A MINIMUM VARIANCE DISTORTIONLESS RESPONSE SPECTRAL ESTIMATOR WITH KRONECKER PRODUCT FILTERS

Xianrui Wang, Jacob Benesty, Gongping Huang, Jingdong Chen

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

5 Scopus citations

Abstract

Spectral estimation is of significant practical importance in a wide range of applications. This paper proposes a minimum variance distortionless response (MVDR) method for spectral estimation based on the Kronecker product. Taking advantage of the particular structure of the Fourier vector, we decompose it as a Kronecker product of two shorter vectors. Then, we design the spectral estimation filters under the same structure, i.e., as a Kronecker product of two filters. Consequently, the conventional MVDR spectrum problem is transformed to one of estimating two filters of much shorter lengths. Since it has much fewer parameters to estimate, the proposed method is able to achieve better performance than its conventional counterpart, particularly when the number of available signal samples is small. Also presented in this paper is the generalization to the estimation of the cross-spectrum and coherence function.

Original languageEnglish
Title of host publication30th European Signal Processing Conference, EUSIPCO 2022 - Proceedings
PublisherEuropean Signal Processing Conference, EUSIPCO
Pages2261-2265
Number of pages5
ISBN (Electronic)9789082797091
StatePublished - 2022
Event30th European Signal Processing Conference, EUSIPCO 2022 - Belgrade, Serbia
Duration: 29 Aug 20222 Sep 2022

Publication series

NameEuropean Signal Processing Conference
Volume2022-August
ISSN (Print)2219-5491

Conference

Conference30th European Signal Processing Conference, EUSIPCO 2022
Country/TerritorySerbia
CityBelgrade
Period29/08/222/09/22

Keywords

  • coherence function
  • cross-spectrum
  • Kronecker product
  • minimum variance distortionless response (MVDR) filter
  • Spectral estimation

Fingerprint

Dive into the research topics of 'A MINIMUM VARIANCE DISTORTIONLESS RESPONSE SPECTRAL ESTIMATOR WITH KRONECKER PRODUCT FILTERS'. Together they form a unique fingerprint.

Cite this