The U.S. Navy's complex passive acoustic surveillance and ASW systems depend significantly on an acoustic operator/analyst's ability to quickly recognize potential targets of interest, analyze the parameters and characteristics of the acoustic data presented to the operator, evaluate the meaning of the parametric data and classify the target. With the advent of numerous friendly and threat and neutral forces operating in the world, the task of consistently classifying numerous acoustic targets has become extremely difficult. Acoustic Intelligence data on hundreds of target types is impossible to memorize or quickly reference. Operators need a passive acoustic data classification tactical decision aid which can help them reference important parametric data and assist in accurate and timely classification of the targets. This proposed effort will research and develop a design for a Passive Acoustic Classification (Computer) System with a robust acoustic parameters data base and algorithms to query the data base, score the results of data base matches using math algorithms, and interact with the operator/analyst in reaching timely and accurate target classification.
