A new method of detecting multi-component LFM signals based on blind signal processing

Qiang Guo, Yajun Li, Changhong Wang

Research output: Contribution to journalArticlepeer-review

4 Scopus citations

Abstract

To effectively detect and recognize multicomponent Linear Frequency-Modulated (LFM) emitter signals, a multi-component LFM emitter signal analysis method based on the complex Independent Component Analysis(ICA) which was combined with the Fractional Fourier Transform(FRFT) was proposed. The idea which was adopted to this method was the time-domain separation and then time-frequency analysis, and in the low SNR cases, the problem which is generally plagued by noised of feature extraction of multi-component LFM signal based on FRFT is overcame. Compared to the traditional method of timefrequency analysis, the computer simulation results show that the proposed method for the multi-component LFM signals separation and feature extraction was better.

Original languageEnglish
Pages (from-to)1976-1982
Number of pages7
JournalJournal of Computers
Volume6
Issue number9
DOIs
StatePublished - 2011
Externally publishedYes

Keywords

  • Feature extraction
  • ICA
  • Multi-component LFM emitter signals
  • Timefrequency analysis

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