Track detection of high-velocity resident space objects in Low Earth Orbit

• Published in: Advances in space research 2023-02, Vol.71 (3), p.1670-1681
• Main Authors: Cutajar, D., Magro, A., Borg, J., Zarb Adami, K., Bianchi, G., Maccaferri, A., Mattana, A., Naldi, G., Pupillo, G.
• Format: Article
• Language: English
• Subjects: Radar; Remote sensing; Space debris; Track detection
• ISSN: 0273-1177
• DOI: 10.1016/j.asr.2022.09.053

•A review of track detection algorithms across different research fields.•Technical description of the initiation, maintenance and termination of a radar track in the BIRALES radar.•Presentation of a new track detection strategy that is used for the detection of orbital debris using a bi-static continuous-wave radar.•Performance evaluation of this new track detection method on synthetic data. The world’s economy has become heavily dependent on the services provided by satellites. With the exponential increase in satellite launches, the population of defunct or inactive hardware in space has grown substantially. This is especially true in sensitive orbits such as the Low Earth Orbit (LEO) and Geostationary Earth Orbit (GEO) regimes. These objects, collectively known as orbital debris, can reach speeds of up to 28 000km h−1 in LEO. At these orbital speeds, even the smallest of objects can pose a considerable threat to operational satellites or astronauts. This makes the monitoring, and detection, of these objects of the utmost importance. This work describes the latest detection strategy used in one of Europe’s largest Space Situational Awareness (SSA) installation; the BIstatic RAdar for LEo Survey (BIRALES) space debris radar. We present a novel bottom-up approach that makes use of single-linkage clustering to identify faint radar streaks in spectrogram data. Tests on synthetic data have shown that the detection strategy presented in this study obtains a higher detection rate when it is compared against existing methods. Unlike other approaches, this detection strategy, using the Multi-beam streak detection strategy (MSDS) algorithm, was still able to recall 90% of the track information at an Signal-to-Noise Ratio (SNR) of 2dB.