Compressed sensing for terahertz body scanners

太赫兹人体扫描仪的压缩传感

• 批准号: 273378044
• 负责人: Professor Dr. Heinz-Wilhelm Hübers
• 金额: --
• 依托单位: Institut für Physik
• 依托单位国家: 德国
• 项目类别: Priority Programmes
• 财政年份: 2015
• 资助国家: 德国
• 起止时间: 2014-12-31 至 2019-12-31
• 项目状态: 已结题
• 来源: https://gepris.dfg.de/gepris/projekt/273378044?language=en
• 关键词: Compressed; sensing; terahertz; body; scanners

Over the last 20 years the terahertz (THz) region of the electromagnetic spectrum has developed from once being known as the THz gap into a very promising region for many applications. The most prominent one is security imaging, where THz body scanners are a vivid research field. For this application high quality, real-time or video-rate imaging capabilities are necessary. However, large-scale detector arrays are not readily available for THz radiation. This challenge is addressed by using a single or just a few very sensitive detectors in combination with mechanical scanning. Therefore, techniques which combine high sensitivity, single pixel detectors with fast, non-mechanical scanning are crucial for not only for security imaging but for all THz imaging applications. Since in many applications THz images are quite smooth it is likely that they are sparse in the Fourier and/or wavelet domain. In fact, first research results demonstrate this sparsity. Utilizing Compressed Sensing (CS) techniques can reduce the number of measurement acquisitions and thus decreasing the imaging time, because if only a single pixel is available the imaging time is directly proportional to the number of acquisitions. Therefore CS is a very promising technique to improve THz imaging significantly. The objective of the project is to develop a measurement design and CS reconstruction algorithms for THz body scanners in order to improve the image quality and the imaging speed of these scanners. The algorithms will be developed for a phase-sensitive passive THz body scanner and a THz radar body scanner. Both are single pixel cameras and capable of imaging at 5 m stand-off distance. The peculiarities of the THz spectral region require tackling several challenges within the CS framework. These are, for example, multi-path propagation, diffraction problems, speckle and coherence effects of the radiation. Among all the issues to be account for, the exact modeling of these phenomena is extremely complex, and hence simplified models need to be introduced for diverse aspects. This may result in severe model errors, i.e. errors in the sensing matrix. During the project we intend to solve these specific challenges using a compressive deconvolution approach. Furthermore, we want to develop a model of the THz imaging process with both scanners. The model will be verified by measuring the accessible model components. The project is a joined research effort by teams of TU Berlin and TU München. TU Berlin contributes its expertise in THz imaging systems and application of CS to THz imaging while TU München contributes its expertise regarding the application of CS to radar techniques.

在过去的20年中，电子光谱的Terahertz（THZ）区域从曾经被称为THZ间隙到许多应用的非常有前途的区域。最突出的是安全成像，THZ身体扫描仪是一个生动的研究领域。对于此应用程序，需要高质量，实时或视频速率成像功能。但是，大规模检测器阵列不容易用于THZ辐射。通过将单个或仅几个非常敏感的检测器与机械扫描结合使用来解决这一挑战。因此，结合高灵敏度的技术，单像素检测器与快速，非机械扫描的技术不仅对于安全成像，而且对于所有THZ成像应用至关重要。由于在许多应用中，THZ图像非常顺畅，因此它们可能在傅立叶和/或小波域中稀疏。实际上，第一个研究结果表明了这种稀疏性。利用压缩感测（CS）技术可以减少测量采集的数量，从而减少成像时间，因为如果只有单个像素可用，则成像时间与采集数量直接成正比。因此，CS是一种非常有希望的技术，可以显着改善THZ成像。该项目的目的是为THZ身体扫描仪开发测量设计和CS重建算法，以提高这些扫描仪的图像质量和成像速度。该算法将用于相关的被动THZ身体扫描仪和THZ雷达体扫描仪。两者都是单个像素摄像机，并且能够在5 m的隔距离距离进行成像。 THZ光谱区域的特殊性需要解决CS框架内的几个挑战。例如，这些是多路传播，衍射问题，辐射的斑点和连贯作用。在所有要解决的问题中，这些现象的确切建模非常复杂，因此需要针对潜水员方面引入简化的模型。这可能会导致严重的模型误差，即灵敏度矩阵中的误差。在项目期间，我们打算使用压缩反卷积方法来解决这些特定的挑战。此外，我们希望使用两个扫描仪开发一个THZ成像过程的模型。该模型将通过测量可访问的模型组件来验证。该项目是Tu Berlin和TuMünchen团队的一项研究工作。柏林在THZ成像系统中贡献了其专业知识，并应用CS在THZ成像中，而TuMünchen则在将CS应用于雷达技术中贡献了专业知识。