超宽带探地雷达多目标压缩感知成像研究

压缩感知成像要求信号在某个域上能满足稀疏性要求,地下多目标在空域上降低了信号的稀疏性,导致成像出现散焦和虚像。扩大成像背景保证了稀疏性要求但又使得成像计算量上升,实时性不足。提出一种根据探地雷达回波特征预提取出潜在目标位置的压缩感知成像方法。通过对数据进行去噪、滑动矩阵过滤来确定目标的水平位置,再对水平位置处的几道A-Scan 数据进行极值搜索,从而可以提取出成像区域目标位置信息,进而在建立成像冗余字典时只需考虑目标位置处的字典元素,无目标处字典元素直接剔除,减少字典建立所需的元素,降低了压缩感知求解计算量。该方法由于只对潜在目标区域进行成像,因此在保证成像实时性的同时也保证了成像精度。实验结果表明算法可行、有效。

Research on Ultra Wideband Ground Penetrating Radar Multiple Targets Compressive Sensing Imaging

Compressive Sensing (CS) imaging requires signal to satisfy the sparsity condition, multiple underground targets will reduce the sparsity of signal in spatial domain and eventually caused the imaging defocus and less effective. Expanding the detect area may ensure the sparsity but makes the calculation amount increase, and leads to real-time disadvantage. A CS imaging method is proposed by previous extracting potential target position according to GPR detect wave feature. By filtering the noise data, sliding matrix to determine the level of the target location, and then to extreme value search for the several A-Scan data of the assured location, which can extract the target location information of imaging area, so that the imaging redundant dictionary can be created by only considering the elements where the potential targets locate, and the rest of elements for no target position can be eliminated directly. It reduces the elements which the redundant matrix building required, and consequently lower the calculated amount of CS solving. The algorithm focuses on the potential target area instead of imaging for the whole area, therefore the precision and real-time performance of imaging is both guaranteed. The experimental results show that the algorithm is feasible and effective.