Adaptive Filtering and Smoothing for Tracking a Hypersonic Aircraft from a Space Platform
AIR FORCE INST OF TECH WRIGHT-PATTERSON AFB OH SCHOOL OF ENGINEERING
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This study took a previously developed six state Kalman filter designed for space-based tracking of a hypersonic transatmospheric vehicle, tuned it, and performed a Monte Carlo analysis. Three multiple model adaptive filters were then developed, with sub-filters designed for quiescent periods and periods with apparent acceleration. Next, a smoother was developed using the six state filter as the forward filter and a form of that same filter as the backward filter. The smoother and all of the above filters were compared for their ability to most accurately estimate the transatmospheric vehicles state, with special emphasis on the acceleration states. This emphasis was motivated by a desire to evaluate the Kalman filters usefulness as a real-time intelligence gathering tool. From the data generated, it was concluded that neither the adaptive filters nor the smoother improved upon the performance of the six state Kalman filter.
- Target Direction, Range and Position Finding