Abstract

 
 
 Synthetic aperture radars are radar platforms that generate detailed images through radio frequency transmission and receiving. These systems can be high peak power, complex systems that can suffer from internal component or subsystem degradation. In addition, the operational environment can also affect the final image of the radar due to scene-based radio frequency interference (RFI). Because of these effects, it is ideal to be able to identify, classify, and quantify the degradation of these systems in order to optimize their performance and life. The work presented in this paper is an extension of QorTek’s previous work using Symbolic Analysis to detect degradation using the radar’s phase history data. In conjunction with the KEYW, Corp., QorTek has acquired field data to train and test its algorithm. To test the trained algorithm, a prototype hardware/software system integrating the SA approach was designed, built and flown on a test flight piggybacking on a radar system provided by KEYW. The initial results were very positive and also identified areas of improvement. The training and test results as well as the flight-test plan and results are presented in this paper. The paper concludes with specific improvements to be made to the algorithm for the next round of radar integration and flight-testing.
 
 
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