Full-aperture processing of airborne microwave photonic SAR raw data

J Chen, M Li, H Yu, M Xing - IEEE Transactions on Geoscience …, 2023 - ieeexplore.ieee.org
J Chen, M Li, H Yu, M Xing
IEEE Transactions on Geoscience and Remote Sensing, 2023ieeexplore.ieee.org
At present, the resolution of the most advanced airborne microwave photonic synthetic
aperture radar (SAR) can reach the order of centimeters or even millimeters, so the 2-D
spatial variation and 2-D coupling characteristics of motion error will become more serious.
In this article, based on the advantages of nonlinear chirp scaling (NCS) and resampling
(RS) processing, a microwave photonic SAR full-aperture autofocus algorithm based on a
cascaded NCS-RS is proposed. First, the proposed algorithm combines the typical two-step …
At present, the resolution of the most advanced airborne microwave photonic synthetic aperture radar (SAR) can reach the order of centimeters or even millimeters, so the 2-D spatial variation and 2-D coupling characteristics of motion error will become more serious. In this article, based on the advantages of nonlinear chirp scaling (NCS) and resampling (RS) processing, a microwave photonic SAR full-aperture autofocus algorithm based on a cascaded NCS-RS is proposed. First, the proposed algorithm combines the typical two-step MoCo and chirp-Z transform (CZT) to correct the range spatial variant (RV) characteristics of motion error. Then, a cascaded NCS-RS processing is used to correct the azimuth RV (AV) characteristics of motion error, in which NCS processing is introduced before range cell migration correction (RCMC) and RS processing is introduced after RCMC. Finally, the RS in cascaded NCS-RS processing is modified to change with range to correct the range-azimuth coupling characteristic of motion error. The three steps of the algorithm belong to the full-aperture processing, which avoids the problems of grating lobes and image stitching caused by the subaperture algorithm. The estimation of the parameters in NCS-RS processing is modeled as a high-dimensional optimization problem. Before solving this optimization problem, it is converted to multiple 1-D optimization problems. The results of processing simulated and measured data verify the effectiveness of the proposed algorithm.
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