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- W4386698049 abstract "In inverse synthetic aperture radar (ISAR) imaging, a lot of attention is paid to the sharpest-image phase adjustment for its good focus quality and robustness against noise and target scintillation. It can be done by the fixed-point algorithm, which is both universally applicable and computationally efficient. This paper develops this algorithm with a general sharpness measure and reveals that for this algorithm to converge stably and correctly, the sharpness measure should have a kernel function whose absolute derivative is an increasing function. Further, a sharpness measure is presented for the fixed-point algorithm. This sharpness measure leads to a good focus quality like the negative entropy because their kernel functions have similar second-order derivatives. Also, since this sharpness measure has a kernel function whose absolute derivative is an increasing function, the fixed-point algorithm with this sharpness measure converges stably and correctly." @default.
- W4386698049 created "2023-09-14" @default.
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- W4386698049 date "2023-09-02" @default.
- W4386698049 modified "2023-09-30" @default.
- W4386698049 title "Convergence of the fixed-point algorithm in ISAR imaging" @default.
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- W4386698049 doi "https://doi.org/10.1080/2150704x.2023.2258461" @default.
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