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Abstract:
An air-to-air missile vector scoring system is proposed for test and evaluation applications. Three different linear missile dynamics models are considered: a six-state constant velocity model and nine-state constant acceleration and three-dimensional coordinated turn models. Frequency modulated continuous wave radar sensors, carefully located to provide spherical coverage around the target, provide updates of missile kinematic information relative to a drone aircraft. Data from the radar sensors is fused with predictions from one of the three missile models using either an extended Kalman filter, an unscented Kalman filter or a particle filter algorithm. The performance of all nine model/filter combinations are evaluated through high-fidelity, six-degree of freedom simulations yielding sub-meter end-game accuracy in a variety of scenarios. Simulations demonstrate the superior performance of the unscented Kalman filter incorporating the continuous velocity dynamics model. The scoring system is experimentally demonstrated through flight testing using commercial off the shelf radar sensors with a Beechcraft C-12 as a surrogate missile.
| Limitations: |
 APPROVED FOR PUBLIC RELEASE |
| Description: |
Master's thesis |
| Pages: |
248 |
| Report Date: |
22 Mar 2012 |
| Report Number: |
A198955 |
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