Abstract The paper focuses on the opportunity to use star sensors to help space situational awareness and space surveillance. Catalogs of orbiting satellites around Earth are usually established on ground-based measurements that rely on optical or radar data provided by instruments on Earth. However, space-based observations offer new opportunities, as they are unrelated to the weather and the circadian rhythm to which the ground system is subjected. Consequently, space-based optical observation systems can provide data without atmospheric distortion from different observer-to-target distances, enhancing the possibility to detect and catalog resident space objects, i.e. satellites and space debris. This work deals with the feasibility study of an innovative strategy, which consists in the use of a star sensor with a dedicated algorithm to run directly on-board. This approach minimizes the impact on the platform so that, from a theoretical point of view, every satellite with a star sensor can be used as a space surveillance observer. The output of the algorithm consists of a database of pre-processed objects, which are then post-processed on ground. Numerical tests on synthetic images provided by a high-fidelity simulator demonstrate the applicability of the proposed approach. The study has been conducted within the framework of the Italian Space Agency project SPOT - Star sensor image Processing for orbiting Objects deTection.

Highlights • A space-based detection of resident space objects (RSOs) is proposed using star sensors. • A novel on-board algorithm for RSOs detection is described. • An analysis of the performances is reported using a high fidelity simulator. • Radial, tangential and orthogonal observations have been compared. • Results show the feasibility of the described approach.