Parallel factor analysis in sensor array processing

Author

Sidiropoulos, Nicholas D. ; Bro, Rasmus ; Giannakis, Georgios B.

Author_Institution

Dept. of Electr. Eng., Virginia Univ., Charlottesville, VA, USA

Volume

48

Issue

8

fYear

2000

fDate

8/1/2000 12:00:00 AM

Firstpage

2377

Lastpage

2388

Abstract

This paper links multiple invariance sensor array processing (MI-SAP) to parallel factor (PARAFAC) analysis, which is a tool rooted in psychometrics and chemometrics. PARAFAC is a common name for low-rank decomposition of three- and higher way arrays. This link facilitates the derivation of powerful identifiability results for MI-SAP, shows that the uniqueness of single- and multiple-invariance ESPRIT stems from uniqueness of low-rank decomposition of three-way arrays, and allows tapping on the available expertise for fitting the PARAFAC model. The results are applicable to both data-domain and subspace MI-SAP formulations. The paper also includes a constructive uniqueness proof for a special PARAFAC model

Keywords

array signal processing; direction-of-arrival estimation; identification; matrix algebra; parallel processing; PARAFAC; PARAFAC model; chemometrics; data-domain; identifiability results; low-rank decomposition; multiple invariance sensor array processing; multiple-invariance ESPRIT; parallel factor analysis; psychometrics; signal-source matrix; single-invariance ESPRIT; subspace MI-SAP formulations; Array signal processing; Azimuth; Calibration; Direction of arrival estimation; Fitting; Interference suppression; Psychometric testing; Radar; Sensor arrays; Wireless communication;

fLanguage

English

Journal_Title

Signal Processing, IEEE Transactions on

Publisher

ieee

ISSN

1053-587X

Type

jour

DOI

10.1109/78.852018

Filename

852018