近空间斜视SAR的子孔径二次距离压缩算法

Yi Sun, Xiaojun Jing, Songlin Sun, Hai Huang
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引用次数: 2

摘要

讨论了近空间平台斜视合成孔径雷达(SAR)成像问题,提出了一种改进的二次距离压缩(SRC)算法——子孔径二次距离压缩(SSRC)算法。在SRC算法中,关键的一步是使用子孔径方法。首先将原始信号在时域方位角方向上分割成子孔径独立成像,然后将频域的子带组合成最终的SAR图像。该方法减少了斜视成像模式下回波信号距离和方位方向的耦合,解决了近空间斜视SAR合成孔径过长、运动误差等问题。通过点目标仿真验证了该算法在方位角分辨率、ISLR和PSLR方面的改进,验证了该算法在近空间斜视SAR成像中的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The Subaperture Secondary Range Compression Algorithm for near space squint SAR
This paper discusses squint synthetic aperture radar (SAR) imaging in the near space platform and proposes an improved Secondary Range Compression (SRC) Algorithm, Subaperture Secondary Range Compression (SSRC) Algorithm. The key step is to use the subaperture approach in the SRC algorithm. First, the original signals are divided into subapertures in the azimuth direction of the time domain to image independently, and then the sub-bands of the frequency domain are combined to form the final SAR image. The method reduces coupling in the range and azimuth direction of the echo signal under the squint imaging mode, and addresses the problems of squint SAR in near space including overlong synthetic aperture and motion error. Simulation through point targets demonstrates the improvement in azimuth resolution, ISLR and PSLR, which verifies the effectiveness of this proposed SSRC algorithm in near space squint SAR imaging.
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