforms, in some difficult scenarios, the ESPRIT-based approach introduced in [2], the ESPRIT-MUSIC of [3], and the tensor-ESPRIT of [4].

Keywords

array signal processing; correlation methods; direction-of-arrival estimation; estimation theory; geometry; research initiatives; sensor fusion; signal classification; tensors; Candecomp-Parafac model; ESPRIT-MUSIC approach; cross-correlated source; data collection; direction-finding algorithm; direction-of-arrival estimation; geometry; multilinear direction finding; multiscale sensor array; spatial invariance; spatial smoothing procedure; tensor-ESPRIT approach; Arrays; Data models; Direction-of-arrival estimation; Estimation; Mathematical model; Minimization; Optimization;

fLanguage

English

Journal_Title

Aerospace and Electronic Systems, IEEE Transactions on

Publisher

ieee

ISSN

0018-9251

Type

jour

DOI

10.1109/TAES.2015.130576

Filename

7272852