Small-aperture imaging for high squint SAR based on modified Omega-K algorithm

Yuanyuan Huai, Yi Liang, M. Xing, Xiaorui Ma
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引用次数: 1

Abstract

For high squint SAR small-aperture data imaging, the conventional Omega-K algorithm will confront two main problems. First, since the data support region (DSR) in the two-dimension (2-D) wavenumber domain is skew, the conventional algorithm cannot exploit the DSR efficiently enough and degrades the resolution when choosing the square region to process. Second, the small-aperture data can only offer short DSR of the azimuth position. When imaging in the azimuth distance domain, the images will result in serious blurring in azimuth direction unless padding large number of zeroes. Correspondingly, to solve such problems, the modified Omega-K algorithm contains mainly two parts, the “No-Squint” Processing, which corrects the skew DSR to maximize the selection area; And the Small-aperture data imaging processing, which enable the azimuth focus in wavenumber domain, eliminating the azimuth blurring. Experiments show the validity and effectiveness of the proposed algorithm.
基于改进ω - k算法的高斜视SAR小孔径成像
对于高斜视SAR小孔径数据成像,传统的ω - k算法将面临两个主要问题。首先,由于二维波数域的数据支持区域(DSR)是倾斜的,传统算法不能充分利用DSR,并且在选择处理的方形区域时降低了分辨率。其次,小孔径数据只能提供较短的方位位置DSR。在方位角距离域成像时,除非填充大量的零,否则图像在方位角方向上会出现严重的模糊。相应地,为了解决这类问题,改进的Omega-K算法主要包含两个部分:“No-Squint”处理,对倾斜的DSR进行校正,使选择面积最大化;采用小孔径数据成像处理,使方位角聚焦在波数域,消除了方位角模糊。实验证明了该算法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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