针对海面场景目标SAR的海量数据压缩与重构问题,提出利用一种新的数据压缩与重构理论——压缩感知理论来完成。首先构造随机高斯噪声观测矩阵对原始回波数据进行降维处理以达到大幅压缩的目的,然后利用平滑L0算法重构原始回波信号,在此基础上,利用传统的频率变标SAR成像算法进行成像。仿真结果证明了该方法的有效性。
The compressed sensing theory (a new data compressing and reconstructing theory) is utilized in this paper to solve the issue of huge SAR data compressing and reconstructing for sea scene target. Firstly, random Gaussian noise matrix is designed as a measurement matrix to complete data compressing. Secondly, smooth L0 (SL0) algorithm is utilized to reconstruct original signal. On the basis of that, traditional frequency scaling (FS) algorithm is carried out to obtain the final SAR image. The effectiveness of the proposed method can be proved by simulation results.