NEW PHYSICS-BASED INVERSE-SCATTERING TECHNIQUES FOR ULTRAWIDEBAND DISTRIBUTED SENSING

这项研究的目标是发展稳健的基于物理的时域超宽带逆散射技术，利用射频和微波信号检测随机介质中的遮挡目标。该方法基于信息论的贝叶斯范式，其中探测、成像和分类遮挡目标的逆散射问题被视为信息状态的连接，该信息状态将(1)先验信息数据与(2)(基于物理的)正问题解和传感器数据获取相结合，以产生(3)信息的后验状态。所提出的超宽带反演方法的智能贡献包括：(1)利用无序介质中超宽带信号的空间去相关所提供的超分辨率效应，以获得超出经典衍射极限(超分辨率)的成像分辨率；(2)利用基于时间反转的超宽带波的合成反向传播来提供随机介质中的频率去相关，从而提供统计稳定的检测/成像算法。拟议的基于物理的反演技术将为超宽带传感器提供新的能力，旨在改善探测和成像系统在微波和无线电频率上的应用方式。拟议中的研究有可能为搜救行动带来好处，救援队必须能够在倒塌的建筑、山体滑坡和其他废墟下找到隐藏的幸存者。它还有助于监视系统探测墙后(穿透墙成像)、屋顶下或角落周围的物体和人员，以及用于人道主义排雷的探地雷达系统。拟议的研究目标与旨在为俄亥俄州立大学的学生提供全面培训的教育部分相结合。

The objective of this research is to develop robust physics-based time-domain ultra-wideband inverse scattering techniques to detect obscured targets in random media using radio-frequency and microwave signals. The approach is based on an information-theoretic, Bayesian paradigm where the inverse scattering problem of detecting, imaging, and classifying obscured targets is treated as a conjunction of states of information that combine (1) a-priori information data with (2) (physics-based) forward problem solution and sensor data acquisition, to produce (3) the a posteriori state of information. The intellectual contributions of the proposed ultra-wideband inversion methodology involve (1) exploitation of super-resolution effects provided by spatial decorrelation of ultra-wideband signals in disordered media to yield imaging resolution beyond the classical diffraction limit (super-resolution) and (2) harnessing of time-reversal based synthetic back-propagation of ultra-wideband waves to provide frequency decorrelation in random media and, hence, statistically stable detection/imaging algorithms. The proposed physics-based inversion techniques will provide new capabilities for ultra-wideband sensors aimed at improving the way detection and imaging systems are employed at microwaves and radio-frequencies. The proposed research has the potential to benefit search-and-rescue operations where rescue teams must be able to locate hidden survivors under collapsed buildings, landslides, and other debris. It can also benefit surveillance systems for detecting objects and personnel behind walls (thru-wall imaging), under roofs, or around corners, and ground penetrating radar systems for humanitarian demining. The proposed research objectives are integrated with an education component aimed at providing a well-rounded training to students at The Ohio State University.