Validation of statistical estimation of transmission loss in the presence of geoacoustic inversion uncertainty

Abstract

Often the ocean acoustic environment is not well known and sonar performance prediction will be affected by this uncertainty. Here, a method for estimating transmission loss (TL) is proposed which incorporates these environmental uncertainties. Specifically, we derive an approach for the statistical estimation of TL based on the posterior probability density of environmental parameters obtained from the geoacoustic inversion process. First, a Markov chain Monte Carlo procedure is employed in the inversion process to sample the posterior probability density of the geoacoustic parameters. Then, these sampled parameters are mapped to the transmission loss domain where a full multidimensional probability distribution of TL as a function of range and depth is obtained. In addition, TL is also characterized by its summary statistics including the median, percentiles, and correlation coefficients. The approach is illustrated using a data set obtained from the ASIAEX 2001 East China Sea experiment. Based on the geoacoustic inversion results, the predicted TL and its variability are estimated and then compared with the measured TL. In general, there is a good agreement with the percentage of observed number of data points inside the credibility interval.