A multichannel cross-spectrum density estimator based on canonical correlation analysis

Document Type

Conference Proceeding

Publication Date

10-12-2012

Abstract

In this work, the problem of multichannel cross-spectrum density (MCSD) estimation is studied. Based on a multichannel data model, the classic periodogram based MCSD estimator and the minimum variance (MV) based MCSD estimator are tested for cross-spectrum density estimation. Our major contribution in this work is a canonical correlation analysis (CCA) based MCSD estimator, relying on the inherent maximization arguments of CCA. It is demonstrated through a model based multichannel simulation example that the newly proposed CCA-MCSD estimator is of high frequency resolution as well as good sidelobe suppression properties, and can serve as an excellent candidate for MCSD estimation. © 2012 IEEE.

Identifier

84867192913 (Scopus)

ISBN

[9781467310710]

Publication Title

Proceedings of the IEEE Sensor Array and Multichannel Signal Processing Workshop

External Full Text Location

https://doi.org/10.1109/SAM.2012.6250558

e-ISSN

2151870X

First Page

533

Last Page

536

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