Network Level Association and Fusion of Kinematic and Attribute Information
Final rept. 1 Oct 2006-30 Sep 2010
CONNECTICUT UNIV STORRS DEPT OF ELECTRICAL ENGINEERING
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This work investigates the various criteria for track-to-track associationfusion T2TAF likelihood ratios and distance criteria. Procedures to obtain the quantities needed by the LR criterion from the limited information available from the real world communication networks are developed. Algorithms for T2TAF with heterogeneous sensors and investigation of several assignment algorithms for the T2TA problem are carried out. Procedures for simultaneous handling of continuous valued kinematic and feature states and discrete valued ones attributeclassification for an integrated approach to the Track Association and Fusion problem are presented.
- Active and Passive Radar Detection and Equipment
- Target Direction, Range and Position Finding