A kernel-based nonlinear blind source separation algorithm with reference and its application in satellite micro-vibration system

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

3 Scopus citations

Abstract

this paper, a kernel-based nonlinear blind source separation algorithm with reference information is proposed to identify the harmonic source signals in satellite micro-vibration system. The kernel feature space with reduced dimension constructed by the proposed algorithm can transform the nonlinear blind source separation in the input space into linear blind source separation. In the linear blind source separation phase, aiming at the weak non-Gaussian characteristic of micro-vibration harmonic sources, a new linear blind source separation objective function with reference information is proposed to ensure the accuracy of source identification. The effective estimated signals of the sources are selected from the linear separated signals according to the spectrum correlation coefficient index. The effectiveness of the proposed algorithm is verified by the satellite cabin structure experiment.

Original languageEnglish
Title of host publicationI2MTC 2020 - International Instrumentation and Measurement Technology Conference, Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781728144603
DOIs
StatePublished - May 2020
Event2020 IEEE International Instrumentation and Measurement Technology Conference, I2MTC 2020 - Dubrovnik, Croatia
Duration: 25 May 202029 May 2020

Publication series

NameI2MTC 2020 - International Instrumentation and Measurement Technology Conference, Proceedings

Conference

Conference2020 IEEE International Instrumentation and Measurement Technology Conference, I2MTC 2020
Country/TerritoryCroatia
CityDubrovnik
Period25/05/2029/05/20

Keywords

  • Kernel feature space
  • Nonlinear blind source separation
  • Reference information

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