A Comparative Analysis of the Latest Statistical Characterization Trends of Narrowband & Broadband Frequency Spectrum of Deep Sea Ambient Noise Using Monte Carlo Simulation Method

Ocean seems to be silent but actually it is not so. It is always enriched with a background noise known as ambient noise caused by wind, heat, turbulence and some other activities and natural phenomenon. This noise poses considerable hindrances in undersea acoustic communication which is so essential for Oceanographic Monitoring. Oceanographic monitoring covers numerous undersea applications like oceanographic data collection, pollution monitoring, offshore undersea exploration, detect climate changes, seismic monitoring, disaster prevention etc. Exploring the latest statistical characterization trends of Indian Ocean ambient noise in highly spatiotemporal sea environment, we put forward a different approach based on Monte-Carlo simulation method to explore, analyze and verify the empirical data / observations of deep sea ambient noise against its well-known standard Gaussian model in both narrowband and broadband frequency spectrums. Results of variances reveal that the actual ambient noise observations are in very close agreement with the predicted standard Gaussian model in most of the selected broadband frequency spectrums except the narrowband frequency spectrum in which the data summary statistics is numerically found to be non-symmetric. This exception in results has a profound impact on the understanding and behavioral modeling of deep sea ambient noise which is to be analyzed specifically in the narrowband frequency spectrum.