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Efficient Reiterative Censoring of Robust STAP Using the FRACTA Algorithm

机译:利用FRaCTa算法对鲁棒sTap进行有效重复截断

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This paper presents further developments of the FRACTA algorithm which has been shown to be robust to nonhomogeneous environments containing outliers. The focus here is on the efficient implementation of the FRACTA algorithm. The key development is a censoring stopping mechanism whereby the number of reiterative steps can be minimized and computation is reduced. We introduce a data dependent stopping rule that demonstrates excellent results as evidenced by the detection of targets in the KASSPER challenge data cube. We also present some other enhancements to the FRACTA algorithm that further improve both efficiency and performance.

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