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Application of empirical mode decomposition for denoising and ground clutter removal on weather radar signals

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  • Ramyakrishna Enugonda
  • V K Anandan
  • Basudeb Ghosh

Abstract

Proper detection and estimation of signal and noise power measurements are important to generate the best quality of meteorological data products such as Reflectivity, Velocity and Spectrum width. In order to obtain the best quality radar products, it is desirable to compute meteorological parameters by estimating noise power and removal of ground clutter. This paper attempts to study the Empirical Mode Decomposition (EMD) denoising techniques on weather radar signals in the presence of noise and ground clutter. Different methods of EMD based denoising techniques have been considered and applied to the weather signals to check the best performance of the denoising and clutter removal technique. The limitations of these methods are brought out through simulation analysis. To overcome these limitations, this paper proposes a new method for denoising and clutter removal in weather signals. This method is a modified version of the correlation-based EMD Interval Threshold (IT) measurements. Moments have been estimated from these techniques and compared with conventional methods like Pulse pair techniques.

Suggested Citation

  • Ramyakrishna Enugonda & V K Anandan & Basudeb Ghosh, 2023. "Application of empirical mode decomposition for denoising and ground clutter removal on weather radar signals," Journal of Electromagnetic Waves and Applications, Taylor & Francis Journals, vol. 37(10-12), pages 966-998, August.
    • Handle: RePEc:taf:tewaxx:v:37:y:2023:i:10-12:p:966-998
    DOI: 10.1080/09205071.2023.2218044
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