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Atmospheric Signal Processing using Wavelets and HHT

N. Padmaja, Srenivas Varadarajan

Open publisher page 3 citations

Abstract

The HHT (Hilbert-Huang transform) and wavelet transform are both signal processing methods. This paper is based on comparing HHT and Wavelet transform applied to Radar signals. HHT can be used for processing nonstationary and nonlinear signals. It is one of the time-frequency analysis techniques which consists of Empirical Mode Decomposition (EMD) and instantaneous frequency solution. EMD is a numerical sifting process to decompose a signal into its fundamental intrinsic oscillatory modes, namely intrinsic mode functions (IMFs). In this paper wavelets and EMD has been applied to the time series data obtained from the mesosphere-stratospheretroposphere (MST) region near Gadanki, Tirupati. The Algorithm is developed and tested using Matlab. Analysis has brought out improvement in some of the characteristic features like SNR, Doppler width of the atmospheric signals. SNR using wavelets and EMD has been compared and plotted for validation.

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What this paper is about

The HHT (Hilbert-Huang transform) and wavelet transform are both signal processing methods. This paper is based on comparing HHT and Wavelet transform applied to Radar signals. HHT can be used for processing nonstationary and nonlinear signals. It is one of the time-frequency analysis techniques which consists of Empirical Mode Decomposition (EMD) and instantaneous frequency solution. EMD is a numerical sifting process to decompose a signal into its fundamental intrinsic oscillatory modes, namely intrinsic mode functions (IMFs). In this paper wavelets and EMD has been applied to the time series data obtained from the mesosphere-stratospheretroposphere (MST) region near Gadanki, Tirupati. The Algorithm is developed and tested using Matlab. Analysis has brought out improvement in some of the characteristic features like SNR, Doppler width of the atmospheric signals. SNR using wavelets and EMD has been compared and plotted for validation.

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Available abstract

The HHT (Hilbert-Huang transform) and wavelet transform are both signal processing methods. This paper is based on comparing HHT and Wavelet transform applied to Radar signals. HHT can be used for processing nonstationary and nonlinear signals. It is one of the time-frequency analysis techniques which consists of Empirical Mode Decomposition (EMD) and instantaneous frequency solution. EMD is a numerical sifting process to decompose a signal into its fundamental intrinsic oscillatory modes, namely intrinsic mode functions (IMFs). In this paper wavelets and EMD has been applied to the time series data obtained from the mesosphere-stratospheretroposphere (MST) region near Gadanki, Tirupati. The Algorithm is developed and tested using Matlab. Analysis has brought out improvement in some of the characteristic features like SNR, Doppler width of the atmospheric signals. SNR using wavelets and EMD has been compared and plotted for validation.

Key concepts: Hilbert–Huang transform, Wavelet, SIGNAL (programming language), Wavelet transform, Signal processing, Instantaneous phase, Algorithm, Time–frequency analysis

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