PFA imaging with range migration correction by compressive sensing

Duan Huajun; Zhu Daiyin

doi:10.11834/jig.20140713

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PFA imaging with range migration correction by compressive sensing
Vol. 19, Issue 7, Pages: 1085-1094(2014)
Published Online：01 July 2014，

Published：2014
DOI： 10.11834/jig.20140713
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DOI：

Duan Huajun, Zhu Daiyin. PFA imaging with range migration correction by compressive sensing[J]. Journal of Image and Graphics, 2014, 19(7): 1085-1094. DOI： 10.11834/jig.20140713.

摘要

极坐标格式算法（PFA）是合成孔径雷达（SAR）聚束模式下的一种高分辨率成像算法，方位向增加孔径长度带来了数据存储和传输的负担，利用压缩感知进行合成孔径雷达成像可以减小采样率，以前的研究往往认为图像是2维可分离的而忽略距离徙动的影响，造成了图像质量的下降。提出一种在方位向利用压缩感知处理的PFA成像算法，可以校正距离徙动，保证压缩感知成像的图像分辨率。在方位向进行压缩感知处理的过程时，采用了随距离空间频率变化的傅里叶基。该方法可以有效代替PFA处理过程中的方位向插值，消除距离徙动的影响，保证距离向和方位向的分辨率。仿真和实测数据的处理结果证明了该方法的有效性。

Abstract

Polar format algorithm is an imaging approach for spotlight mode synthetic aperture radar (SAR). It increases the load of data transmission and storage severely because of the greater synthetic aperture length. Synthetic aperture radar imaging by compressive sensing can reduce the sampling rate. Previous studies result in a decrease in image quality because they assume that the two dimensions of images are separable and ignore the range migration. An imaging approach based on range-cross compressive sensing is presented. It can correct the range migration and ensure the range and range-cross resolution of the image. The method introduces the Fourier basis varying with the range spatial frequency

reconstructing the image based on compressive sensing. It ensures the range and range-cross resolution because it may be an efficient substitute for Polar format algorithm range-cross interpolation and eliminates the range migration. The simulations and live data processing results show the validity of the proposed approach.