Optimal joint azimuth-elevation and signal-array response estimation using parallel factor analysis

Author

Bro, R. ; Sidiropoulos, N.D. ; Giannakis, G.B.

Author_Institution

Chemometrics Group, Food Tech., R. Veterinary & Agric. Univ., Frederiksberg, Denmark

Volume

2

fYear

1998

fDate

1-4 Nov. 1998

Firstpage

1594

Abstract

We consider deterministic joint azimuth-elevation, signal, and array response estimation, and establish a direct link to parallel factor (PARAFAC) analysis, a tool with roots in linear algebra for multi-way arrays. This link affords a powerful identifiability result, plus the opportunity to tap on and extend the available expertise for fitting the PARAFAC model, to derive a deterministic (least squares) joint estimation algorithm, also applicable to multiple-parameter/multiple-invariance ESPRIT subspace fitting problems. These and other issues are demonstrated in pertinent simulation experiments.

Keywords

array signal processing; deterministic algorithms; least squares approximations; linear algebra; optimisation; parameter estimation; ESPRIT subspace fitting problems; PARAFAC model; deterministic joint estimation algorithm; identifiability result; least squares estimation algorithm; linear algebra; multi-way arrays; multiple-parameter/multiple-invariance problems; optimal joint azimuth-elevation estimation; parallel factor analysis; signal-array response estimation; simulation experiments; Azimuth; Data models; Electric variables measurement; Food technology; Least squares methods; Linear algebra; Narrowband; Noise measurement; Sensor arrays; Signal analysis;

fLanguage

English

Publisher

ieee

Conference_Titel

Signals, Systems & Computers, 1998. Conference Record of the Thirty-Second Asilomar Conference on

Conference_Location

Pacific Grove, CA, USA

ISSN

1058-6393

Print_ISBN

0-7803-5148-7

Type

conf

DOI

10.1109/ACSSC.1998.751595

Filename

751595