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带距离徙动校正的压缩感知PFA成像方法
引用本文:段化军,朱岱寅.带距离徙动校正的压缩感知PFA成像方法[J].中国图象图形学报,2014,19(7):1085-1094.
作者姓名:段化军  朱岱寅
作者单位:南京航空航天大学电子信息工程学院, 南京 210016;南京航空航天大学电子信息工程学院, 南京 210016
基金项目:国家自然科学基金项目(61071165);教育部新世纪优秀人才支持计划(NCET-09-0069);航空科学基金项目(20102052024)
摘    要:目的 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。方法 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。结果 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。结论 仿真和实测数据的处理结果证明了该方法的有效性。

关 键 词:极坐标格式算法(PFA)  压缩感知  距离向插值  方位向插值  距离徙动校正
收稿时间:2013/10/16 0:00:00
修稿时间:2014/1/13 0:00:00

PFA imaging with range migration correction by compressive sensing
Duan Huajun and Zhu Daiyin.PFA imaging with range migration correction by compressive sensing[J].Journal of Image and Graphics,2014,19(7):1085-1094.
Authors:Duan Huajun and Zhu Daiyin
Affiliation:College of Electronic and Information Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China;College of Electronic and Information Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China
Abstract:Objective 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. Method The method introduces the Fourier basis varying with the range spatial frequency, reconstructing the image based on compressive sensing. Result 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. Conclusion The simulations and live data processing results show the validity of the proposed approach.
Keywords:potar fonmat algorilhm (PFA)  compressive sensing  range interpolation  range-cross interpolation  range migration correction
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