A super-resolution algorithm for synthetic aperture radar based on modified spatially variant apodization
The existing spatially variant apodizations (SVAs) either cannot depress the sidelobes effectively or reduce the energy of the mainlobe. To improve this, a modified SVA (MSVA) is put forward in this paper, which expands the traditional filter from 3-taps to 5-taps and sets relevant parameters according to different sampling rates to get the excellent result that satisfies constrained optimization theory. A modified super-SVA is also presented, which compares the result after the iteration with the original signal and makes the one whose amplitude is smaller as the initial value of the next iteration. This method can eliminate the sidelobes produced by the intermediate operation, so that the following bandwidth extrapolation is more available. Super-MSVA is presented based on the modified SVA and modified super-SVA, which is suitable for any Nyquist sampling rate, can extrapolate the signal bandwidth many times through iteration with a commensurate improvement in resolution, as demonstrated by the result of th e experiment.
synthetic aperture radar sidelobe suppression super-resolution SVA
NI Chong WANG YanFei XU XiangHui ZHOU ChangYi CUI PengFei
Institute of Electronics, Chinese Academy of Sciences. Beijing 100190, China Graduate University of Institute of Electronics, Chinese Academy of Sciences. Beijing 100190, China
国际会议
北京
英文
355-364
2010-04-27（万方平台首次上网日期，不代表论文的发表时间）