Near-field Microwave Imaging of Complex Objects

这项提议的目标是开发对光学不透明但可被微波穿透的物体进行成像的方法。这类材料种类繁多，包括生物组织、木材、陶瓷、塑料、服装、混凝土、土壤等。本方案的重点是对具有复杂内部结构的物体进行近场微波成像。该领域的研究在生物医学成像、隐蔽武器探测、地下探测等领域有着重要的应用。理论上，近场测量，而不是远场测量，由于有可能捕捉到更精细的形状细节，因此有可能获得更高的图像质量。在实践中，这种潜力在很大程度上仍未得到开发。 最近，我们的团队提出了两种新的图像重建算法：基于模型的全息术和基于灵敏度的成像。这两种技术的一个重要优势是它们是准实时执行的；换句话说，与测量本身相比，从测量数据生成图像所需的时间可以忽略不计。更重要的是，它们可以充分利用近场散射微波信号中包含的丰富信息，获得精细分辨率的图像，其中可以分辨出小到波长的百分之一的形状细节。由于这两种技术在概念上使用了不同的重建原理，因此它们在提供独立的诊断或检测结果方面具有互补性。因此，它们可以在一种方法中协同结合，其结果基于两种基本技术的结果，但优于单独采取的任何一种方法。 目前的提议旨在发展上述协同方法，并将其与近场微波数据采集实验装置相结合。软件和硬件的开发将针对组织传感工具，并将其应用于乳腺癌的早期检测，这具有重要的社会意义。同时，所开发的方法将有更广泛的应用范围，可能扩展到隐蔽武器和埋藏物检测。

THE OBJECTIVE of this proposal is the development of methods for the imaging of objects which are optically opaque but are penetrable by microwaves. There is a great variety of such materials including living tissues, wood, ceramics, plastics, clothing, concrete, soil, etc. The focus of this proposal is on the near-field microwave imaging of objects with complex internal structure. This line of research has important applications in biomedical imaging, concealed-weapon detection and underground detection. In theory, near-field measurements, as opposed to far-field measurements, offer the potential for higher image quality due to the possibility of capturing much finer shape details. In practice, this potential has remained largely untapped. Recently, our team has proposed two novel image reconstruction algorithms: model-based holography and sensitivity-based imaging. One important advantage of both techniques is that they perform in quasi-real time; in other words, producing the images from the measured data takes negligible time compared to the measurement itself. More importantly, they can take full advantage of the wealth of information contained in the near-field scattered microwave signals and achieve fine-resolution images where shape details as small as one-hundredth of a wavelength can be distinguished. Since the two techniques exploit conceptually different reconstruction principles, they are complementary in the sense that they provide independent diagnostic or detection results. Thus, they can be combined synergistically in a methodology the outcome of which is based on the results of the two underlying techniques but is superior to any one of them taken separately. The current proposal aims at the development of the synergistic methodology described above and its integration with an experimental setup for near-field microwave data acquisition. The software and hardware development will target tools for tissue sensing with applications in early stage breast-cancer detection, which is of great societal importance. At the same time, the developed approaches will have a much wider range of applications with possible extensions into concealed-weapon and buried-object detection.