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MST Radar Signal Processing with Fast Approximate Fourier Transform Using DWT


Affiliations
1 Department of ECE, S V Engineering College for Women, Tirupati, India
2 Department of ECE, S V University College of Engineering, Tirupati, India
     

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Discrete Wavelet Transform (DWT), being non-redundant is a very powerful tool for many signal processing applications. This paper uses its advantages to estimate the power spectral density of a non-stationary signal with help of Fast Approximate Fourier Transform (FAFT) in wavelet domain itself. For that, here rather than computing the DFT from the time domain using FFT algorithm, we will first transform the signal into the wavelet domain by using DWT, then calculate the FFT, and finally go to the Fourier domain without going back to the signal domain. Analysis, power spectrum estimation and synthesis of a signal are performed on a test signal to verify the Fast Approximate Fourier Transform application on 1D signal. The same is implemented for the MST radar signal. In this paper, the Fast Approximate Fourier Transform using Discrete Wavelet Transform algorithm is proposed for cleaning the estimated spectrum. 


Keywords

DWT, FAFT, Denoising.
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  • MST Radar Signal Processing with Fast Approximate Fourier Transform Using DWT

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Authors

C. Madhu
Department of ECE, S V Engineering College for Women, Tirupati, India
T. Sreenivasulu Reddy
Department of ECE, S V University College of Engineering, Tirupati, India

Abstract


Discrete Wavelet Transform (DWT), being non-redundant is a very powerful tool for many signal processing applications. This paper uses its advantages to estimate the power spectral density of a non-stationary signal with help of Fast Approximate Fourier Transform (FAFT) in wavelet domain itself. For that, here rather than computing the DFT from the time domain using FFT algorithm, we will first transform the signal into the wavelet domain by using DWT, then calculate the FFT, and finally go to the Fourier domain without going back to the signal domain. Analysis, power spectrum estimation and synthesis of a signal are performed on a test signal to verify the Fast Approximate Fourier Transform application on 1D signal. The same is implemented for the MST radar signal. In this paper, the Fast Approximate Fourier Transform using Discrete Wavelet Transform algorithm is proposed for cleaning the estimated spectrum. 


Keywords


DWT, FAFT, Denoising.