Abstract
The overall goal of our research is to incorporate knowledge of variability and uncertainty in received passive sonar signals into the signal processing. As part of this goal, we need to better understand the sources of this variability. It is well known that wave motion on the ocean surface can introduce significant effects on undersea acoustic signals. This talk focuses on predicting the impact of rough ocean surfaces on the variability of the received signal. An acoustics propagation code, range-dependent acoustic model (RAM) rough surface fine coarse (RRSFC), is utilized to simulate environments with flat and rough ocean surfaces. To explore the effects of random rough surfaces, a Monte Carlo method is applied to yield environment realizations with varying rough surfaces. From these simulations, probability density functions are generated and are compared with amplitude figures from environments with a flat surface in order to distinguish any overall effect on a received signal. [Work supported by ONR Undersea Signal Processing Code 321US.]
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