Accession Number : AD0758735

Title :   Predicting Deep Ocean Sound Speed by Stochastic Models.

Descriptive Note : Research rept. Apr 71-Oct 72,

Corporate Author : NAVAL UNDERSEA CENTER SAN DIEGO CALIF

Personal Author(s) : Frye,H. W.

Report Date : MAR 1973

Pagination or Media Count : 32

Abstract : Archived hydrographic cast data were the basis of a stepwise regression analysis to develop a stochastic model of sound-speed distribution below a depth of 500 m in the Gulf of Alaska. A simple polynomial expression in three variables was found to fit the empirical data with a standard deviation of 0.51 m/sec and a percent variance explained by regression of 98.6 percent. Various comparisons of sound predictions (from the model) with observed data indicated close agreement. The accuracy and compactness of the model make it ideally suited for various applications in sonar prediction, as well as for rapid information retrieval. The method is recommended for employment in other geographical areas of interest to the Navy. (Author)

Descriptors :   (*UNDERWATER SOUND, MATHEMATICAL PREDICTION), (*SONAR SIGNALS, VELOCITY), STOCHASTIC PROCESSES, REGRESSION ANALYSIS, DEEP WATER, INFORMATION RETRIEVAL, ALASKA, PACIFIC OCEAN

Subject Categories : Physical and Dynamic Oceanography
      Acoustic Detection and Detectors
      Acoustics

Distribution Statement : APPROVED FOR PUBLIC RELEASE