Denoising of MST radar data using complex wavelets

This paper discusses the application of complex wavelet transform (CWT) which has significant advantages over real wavelet transform. CWT is a form of discrete wavelet transform, which generates complex coefficients by using a dual tree of wavelet filters to obtain their real and imaginary parts. In this paper we implement Selesnick's idea of dual tree complex wavelet transform where it can be formulated for standard wavelet filters without special filter design. We examine the behavior of 1 dimensional signal and implement the method for the analysis and synthesis of signal in frequency domain. Analysis and synthesis of a signal is performed on a test signal to verify the CWT application on 1D signal. The same is implemented for the MST radar signal. In this paper, CWT with custom thresholding algorithm is proposed for cleaning the spectrum. The proposed algorithm is self-consistent in detecting wind speeds up to a height of 20 km, in contrast to existing methods, which estimates the spectrum manually and failed at higher altitudes.