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

Xiaoli Wang, Hongya Ge

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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.

Original languageEnglish (US)
Title of host publication2012 IEEE 7th Sensor Array and Multichannel Signal Processing Workshop, SAM 2012
Pages533-536
Number of pages4
DOIs
StatePublished - Oct 12 2012
Event2012 IEEE 7th Sensor Array and Multichannel Signal Processing Workshop, SAM 2012 - Hoboken, NJ, United States
Duration: Jun 17 2012Jun 20 2012

Publication series

NameProceedings of the IEEE Sensor Array and Multichannel Signal Processing Workshop
ISSN (Electronic)2151-870X

Other

Other2012 IEEE 7th Sensor Array and Multichannel Signal Processing Workshop, SAM 2012
CountryUnited States
CityHoboken, NJ
Period6/17/126/20/12

All Science Journal Classification (ASJC) codes

  • Signal Processing
  • Control and Systems Engineering
  • Electrical and Electronic Engineering

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