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

我们生活在一个联系日益紧密的世界，依赖于无处不在的数字基础设施，这些基础设施的覆盖范围和复杂性越来越大，地面和空间通信和传感网络的整合已经开始以一种持久的方式收集、共享和交换信息，没有自然障碍。更高级别的服务互可靠性要求对物理基础设施进行快速和可操作的自动评估，以检测潜在的异常。在受保护的近地轨道和地球同步轨道区域，地球轨道卫星数量的爆炸性增长加剧了受到空间物体或碎片撞击或意图利用产生的物体重新利用卫星或其整个网络的敌对活动破坏的风险。该研究为利用量子星载逆合成孔径雷达（ISAR）图像实现动态环境的多视角监测奠定了基础。它将使用来自多尺度人造物体和碎片簇的次太赫兹散射来生成卫星描述符和可部署物的散射特征库，并开发用于异常检测和表征的鲁棒深度学习分类和识别方法。该技术将充分利用空间在轨监测的优势，包括：-消除大气吸收和衰减，因此需要高功率传输来补偿地面系统固有的长距离大传播损耗。-较短的工作范围和没有大气不利现象允许使用高频（超过100千兆赫），能够提供前所未有的分辨率雷达图像与一个紧凑的传感器。-空间三维观测轨迹提供的可达有利位置的多样性。这可以从地面上无法获得的观测方面提供目前缺失的物体观测，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，特别是在外观或行为上的异常。该项目雄心勃勃的目标是开展多学科基础和应用研究，利用在亚太赫兹区域（Sub-THz）工作的天基多维逆合成孔径雷达（ISAR），实现空间基础设施监测的创新传感。这种技术将能够提供基于量子支持的分布式星载雷达的协同空间域感知（CoSDA），这可能会改变高价值资产的监控和保护。该系统将能够跟踪潜在的危险，从地球无法获得的范围和方面对太空居民进行成像和表征，并以地球无法实现的分辨率向现有的空间态势感知（SSA）光电传感器和地面雷达（GBR）提供额外的数据维度。该技术为确保高度互联的自主系统的未来安全性奠定了坚实的基础。

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.