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Noise Reduction Algorithm

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A survey: Noise reduction algorithm for underwater signal
Anjali singh1, Selva balan2 and Prof Dr.R S kawitkar 3
M.E. Student, Dept. of Electronics, Sinhgad College of Engineering, Pune, India1
Professor, Dept. of Electronics, Sinhgad College of Engineering, Pune, India3

Abstract
Underwater acoustics signal is the study of the propagation of sound in water and the interaction of the mechanical waves that constitute sound with the water and its boundaries. The water may be in the dam, ocean, a lake or a tank. There are some frequencies affiliated with underwater acoustics are between 10 Hz and 1 MHz .There are some major steps for underwater signal de-noising. The first step deals with signal pre-processing which including amplifying, filtering, …show more content…
The aim of this paper is to develop a de-noising system and evaluate the effect of wavelet de-noising processing for underwater acoustic signals. Noise hampers sonar data collection and related processing of the data to extract information since many of the signals of interest are of short duration and of relatively low energy. Underwater signal transmission is a challenging task since the usable frequency range is limited to low frequency and the transmission of electromagnetic waves is impossible due to its high attenuation …show more content…
Literature review
A noise removal algorithm based on short-time Wiener filtering is described. An analysis of the performance of the filter in terms of processing gain, mean square error, and signal distortion is presented. Noise hampers sonar data collection and related processing of the data to extract information since many of the signals of interest are of short duration and of relatively low energy [1].
The evaluation is performed on a representative real data set of underwater acoustic records. Rationales used to process the proposed evaluation are mean squared error, global signal-to noise ratio (SNR), segmental SNR and mean squared spectral error. These filters are generally designed by a calculation which involves the signal autocorrelation estimation, a difficult task in case of low SNR or presence of non-stationary components. Musical noise is a perceptual phenomenon that occurs when isolated peaks remain in the time-frequency representation after processing with spectral subtraction algorithm [2].
The authors S.S.Murugan, et al [3] studied the real time data collected from the Bay of Bengal at Chennai by implementing Welch, Barlett and Blackman estimation methods and improved the maximum Signal to Noise Ratio to 42-51

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