Abstract
A statistical method based on symbolic analysis is presented for health management of Synthetic Aperture Radar systems. The approach, based on symbolic theory, develops statistical models of the underlying system dynamics using an underlying Markov assumption and tracks the change in model over time to determine system health. The methodology was designed for minimal impact to legacy systems and required minimal computational effort in order to operate at radar data rates. The approach was applied to radar phase history data corrupted with simulated degradation. Two degradation mechanisms were studied: interference and array degradation. In addition, the results of combined degradation were also studied in this work.
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