Incorporating environmental variability into received signal statistics

Abstract

We have developed a Monte Carlo-based method for estimating the variability of acoustic signal parameters caused by uncertain ocean environments. The method begins with a physics-based model for the environmental properties and uses the maximum entropy (MaxEnt) method to construct probability density functions (pdf’s) describing the measured deviations from the model mean. Random realizations of environmental variability, with proper depth correlation, are constructed from the pdf’s and added to the mean model parameters. A parabolic equation code (ram) is used to propagate acoustic energy through each realization of the environment. Fourier synthesis is used to recreate the arrival structure. The method is demonstrated using measurements from the Strait of Gibraltar, which is a particularly complicated region dominated by strong tidal fluctuations and internal waves. During 1996, an international group carried out the Strait of Gibraltar Acoustic Monitoring Experiment (SGAME), in which detailed environmental and 250-Hz acoustic data were collected. Here, pdf’s of the received signal level are compared with results of the Monte Carlo method to demonstrate performance. [Gibraltar data and SVP model provided by Chris Tiemann (ARL:UT) and Peter Worcester (SIO). Work supported by ONR Undersea Signal Processing.]