A time series model for the stochastic process associated with acoustic measurement systems.

This paper describes a technique which can be used to model the fluctuations or Stochastic processes associated with the output of acoustic measurement systems. At-sea data was utilized and successfully modeled. In general, the preliminary results show that the fluctuations fall into a general class of time series referred to as an ARIMA (Autoregressive Integrated Moving Average) process. High Signal-to-Noise (S/N) cases were modeled as second order difference equations with an associated second order moving average process.