Machine Assisted Expert Anti-Submarine Warfare (ASW) Passive Acoustic Classification Computer System, Using Fuzzy Conditioned Dempster Shafer Algori

Period of Performance: 06/01/1995 - 06/01/1997


Phase 2 SBIR

Recipient Firm

Summit Research Corp.
1 West Deer Park Drive
Gaithersburg, MD 20877
Principal Investigator

Research Topics


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 o 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 proposal effort will research, design, develop, test and implement an expert-based Passive Acoustic Classification System (PACS), incorporating unique acoustic signature features extraction algorithms, ACXINT Specialist-developed Target Characteristics Data Base, use of SRC/Unisys-developed Fussy-Conditioned Dempster Shafer Classification Reasoning algorithms; Machine-assisted PACS MMI routines to optimize operator/algorithms-generated input data characterization; and FCDS algorithms-based data base Query, Match, Score and classification code/algorithms, migrated to IUSS-standard work station environment.