Signal to noise ratio improvement using wavelet and frequency domain based processing
Hippenstiel, Ralph Dieter
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This work investigates the use of wavelet and FFT based decompositions to improve the signal to noise ratio of noisy signals. In their respective transform domains, median filtering or predictive filtering is employed. Prior to the decompositions a short time domain median filter is used. As a benchmark, only a median time domain filter (order 3) is used and for part of the work the pre-filtering is disabled. Three test signals are used: two frequency chirped signals and a Barker coded BPSK signal. The most effective processing sequence for the chirp signals is median filtering, followed by FFT processing, which in turn, is followed by median filtering of the FFT transform coefficients. For the BPSK signal, the time domain median filter provided the best results.
NPS Report NumberNPS-EC-02-003
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