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• W4205087105 endingPage "103418" @default.
• W4205087105 startingPage "103418" @default.
• W4205087105 abstract "Under the interference of airborne radar clutter, it is a challenge for fast maneuvering target detection, because of the nonstationary echo signal involved within the long coherent processing interval (CPI). To tackle this issue, a robust clutter suppression and small maneuvering target detection method is proposed in airborne radar system, which is referred to as the sub-CPI space-time adaptive processing (STAP) based refocusing. For robust clutter suppression, the whole CPI is divided into a series of equal-length and overlapped sub-CPIs with the sliding window technique. In each sub-CPI, the STAP algorithm is adopted for robust clutter suppression, in which the consistent covariance matrix estimation is derived to guarantee the linear phase response within the whole CPI. However, as endo-clutter weak target is considered, the signal-to-clutter-plus-noise ratio (SCNR) after sub-CPI STAP still cannot meet the performance requirement. Thus, the target refocusing is applied for further SCNR improvement based on the semi-searching mechanism. However, the range walking (RW) and Doppler frequency migration problems defocus the energy of fast maneuvering target over range and Doppler frequency dimensions, respectively. To circumvent such problems, Keystone transform is utilized to correct the RW, followed by the Lv's distribution to achieve target refocusing. Numerical simulations and measured results with sum and difference channels validate the effectiveness of the proposed method." @default.
• W4205087105 created "2022-01-26" @default.
• W4205087105 creator A5009278756 @default.
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• W4205087105 date "2022-04-01" @default.
• W4205087105 modified "2023-10-18" @default.
• W4205087105 title "Sub-CPI STAP based clutter suppression and target refocusing with airborne radar system" @default.
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• W4205087105 doi "https://doi.org/10.1016/j.dsp.2022.103418" @default.
• W4205087105 hasPublicationYear "2022" @default.
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