Ultra Wideband Radar for Environmental Polarimetric Observation and Scattering Analysis

超EPOS项目致力于超宽带(UWB)雷达应用中的偏振测量。超宽带雷达在近程定位、跟踪和成像应用中以其优异的时间分辨率而闻名。然而，尽管在窄带SAR遥感(地球观测卫星、机载成像系统)领域，UWB极化信息的开发仍处于起步阶段。本项目的主要目标是填补这一空白，并将极化测量的优势带入超宽带雷达领域。UWB偏振测量仪预计将提供有关目标和结构的更详细信息，如形状、取向(边缘、角)、材料成分或表面粗糙度。与在图像(聚焦)域分析极化信息的经典遥感方法不同，UWB极化信号处理可能已经应用于测量(时间)域。UWB传感器的大带宽允许测量的极化信号分量的时间分离。因此，可以将信号特征分配给已经在时间域中的特定散射过程。这将对能够放大或抑制特定信号分量的成像技术、目标检测方法和偏振滤光器产生重大影响。极化处理将改进杂波滤波，并支持利用来自环境的多路径反射来增强场景照明。在我们假设的场景中，发射机和接收机处于多基地布置中。它们可以沿任意轨迹移动，通过从不同的多基地角度照明和观察目标和环境结构来获得空间分集。由此产生的几何星座与我们在经典遥感中所知道的完全不同，需要在成像和探测中利用UWB极化信息的新方法。新的UWB极化成像算法将基于代表不同极化指纹的模型。这允许从各自的对象模型类构造不同的图像。这样，杂乱无章的情况就会减少。多幅局部图像的数据融合将使目标物体的整体图像更加清晰，并允许对目标形状、材料成分和表面结构进行更可靠的解释。我们考虑两个相辅相成的场景。第一种情况包括单独的目标对象。我们对选定的物体进行广泛的测量，以获得不受环境(墙壁、其他物体)干扰杂波影响的基本极化指纹库。在第二种现实的室内场景中，应利用这种目标与环境的相互作用来获得有关目标的更多信息(多径利用)，并改进探测和成像性能。

The Ultra EPOS project addresses polarimetry in ultra wideband (UWB) radar applications. UWB radars are well known for their excellent time resolution in short range localization, tracking and imaging applications. However, exploitation of UWB polarimetric information is still in its infancy despite the fact that the polarimetry is renowned in the field of narrowband SAR remote sensing (earth observation satellites, airborne imaging systems). The main goal of this project is to fill in this gap and to bring advantages of polarimetry into the field of UWB radars as well. UWB polarimetry is anticipated to provide more detailed information about targets and structures such as shape, orientation (edges, corners), material composition or surface roughness. In contrast to the classical remote sensing methods which analyse polarimetric information in the image (focused) domain, UWB polarimetric signal processing may already be applied in the measurement (time) domain. The large bandwidth of UWB sensors allows temporal separation of measured polarimetric signal components. Therefore, signal features can be assigned to a specific scattering process already in the time domain. This will significantly influence imaging techniques, object detection methods and polarimetric filters that can amplify or suppress specific signal components. Polarimetric processing will enable improvement of clutter filtering and support exploitation of multipath reflections from the environment to enhance scene illumination. In our assumed scenarios, transmitters and receivers are in a multistatic arrangement. They can be moved along arbitrary tracks in order to gain spatial diversity by illuminating and observing targets and environmental structures from different multistatic angles. The resulting geometric constellation is completely different from what we know in classical remote sensing and requires new methods for exploitation of UWB polarimetric information in imaging and detection. The new UWB polarimetric imaging algorithms will be based on models that represent different polarimetric fingerprints. This allows the construction of distinct images form the respective object model classes. In this way clutter will be reduced. Data fusion of multiple partial images will lead to a clearer overall image of the target object and allow more reliable interpretation on target shape, material composition and surface structure. We consider two complementary scenarios. The first scenario encompasses solitary target objects. We perform extensive measurements of selected objects in order to obtain a library of basic polarimetric fingerprints that are not influenced by a disturbing clutter due to the environment (walls, other objects). In a second realistic indoor scenario this target-to-environment interaction shall be exploited to obtain more information about the target (multipath exploitation) and to improve detection and imaging performance.