基于子空间投影的SFGPR压缩感知成像算法

Subspace Projection Based Compressive Sensing SFGPR Imaging Algorithm

针对传统压缩感知SFGPR成像重建算法在强杂波测量环境中往往会失效的问题,提出一种基于子空间投影杂波抑制技术的SFGPR压缩感知成像重建算法.该算法首先在每个天线测量位置通过压缩感知测量模型重建所有的频域原始均匀采样数据,然后采用子空间投影杂波抑制技术滤除较强的地面回波,最后结合稀疏重建算法对地下目标图像进行压缩感知重建.实验数据处理结果验证了所提方法的有效性和准确性.

The traditional compressive sensing （CS） stepped frequency ground penetrating radar （SFGPR） imaging algorithm usually loses effect in strong clutter environment. To alleviate this problem, a CS SFGPR imaging algorithm based on the subspace projection clutter suppression technique was proposed. The original uniform frequency sampling data at each measurement position were reconstructed from the reduced set of randomly measured data using CS measurement model. Then the subspace projection clutter suppression technique was employed to suppress the strong ground reflection signal. Finally the sparse reconstruction algorithm was used to reconstruct the image of underground targets. The experimental data has verified the validity and effectiveness of the proposed imaging method.