Recognition of objects in orbit and their intentions with space‐borne sub‐THz Inverse Synthetic Aperture Radar

An important aspect of Space Situational Awareness is to estimate the intent of objects in space. This paper discusses how discriminating features can be obtained from Inverse Synthetic Aperture Radar images of such objects and how these discriminators can be used to recognise the objects or to esti...

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Veröffentlicht in:IET Radar, Sonar & Navigation Sonar & Navigation, 2024-04, Vol.18 (4), p.564-576
Hauptverfasser: Cherniakov, Mikhail, Hoare, Edward G., Gashinova, Marina, Marchetti, Emidio, Stove, Andrew G.
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Sprache:eng
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Zusammenfassung:An important aspect of Space Situational Awareness is to estimate the intent of objects in space. This paper discusses how discriminating features can be obtained from Inverse Synthetic Aperture Radar images of such objects and how these discriminators can be used to recognise the objects or to estimate their intent. If the object is, for example, a satellite of a known type, the scheme proposed is able to recognise it. The ability of the scheme to detect damage to the object is also discussed. The focus is on imagery obtained in the sub‐terahertz band (typically 300 GHz) because of the greater imaging capability given by the diffuse scattering which is observed at these frequencies. The paper also discusses the importance of being able to use images obtained by electromagnetic simulation to be able to train the subsystem which recognises features of the objects and describes a practical scheme for creating these simulations for large objects at these very short wavelengths. The paper describes a processing scheme to extract discriminating features from Inverse Synthetic Aperture Radar images of objects in space and how these discriminators can be used to recognise or to estimate the intention of these objects. It describes how electromagnetic simulation can be used to create images to train the object recognition subsystem, in the sub‐terahertz band (typically 300 GHz). It describes using an expert system and also a Bayesian approach to estimate an object's intent from its features.
ISSN:1751-8784
1751-8792
DOI:10.1049/rsn2.12513