Empirical mode decomposition of Atmospheric radar signals

Vol.1 No. 4

Year: 2011

Issue: June-August

Title: Empirical mode decomposition of Atmospheric radar signals 

Author Name: Padmaja Nimmagadda, S. Varadarajan, G. Madhavi Latha 

Synopsis: 

In this paper, comparison study of wavelet transforms and Empirical mode decomposition (EMD) was performed for two sets of atmospheric radar data. Wavelets and EMD has been applied to the time series data obtained from the mesosphere-stratosphere-troposphere (MST) region near Gadanki, Tirupati.  Wavelet analysis is one of the most important methods for removing noise and extracting signal from any data. The de-noising application of the wavelets has been used in spectrum cleaning of the atmospheric signals. EMD is a numerical sifting process to decompose a signal into its fundamental intrinsic oscillatory modes, namely intrinsic mode functions (IMFs).  A series of IMFs can be obtained after the application of EMD. The Algorithm is developed and tested using Matlab. Analysis has brought out some of the characteristic features such as Doppler width, SNR of the atmospheric signals. The results showed that the proposed algorithm is efficient for dealing non-linear and non- stationary signals contaminated with noise.  SNR using wavelets and EMD has been compared and plotted for validation of the proposed algorithm. EMD is found to be effective in removing the noise embedded in radar echoes.