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.

The reliance of military systems and armed forces on the EM spectrum creates vulnerabilities and opportunities for electronic warfare (EW) in support of military operations. EW is concerned with detecting, recognising then exploiting and countering the enemy's electronic order of battle, and calls for the development of innovative algorithmic solutions for information extraction and delivery of signals in contested electromagnetic environment. Traditionally, the subject of signal sensing/information extraction has been developed separately from the area of signal delivery. In contrast, this visionary project conducted at Imperial College London and University College London aims at leveraging the consortium complementary expertise in various areas of signal processing (sparsity, super-resolution and subspace methods, communications, radar, and machine learning) for civilian and defence applications to design and develop novel and innovative solutions for a cohesive treatment of information extraction and delivery of signals in contested electromagnetic environment. To put together this novel approach in a credible fashion, this project is organized in two major work packages. The first work package will analyze, separate and characterize signals across time, frequency, and space and extract useful information from those signals by developing and leveraging novel super-resolution, subspace and deep learning methods. The second work package will leverage progress made in the first work package and design signals and system responses for sensing and signaling in congested RF environments. Novel waveform design approaches will be derived for sensing using an extended ambiguity function-based framework, for precise spatiotemporal energy delivery using network-wide time-reversal and for joint sensing and signaling. Attention will also be drawn to the design of signals resilient to hardware and nonlinear channel responses. The project will be performed in partnership with academia/research institutes (University of Kansas, Fraunhofer) and industrial leaders in civilian and military equipment design and manufacturing (IBM, US Army Research Lab, Thales). The project demands a strong track record in a wide range of signal processing techniques and it is to be conducted by a unique research consortium with a right mix of theoretical and practical skills. With the above and given the novelty and originality of the topic, the research outcomes will be of considerable value to transform the future of electronic warfare and give the industry and defence a fresh and timely insight into the development of signal processing for contested electromagnetic environment, advancing UK's research profile in the world. Its success would radically change the design of electronic support measures, electronic coutermeasures and electronic counter-coutermeasures and have a tremendous impact on the defence sector and industry.