Please use this identifier to cite or link to this item: https://www.um.edu.mt/library/oar/handle/123456789/102727
Title: Track detection of high-velocity resident space objects in Low Earth Orbit
Authors: Cutajar, Denis
Magro, Alessio
Borg, Josef
Bianchi, Germano
Maccaferri, Andrea
Mattana, Andrea
Naldi, Giovanni
Pupillo, Giuseppe
Keywords: Aerospace engineering
Remote sensing
Space debris -- Tracking
Issue Date: 2022
Publisher: Elsevier Ltd.
Citation: Cutajar, D., Magro, A., Borg, J., Bianchi, G., Maccaferri, A. Mattana, A., Naldi, G. & Pupillo, G. (2022). Track detection of high-velocity resident space objects in Low Earth Orbit. Advances in Space Research, 10.1016/j.asr.2022.09.053
Abstract: 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.
URI: https://www.um.edu.mt/library/oar/handle/123456789/102727
Appears in Collections:Scholarly Works - InsSSA

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