TRACKING ALGORITHM-EXPOITATION OF TOTAL INFERENCE BASE IN SURFACE SHIPS

TO KEEP PACE WITH ADVANCED THREATD, FUTURE COMBAT SYSTEMS MUST TAKE FULL ADVANTAGE OF ALL INFORMATION AVAILABLE IN THE SHIPBOARD SENSORS. THIS STUDY ADDRESES IMPROVEMENTS TO INTEGRATED AUTOMATIC DETECTION AND TRACKING (IADT) SYSTEMS IN TWO AREAS: INCREASING THE BASE OF SENSOR DATA AND EXTENDING THE MULTI-SENSOR CONTROL FUNCTION. CURRENT MULTI-SENSOR INTEGRATION ALGORITHMS WORK WELL IN CLEAR ENVIRONMENTS, THESE "STATISTICAL DISTANCE" ALGORITHMS BREAKDOWN PRIMARILY DUE TO LACK OF INFORMATION. TO EXTEND THE CAPABILITIES OF CURRENT ALGORITHMS, DATA WHICH ARE AVAILABLE BUT NOT TYPICALLY USED WILL BE EXAMINED TO DETERMINE APPLIABILITY IN EXPLOITING DIFFERENCES BETWEEN TARGET, ENVIRONMENT AND INTERFERENCE RETURNS. A GENERALIZED ASSOCIATION AND TRACKING ALGORITHM WILL BE DEVELOPED BASED ON THE STATISTICAL CHARACTERIZATION OF THE ADDITIONAL DATA. THE ALGORITHM AND ITS INPUTS WILL SIMULATED AND EVALUATED TO DETERMINE ITS EFFECTIVENESS IN VARIOUS ENVIRONMENTS. INCREASING USE OF COMPUTERS IN INDIVIDUL SENSORS FOR ADAPTIVE MODE CONTROL PROVIDES ADDITIONAL DATA FOR USE IN MULTI-SENSOR INTEGRATION AND THE NEED FOR NEW MULTI-SENSOR CONTROL PROCEDURES. NEW LOCAL AND IADT CONTROL ARCHITECTURES WILL BE DEVELOPED FOR COMPUTER-CONTROLLED SENSORS. USE OF LOCAL TRACK DATA AND CLUTER\ENVIRONMENT MAP DATA IN THE MULTI-SENSOR INTEGRATION PROCESS WILL BE INVESTIGATED.