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An increasing number of space objects, debris, and satellites in Low Earth Orbit poses a significant threat of collisions during space operations. The situation is currently monitored by radar and radio-telescopes that track space objects, but much of space debris is composed of very small metallic objects that are difficult to detect.<\/p>\n
In a study published in IET Radar, Sonar & Navigation<\/i>, investigators demonstrate the benefits of using deep learning\u2014a form of artificial intelligence\u2014for small space object detection by radar.<\/p>\n
The team modeled a prominent radar system in Europe (called Tracking and Imaging Radar) in tracking mode to produce training and testing data. Then, the group compared classical detection systems with a You-Only-Look-Once (YOLO)\u2013based detector. (YOLO is a popular object detection algorithm that has been widely used in computer vision applications.)<\/p>\n
An evaluation in a simulated environment demonstrated that YOLO-based detection outperforms conventional approaches, guaranteeing a high detection rate while keeping false alarm rates low.<\/p>\n
“In addition to improving space surveillance capabilities, artificial intelligence\u2013based systems like YOLO have the potential to revolutionize space debris management,” said co\u2013corresponding author Federica Massimi, Ph.D., of Roma Tre University, in Italy.<\/p>\n
“By quickly identifying and tracking hard-to-detect objects, these systems enable proactive decision-making and intervention strategies to mitigate collisions and risks and preserve the integrity of critical space resources.”<\/p>\n
More information:<\/strong> \t\t\t\t\t\t\t\t\t\t<\/p>\n \n\t\t\t\t\t\t\t\t\t\t\t\tCitation<\/strong>: \n\t\t\t\t\t\t\t\t\t\t\t This document is subject to copyright. Apart from any fair dealing for the purpose of private study or research, no
\n\t\t\t\t\t\t\t\t\t\t\t\tFederica Massimi et al, Deep learning\u2010based space debris detection for space situational awareness: A feasibility study applied to the radar processing, IET Radar, Sonar & Navigation<\/i> (2024). DOI: 10.1049\/rsn2.12547<\/p>\n<\/div>\n
\n\t\t\t\t\t\t\t\t\t\t\t\tStudy find potential benefits in AI\u2013based systems for spotting hard-to-detect space debris (2024, March 6)
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\n\t\t\t\t\t\t\t\t\t\t\t part may be reproduced without the written permission. The content is provided for information purposes only.\n\t\t\t\t\t\t\t\t\t\t\t <\/p>\n<\/p><\/div>\n<\/p><\/div>\n