Multi-dimensional quantum-enabled sub-THz Space-Borne ISAR sensing for space domain awareness and critical infrastructure monitoring - SBISAR

我们生活在联系日益紧密的世界，依赖于覆盖范围越来越广、越来越复杂的无处不在的数字基础设施，地面和空间通信和传感网络的整合已经开始，以无自然障碍的持续方式收集、共享和交换信息。服务的更高水平的相互可靠性要求对物理基础设施进行快速和可行的自动评估，以检测潜在的异常情况。受保护的低轨和地球静止轨道区域的地球轨道卫星数量呈爆炸性增长，这加剧了空间物体或碎片的撞击，或旨在利用所产生的物体改变卫星或其整个网络用途的敌对活动造成破坏的风险。这项研究为利用量子星载逆合成孔径雷达(ISAR)图像对动态环境进行多视角监测奠定了新的能力。它将利用多尺度人造物体和碎片簇的亚太赫兹散射来生成卫星描述符和可展开物的散射特征库，并为异常检测和表征开发强大的深度学习分类和识别方法。该技术将最大限度地利用从太空进行在轨监测的优势，包括：-消除大气吸收和衰减，从而需要高功率传输以补偿地面系统固有的大距离传播损失。-较短的工作距离和没有大气不利现象，使得能够使用高频(100 GHz以上)，通过紧凑的传感器提供前所未有的分辨率的雷达图像。-从空间进行三维观测轨迹提供的可接近的有利位置的多样性。这提供了从地面不可用的角度观察当前缺失的物体，以及重建多时间或多视角的2D和3D图像。来自这些多维观测的数据将实现端到端的分割和分类，特别是外观或行为方面的异常。该项目雄心勃勃的目标是开展多学科的基础和应用研究，以便能够利用工作在亚太赫兹区域(亚太赫兹)的天基多维逆合成孔径雷达为空间基础设施监测提供创新的遥感。这种技术将能够提供基于量子分布式星载雷达的合作空间领域感知(CoSDA)，这可能会改变监测和保护高价值资产的游戏规则。该系统将能够以地球无法实现的分辨率，跟踪潜在危险，从地球上无法获得的范围和方面对空间居民进行成像和定性，从而向现有的空间态势感知光电传感器和地面雷达提供更多维度的数据。该技术为确保未来高度互联的自治系统的安全和保障奠定了坚实的基础。

We live in increasingly connected world, reliant on ubiquitous digital infrastructure of increasing reach and complexity, and integration of terrestrial and space communication and sensing networks to gather, share and exchange information in a persistent way without natural barriers has already started. Higher levels of inter-reliability of the services require fast and actionable automatic assessment of physical infrastructure to detect potential anomalies. The explosive growth of Earth-orbiting satellite populations in protected LEO and GEO regions exacerbates the risk of disruption from either impact with space objects or debris, or hostile activity intended to re-purpose the satellite or its whole network using spawned objects. This research lays the foundation for a new capability for multi-perspective monitoring of dynamic environments, using quantum enabled space-borne inverse synthetic aperture radar (ISAR) imagery. It will use sub-THz scattering from multi-scale manmade objects and clusters of debris to generate a library of scattering characteristics of satellite descriptors and deployables, and develop robust deep-learning classification and recognition approaches for anomaly detection and characterization. The technology will make the most of the advantages for in-orbit monitoring from space, including:- The elimination of atmospheric absorption and attenuation, and thus the need for high power transmission to compensate for large propagation losses over large distances, inherent to ground based systems. - The shorter operational ranges and the absence of atmospheric adverse phenomena allow use of high frequencies (above 100 GHz) able to deliver unprecedented resolution of radar imagery with a compact sensor. - The diversity of accessible vantage points provided by 3D observation trajectories from space. This delivers currently missing object observation from viewing aspects not available from the ground, as well as reconstruction of multi-temporal or multi-perspective 2D and 3D imagery.The data from these multi-dimensional observations will enable end-to-end segmentation and classification, in particular, anomalies in appearance or behaviour. The project's ambitious goal is to undertake multi-disciplinary fundamental and applied studies to enable innovative sensing for space infrastructure monitoring by use of space-based multi-dimensional Inverse Synthetic Aperture Radar (ISAR) operating in the sub-terahertz region (Sub-THz). Such technology will be able to deliver co-operative Space Domain Awareness (CoSDA) based on quantum-enabled distributed space-borne radar, which can be a game changer for monitoring and protection of high value assets. The system will be able to track potential hazards, image and characterize the space residents at ranges and from aspects unavailable from Earth, and with a resolution unachievable from Earth, to deliver additional dimensionality of data to existing Space Situational Awareness (SSA) electro-optical sensors and ground-based radar (GBR). The technology builds a strong foundation for ensuring the future safety and security of highly interconnected autonomous systems.