Validation of Webster ambient noise model for real data in tropical littoral water

Ambient noise has a profound impact on the performance of underwater systems, specifically in the tropical littoral waters. The site specific nature presents its unique challenge and efforts at mitigation have not been effective. Synthetic ambient noise generation has emerged as an effective Modeling and Simulation (M&S) tool for Signal to Noise Ratio (SNR) enhancement. Webster model of random number generation with implicit ambient noise power spectral density structure has been reported to simulate synthetic noise. The power spectral estimation of ambient noise in the tropical littoral waters has always been sub-optimal due to random fluctuations. This work presents the frequency sampling method of FIR filter design for the accurate generation of colored spectra for improved tropical littoral ambient noise generation using the Webster model. This effort focuses on the efficiency of Webster model with expected Power Spectral Density (PSD), kurtosis and the Probability Distribution Function (PDF). The synthetic data generated using the proposed model has been validated using real data recorded by fixed sensors off the west coast of India with a mix of dominance of shipping and wind noise. The recording site has a unique combination of a port being close by, to incorporate dominance of shipping noise in the calm months and the wind noise dominating the spectrum during rough weather condition.