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基于ROSAR的高分辨波数域成像算法
引用本文:张俊,廖桂生,许京伟,朱圣棋,杨科.基于ROSAR的高分辨波数域成像算法[J].系统工程与电子技术,2017,39(6):1227-1234.
作者姓名:张俊  廖桂生  许京伟  朱圣棋  杨科
作者单位:1. 西安电子科技大学雷达信号处理国家重点实验室, 陕西 西安 710071;; 2. 上海无线电设备研究所, 上海 200090
摘    要:旋转式合成孔径雷达(rotor synthetic aperture radar,ROSAR)是一种新型成像雷达,在高分辨条件下,距离徙动对ROSAR成像结果影响严重。波数域成像算法利用插值操作实现距离徙动的精确校正,但由于ROSAR复杂的斜距历程,导致传统波数处理获得的二维波数谱形式复杂,难以进行插值操作。针对这一问题,提出了一种改进ROSAR波数域成像算法。重新构建角度维波数,通过求解隐函数获得易于插值操作的信号二维波数域表达式,设计参考函数消除高频调制影响,最终通过Stolt插值实现宽波束大场景下距离徙动无近似校正与精确聚焦。仿真实验验证了算法的可行性与有效性。


Research on high resolution wavenumber-domain imaging algorithm for ROSAR
ZHANG Jun,LIAO Guisheng,XU Jingwei,ZHU Shengqi,YANG Ke.Research on high resolution wavenumber-domain imaging algorithm for ROSAR[J].System Engineering and Electronics,2017,39(6):1227-1234.
Authors:ZHANG Jun  LIAO Guisheng  XU Jingwei  ZHU Shengqi  YANG Ke
Institution:1. National Lab of Radar Signal Processing, Xidian University, Xi’an 710071, China;; 2. Shanghai Radio Equipment Research Institute, Shanghai 200090, China
Abstract:Rotor synthetic aperture radar (ROSAR) is a new mode of imaging radar. Under the condition of high resolution, range cell migration (RCM) has significant effects on the image. The wavenumber-domain imaging algorithm involves precise RCM correction by means of interpolation, but it is hard to use interpolation for two-dimensional wavenumber spectrum acquired by the traditional wavenumber-domain method, due to the complex expression of distance history. To deal with this problem, a modified wavenumber-domain imaging algorithm for ROSAR is proposed. The wavenumber vector is rebuilt in azimuthal angle domain, the 2-D wavenumber spectrum which is proper to perform interpolation can be obtained by solving implicit function, the reference function is designed to eliminate effects from high frequency modulation, the well-focused image and RCM correction with no approximation for wide-beam and large-scale scene are obtained by Stolt interpolation. The simulation results validate the effectiveness and feasibility of the proposed algorithm.
Keywords:
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