AUTOMATED CLASSIFICATION AND DETECTION OF SONAR SIGNALS USING A PATTERN RECOGNITION EXPERT SYSTEM

THE GOAL OF THIS RESEARCH PROJECT IS THE DEVELOPMENT OF A PATTERN RECOGNITION EXPERT SYSTEM FOR AUTOMATED CLASSIFICATION AND DETECTION OF SONAR SIGNALS. THE EXPERT SYSTEM WILL BE COMPOSED OF TWO PARTS: I) FRONT END SIGNAL PROCESSING SYSTEM TO EXTRACT POWER SPECTRUM PARAMETERS, AND II) AN EXPERT SYSTEM WHICH WILL MAKE DECISIONS ON THE POWER SPECTRUM PARAMETERS BASED UPON A RULE-BASED LIBRARY. THE ULTIMATE GOAL OF THIS EFFORT IS AN AUTOMATED SYSTEM WHICH CAN DETECT AND CLASSIFY BOTH ACTIVE AND PASSIVE SONAR SIGNALS IN NOISY ENVIRONMENTS (LESS THAN -10 DB SNR). BASED UPON PRELIMINARY WORK IN THIS AREA, AN EXPERT SYSTEM HAS BEEN PREVIOUSLY DEVELOPED WHICH CAN EFFECTIVELY DETECT NARROWBAND AND BROADBAND SIGNALS IN -20 DB TO -30 DB SNR ENVIRONMENTS. APPLICATION OF ADDITIONAL CLASSIFICATION RULES WILL FURTHER ENHANCE THE EXISTING SYSTEM SO THAT UNIQUE CLASSIFICATION CAPABILITIES CAN BE ACHIEVED IN NOISY ENVIRONMENTS. THE PHASE I PROPOSED RESEARCH WILL BE COMPOSED OF THE FOLLOWING STAGES: I) COMPUTER MODELING OF EXPERT SYSTEM, II) RULE-BASE DEVELOPMENT, III) SYSTEM INTEGRATION AND REAL-TIME TESTING. ONCE THE BASIC PRINCIPLES OF PHASE I HAVE BEEN ESTABLISHED, PHASE II & III EFFORTS WILL INCORPORATE FULL-SCALE DEVELOPMENTAL EFFORTS TOWARDS AN OPERATIONAL SYSTEM.