Weak signal detection based on stochastic resonance

Jun Li Liang, Shu Yuan Yang, Zhi Feng Tang

Research output: Contribution to journalArticlepeer-review

12 Scopus citations

Abstract

In a heavy noise, the method based on Wigner Ville (WV) and Hough transformations has the poor performance of detecting the weak signal. To improve it, this paper analyzes the influence of the Fitz Hugh Nagumo (FHN) model's parameters on its filtering characteristics, and presents a method of detecting weak sinusoid and LFM signals based on FHN model of stochastic resonance. Firstly, the received signal is filtered by FHN model, and transformed by WV and Hough in turns, thus whether a signal is present in noise is determined according to whether there is a line in time-frequency picture. Finally, the validity of this method is well verified by the experiments.

Original languageEnglish
Pages (from-to)1068-1072
Number of pages5
JournalDianzi Yu Xinxi Xuebao/Journal of Electronics and Information Technology
Volume28
Issue number6
StatePublished - Jun 2006
Externally publishedYes

Keywords

  • Hough transform
  • Stochastic resonance
  • Weak signal detection
  • Wigner Ville transform

Fingerprint

Dive into the research topics of 'Weak signal detection based on stochastic resonance'. Together they form a unique fingerprint.

Cite this