Recent studies show that Cohen class bilinear time-frequency distribution methods do not have satisfactory denoising performance when analyzing multi-component LFM signals. This paper has constructed a new adaptive time-frequency filtering factor and has proposed an adaptive time-frequency filtering algorithm based on generalized S-transform. Firstly, the time-frequency distribution is obtained by transforming the time domain signals to time-frequency domain by using generalized S-transform, which is followed by calculating instantaneous frequency based on the phase information from the time-frequency distribution. Secondly, the time-frequency distribution regions occupied by clustered energy of effective signal are identified through time-frequency region extraction method and all time-frequency distribution spectrum out of the regions are removed. Thirdly, a novel TF filtering factor is constructed by the time-frequency concentration characteristic to restrain the random noise components in the regions of effective signal. Finally, the filtered signals are retrieved by using inverse generalized S-transform. Simulation results demonstrate that the proposed filtering algorithm has satisfactory performances for signal denoising which most features of original signal can be remained.
|Title of host publication
|2015 21st International Conference on Automation and Computing: Automation, Computing and Manufacturing for New Economic Growth, ICAC 2015
|Institute of Electrical and Electronics Engineers Inc.
|Published - 30 Oct 2015
|21st International Conference on Automation and Computing: Automation, Computing and Manufacturing for New Economic Growth - University of Strathclyde, Glasgow, United Kingdom
Duration: 11 Sep 2015 → 12 Sep 2015
Conference number: 21
https://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=7301994 (Link to Conference Proceedings)
|21st International Conference on Automation and Computing
|11/09/15 → 12/09/15