Received Signal Parameter Statistics in Random/Uncertain Oceans

Abstract

A Monte Carlo-based method has been developed to estimate parameter statistics for acoustic signals that have propagation through random and uncertain ocean environments. The method uses physics-based models for relevant environmental parameters and utilizes available environmental measurements. Statistical moments and covariance functions of the environmental parameters are used with the Maximum Entropy (Max-Ent) method to construct parameter probability density functions (pdfs). Random but properly correlated realizations of the environment are constructed from the pdfs. An acoustic propagation code is used to propagate acoustic energy through each realization of the environment in a Monte Carlo simulation. From the ensemble of received signals, signal parameters are estimated and the MaxEnt method used to construct signal parameter pdfs at all ranges and depths of interest. The method is demonstrated using 250 Hz acoustic propagation measurements and comprehensive environmental characterization from a 1996 experiment in the Strait of Gibraltar. This is a particularly complicated region dominated by strong tidal fluctuations and internal waves. Pdfs of rms received pressure calculated from the acoustic measurements are compared with simulated pdfs obtained using the Monte Carlo method. The agreement is generally good and the method appears promising