文章基本信息

标题：Signal Processing of Radar Echoes Using Wavelets and Hilbert Huang Transform
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作者：N. Padmaja ; S. Varadarajan ; R. Swathi 等
期刊名称：Signal & Image Processing : An International Journal (SIPIJ)
印刷版ISSN：2229-3922
电子版ISSN：0976-710X
出版年度：2011
卷号：2
期号：3
页码：101
出版社：Academy & Industry Research Collaboration Center (AIRCC)
摘要：Atmospheric Radar Signal Processing is one field of Signal Processing where there is a lot of scope fordevelopment of new and efficient tools for spectrum cleaning, detection and estimation of desiredparameters. The wavelet transform and HHT (Hilbert-Huang transform) are both signal processingmethods. This paper is based on comparing HHT and Wavelet transform applied to Radar signals. Waveletanalysis is one of the most important methods for removing noise and extracting signal from any data. Thede-noising application of the wavelets has been used in spectrum cleaning of the atmospheric radarsignals. HHT can be used for processing non-stationary and nonlinear signals. HHT is one of the timefrequencyanalysis techniques which consists of two parts: Empirical Mode Decomposition (EMD) andinstantaneous frequency solution. EMD is a numerical sifting process to decompose a signal into itsfundamental intrinsic oscillatory modes, namely intrinsic mode functions (IMFs). A series of IMFs can beobtained after the application of EMD. In this paper wavelets and EMD has been applied to the time seriesdata obtained from the mesosphere-stratosphere-troposphere (MST) region near Gadanki, Tirupati for 6beam directions. The Algorithm is developed and tested using Matlab. Moments were estimated andanalysis has brought out improvement in some of the characteristic features like SNR, Doppler width,Noise power of the atmospheric signals. The results showed that the proposed algorithm is efficient fordealing non-linear and non- stationary signals contaminated with noise. The results were compared usingADP (Atmospheric Data Processor) and plotted for validation of the proposed algorithm.
关键词：Hilbert-Huang Transformation (HHT); Empirical Mode Decomposition (EMD); Intrinsic mode;Functions (IMF); Wavelets; Radar Signals.