• DocumentCode
    1288744
  • Title

    MST Radar Signal Processing Using Wavelet-Based Denoising

  • Author

    Thatiparthi, Sreenivasulu Reddy ; Gudheti, Ramachandra Reddy ; Sourirajan, V.

  • Author_Institution
    Dept. of Electr. & Electron. Eng., Sri Venkateswara Univ., Tirupati, India
  • Volume
    6
  • Issue
    4
  • fYear
    2009
  • Firstpage
    752
  • Lastpage
    756
  • Abstract
    Atmospheric signal processing is of interest to many scientists, where there is scope for the development of new and efficient tools for cleaning the spectrum, detection, and estimation of parameters like zonal (U), meridional (V), wind speed (W), etc. This letter deals with a signal processing technique for the estimation of the aforementioned parameters, based on the wavelets, by analyzing the mesosphere-stratosphere-troposphere radar data that are backscattered from the atmosphere at high altitudes and severe weather conditions with low signal-to-noise ratio. The proposed algorithm is self-consistent in detecting wind speeds up to a height of 18 km, in contrast to the existing method which estimates the Doppler manually and fails at higher altitudes. The results have been validated using the Global Positioning System sonde data.
  • Keywords
    Doppler radar; Global Positioning System; atmospheric techniques; mesosphere; parameter estimation; radar signal processing; remote sensing by radar; stratosphere; troposphere; wavelet transforms; Doppler radar; Global Positioning System; MST radar signal processing; atmospheric signal processing; mesosphere-stratosphere-troposphere radar data; parameter detection; parameter estimation; wavelet based denoising; Adaptive denoising; Doppler frequencies; Global Positioning System (GPS) sonde; existing algorithm (EALG); mesosphere–stratosphere–troposphere (MST) radar; proposed algorithm (PALG); wavelet transform;
  • fLanguage
    English
  • Journal_Title
    Geoscience and Remote Sensing Letters, IEEE
  • Publisher
    ieee
  • ISSN
    1545-598X
  • Type

    jour

  • DOI
    10.1109/LGRS.2009.2024556
  • Filename
    5196734