Advanced Processing Methods for Long Baseline Multistatic Radars for Space Situational Awareness

Since their inception, ground-based Space Situational Awareness (SSA) systems, also known as Space Surveillance and Tracking (SST), primarily utilise radar sensors due to their ability to operate in very long ranges and under various atmospheric conditions while also providing very accurate range measurements. Initially used for early missile warning, modern SST radars are designed to monitor targets in Low Earth Orbit (LEO) up to deep space. Having very high-power transmissions, to improve their efficiency radar can also operate in tandem with nearby radio telescopes forming what is known as bistatic configuration.

Recently, the use of long baseline bistatic radar systems for SST was proposed. The difference with existing bistatic systems is that the RF telescopes are remotely located from the radar allowing larger bistatic angles and essentially viewing the target from different aspect angles, forming a long baseline bistatic radar.

This project will investigate the concept of such long baseline SST systems in multistatic (2 or more receivers) configurations. The advantage of such a system is that multiple observations of a target can be acquired from a single transmission point. Furthermore, by exploiting multiple remote receivers, the target can be observed from different aspect angles which can be extremely beneficial for detection and identification purposes.

The research aims to develop novel processing solutions to enhance the capability to detect and monitor space targets from this innovative sensing scenario. The main objectives will include the development of algorithms for advanced multistatic Inverse Synthetic Aperture Imaging for target attitude estimation, AI/ML based space target recognition and target manoeuvre detection/classification.