Abstract
Underwater acoustics has made significant strides over the last century, which finds applications over a wide range from basic bathymetry study to high-end research extensions. The acoustic propagation in underwater is typically governed by physical properties of the underwater channel, such as temperature, pressure, and salinity. The seasonal fluctuations in the physical properties of the tropical region manifest as thermal stratification. The random thermal stratification has a significant impact on the Sound Speed Profile (SSP), thereby distorting the received echoes from the surface and the bottom. The site-specific behavior in the tropical region makes it an interesting research problem to investigate the correlation of the surface parameters like temperature with the surface and bottom reflection due to variations in the SSP. In this work, we attempt to present underwater channel characteristics of the tropical freshwater lake system at Khadakwasla (18.43° N, 73.76° E), located in the municipal limits of Pune city in India. The temperature gradient along the water column is computed using the one-dimensional Freshwater Lake Model (FLake) to derive the SSP using Medwin relation. The statistical analysis of the sound speed fluctuations resulted due to seasonal variation in the water temperature is presented using the Kolmogorov–Smirnov (KS) Goodness-of-Fit test is used to find a close Probability Density Function (pdf) match for the surface and the bottom path impulse response. The results indicate a good match of the surface and bottom path impulse response with Weibull distribution with a high confidence level. Such characterization can facilitate the design of adaptive algorithms to minimize the underwater channel impact based on a precise estimate of the channel impulse response.
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Sadalage, J.A., Das, A., Joshi, Y. (2019). Statistical Characterization of an Underwater Channel in a Tropical Shallow Freshwater Lake System. In: Iyer, B., Nalbalwar, S., Pathak, N. (eds) Computing, Communication and Signal Processing . Advances in Intelligent Systems and Computing, vol 810. Springer, Singapore. https://doi.org/10.1007/978-981-13-1513-8_73
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DOI: https://doi.org/10.1007/978-981-13-1513-8_73
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