Location Fusion in Land Combat Models
NAVAL POSTGRADUATE SCHOOL MONTEREY CA DEPT OF OPERATIONS RESEARCH
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This document discusses methods for representing and fusing location information in combat models, distinguishing between Monte Carlo and analytic models. The Kalman filter is emphasized as a practical and accurate method for fusing new and old information. One particularly useful Kalman filter, the Maneuvering Target Statistical Tracker MTST, is dealt with explicitly. Fused information is often represented graphically by ellipses, the equivalent of a Kalman filters covariance matrix. The connection between elliptical dimensions and kill probabilities also is reviewed. The report focuses on the following topics fusion -- what is it filtering of position, including motion model MTST and measurement data association Monte Carlo fusion analytic fusion and kill probabilities, including notation, Carleton weapons, cookie-cutter weapons, and patterns.
- Information Science
- Numerical Mathematics
- Statistics and Probability
- Target Direction, Range and Position Finding