Abstract

Infrasound propagation depends critically on the temperature and wind velocity profiles at the time of signal propagation. These vary wildly, showing at best qualitative systematic behavior. It follows that any predictions of signal detection capability are necessarily statistical in nature. One approach is to collect a large number of historical temperature and wind velocity profiles, for a specific time and location, and use this as a sample space from which to generate a statistical model for the atmosphere as a propagation medium. To generate a statistical model for the expected transmission loss one must run a propagation model through a sampling of atmospheric profiles sufficient to reproduce the statistical behavior. The sampling is done using an Empirical Orthogonal Function (EOF) decomposition. The advantages of the use of an EOF decomposition will be discussed and examples from transition zone (ranges less than 100 km) and regional (ranges of several hundreds of kilometers) will be presented. Given a model for the turbulent pressure fluctuation levels near a receiving array, signal detection probability functions can be estimated.

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