Abstract: The major target of our research is to design and develop wiener filtering based on Short Time Fractional Fourier Transform for chirp signal enhancement. One of the efficient methods to analyze the chirp signal is fractional Fourier Transform (FRFT). Still, it fails in locating the Fractional Fourier Domain (FRFD) frequency contents which is required in some applications. For that reason in our research, we introduce the Short-Time Fractional Fourier Transform (STFRFT) for chirp signal enhancement. Using the advantage of STFRFT, we plan to design the wiener filtering based on STFRFT. In this study, at first the input signal is split in to two signals such as clean chirp signal and the noisy chirp signal based on the size of the hamming window. After that, multiplying the hamming window function with the frame of the signal is then multiplied with the Fractional Fourier Transform (FRFT). Finally, we apply the wiener filter to remove the noise from the signal. In experimental evaluation, we generate the mono signal model to compare the results of our proposed method.We compare our proposed technique with the wiener filter based on STFT, FFT and FRFT. Here, we obtain the maximum SNR of 30.79 db which is high compare to existing approach.
P. Jaisi Praba and Vinsley Sathianathan, 2016. W-STFRFT: Wiener Filtering in Short-Time Fractional Fourier Domain for Chirp Signal Enhancement. Asian Journal of Information Technology, 15: 4744-4757.