摘要
针对高分辨率宽测绘带合成孔径雷达(SAR)成像面临高速采样、大数据量存储等问题,将压缩感知(CS)理论与方位多波束(MAB)技术结合,提出一种基于压缩感知的方位多波束SAR成像方法。该方法对SAR回波信号进行快时间和慢时间维的降采样,然后分别构造距离和方位维的测量矩阵,利用随机滤波CS理论实现对目标的二维稀疏重建。仿真结果表明,该方法不仅能以较少的采样数据解决方位高分辨与宽测绘带之间的矛盾,还能在噪声存在的情况下重建目标的二维图像。
To address the problem that high speed sampling and large scale data storage are encountered by a high-resolution and wide-swath synthetic aperture radar(SAR), a novel method of multiple azimuth beams(MAB) SAR imaging via compressed sensing is proposed. The raw data is collected with lower sampling rate than the required Nyquist sampling rate in the fast and slow time dimension respec- tively, then the measurement matrix is established in range and azimuth dimension respectively, and two-dimensional reconstruction of a target using compressed sensing is carried out. The simulation results indicate that this method can not only solve the contradiction between azimuth high resolution and wide swath with less sampled data, but also reconstruct the target image under the noise.
出处
《电波科学学报》
EI
CSCD
北大核心
2012年第5期979-984,共6页
Chinese Journal of Radio Science
基金
中央高校基本科研业务费项目(No.ZYGX2010J118)
关键词
方位多波束合成孔径雷达
压缩感知
随机滤波
azimuth multiple beams synthetic aperture radar
compressed sensing
random filter