稀疏目标多频GPR微波成像的多任务贝叶斯压缩感知方法
Multi-Frequency GPR Microwave Imaging of Sparse Targets Through a Multi-Task Bayesian Compressive Sensing Approach
摘要：
提出了一种新颖的逆散射（IS）方法，用于有耗半空间中像素稀疏散射体的定量成像。一方面，这种方法通过联合处理所收集的雷达图的多频（MF）谱分量来利用地面穿透雷达（GPR）数据的宽带性质。另一方面，它强制稀疏先验问题的未知数，以产生正则化的解决方案的完全非线性散射方程。为此，多任务贝叶斯压缩感知（MT-BCS）的方法，并适当定制，以充分利用可用的频率分集和先验信息的类成像目标。有代表性的结果报告，以评估拟议的MF-MT-BCS战略也比较有竞争力的国家的最先进的替代品。
英文摘要：
An innovative inverse scattering (IS) method is proposed for the quantitative imaging of pixel-sparse scatterers buried within a lossy half-space. On the one hand, such an approach leverages on the wide-band nature of ground penetrating radar (GPR) data by jointly processing the multi-frequency (MF) spectral components of the collected radargrams. On the other hand, it enforces sparsity priors on the problem unknowns to yield regularized solutions of the fully non-linear scattering equations. Towards this end, a multi-task Bayesian Compressive Sensing (MT-BCS) methodology is adopted and suitably customized to take full advantage of the available frequency diversity and of the a-priori information on the class of imaged targets. Representative results are reported to assess the proposed MF-MT-BCS strategy also in comparison with competitive state-of-the-art alternatives.
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