Space Domain Awareness Using Radio Telescope-Based Radar Systems

Resident Space Objects (RSOs) are increasing rapidly in number and must be continuously monitored in order to preserve the safety, reliability, and long-term sustainability of space-based services. This requires reliable surveillance systems capable of detecting, tracking, and characterizing objects across different orbital regimes under increasingly demanding observational conditions. Although radar systems remain among the most reliable sensors for these tasks, current architectures still face important limitations in terms of coverage, measurement diversity, tracking robustness, and cost, particularly for weakly observed or manoeuvring targets. This dissertation investigates radar-based sensor network architectures for space surveillance and tracking, with particular emphasis on the use of radio telescope receivers in bistatic, multi-bistatic, and passive radar configurations, examining both geometries that exploit dedicated transmitters and those that rely on signals of opportunity. The unifying motivation is to demonstrate that existing radio astronomy assets, when integrated with advanced signal processing, orbit determination, and data-driven prediction techniques, can meaningfully extend the observational capability of current space domain awareness systems across both Low Earth Orbit (LEO) and Geostationary Earth Orbit (GEO) regimes, without the prohibitive cost of deploying new dedicated radar infrastructure. The observational analysis begins in the GEO regime, where monostatic, bistatic, and multi-bistatic long-baseline radar configurations employing TIRA as the transmitter and e-MERLIN and WSRT as bistatic radio telescope receivers are systematically studied to assess how measurement geometry influences tracking performance and observability. The results demonstrate that the inclusion of bistatic measurements from radio telescope receivers improves state estimation accuracy, while multi-bistatic configurations yield the most favourable performance through increased geometric diversity and measurement complementarity. The analysis then extends to objects undergoing constant thrust manoeuvres, where sustained non-gravitational accelerations make conventional orbit determination frameworks inadequate. A simulation-based study is carried out using three Italian radio telescopes, Medicina, Noto, and SRT, modelling a LEO-to-GEO transfer scenario. A trilateration-based initial orbit determination approach is extended to retrieve thrust acceleration components from multi-bistatic measurements. An unscented Kalman filter operating on the augmented state vector is then employed to accurately estimate the evolving state of the manoeuvring object throughout the transfer. The scope then shifts to passive radar, where InteRFeX, a radio astronomy-inspired array-based space domain awareness facility located in South Australia, is presented. Designed specifically for space surveillance and exploiting signals of opportunity from non-cooperative transmitters, the facility avoids dependence on both dedicated radar infrastructure and astronomical observing schedules. A coherent signal processing pipeline is developed and experimentally validated using real data, confirming the feasibility of passive array architectures for LEO space surveillance. The thesis further addresses the problem of long-term satellite trajectory prediction, where purely data-driven approaches struggle to maintain physical consistency over extended prediction horizons. A hybrid LSTM--PINN framework is formulated that embeds orbital mechanics constraints directly into the learning process, showing that the incorporation of physical knowledge into neural network training yields more reliable and consistent trajectory estimates than learning from data alone. Overall, the thesis demonstrates that improved radar-based sensor networks for space object monitoring can be achieved through the joint development of innovative observation architectures, advanced estimation methods, and modern signal processing techniques. The results support the use of radio telescope receivers and array-based sensing concepts as efficient and potentially cost-effective components of future radar systems for space surveillance and tracking.