This paper investigates the acoustic uncertainty due to hydrographic data error and in turn to determine the necessity of a near real time ocean analysis capability such as the Naval Oceanographic Office's (NAVOCEANO) Modular Ocean Data Assimilation System (MODAS) model in shallow water (such as the Yellow Sea) mine hunting applications using the Navy's Comprehensive Acoustic Simulation System / Gaussian Ray Bundle (CASS/GRAB) model. To simulate hydrographic data uncertainty, Gausiantype errors (produced using the random number generator in MATLAB) with zero mean and three standard deviations (1 m/s, 5 m/s, and 10 m/s) are added to the sound profile. It is found that the acoustic uncertainty depends on the location of the error and sound sources. It is more sensitive to errors in the isothermal structure in the winter than in the layered structure in the summer.

This paper investigates the acoustic uncertainty due to hydrographic data error and in turn to determine the necessity of a near real time ocean analysis capability such as the Naval Oceanographic Office's (NAVOCEANO) Modular Ocean Data Assimilation System (MODAS) model in shallow water (such as the Yellow Sea) mine hunting applications using the Navy's Comprehensive Acoustic Simulation System / Gaussian Ray Bundle (CASS/GRAB) model. To simulate hydrographic data uncertainty, Gausiantype errors (produced using the random number generator in MATLAB) with zero mean and three standard deviations (1 m/s, 5 m/s, and 10 m/s) are added to the sound profile. It is found that the acoustic uncertainty depends on the location of the error and sound sources. It is more sensitive to errors in the isothermal structure in the winter than in the layered structure in the summer.

No abstract