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Sensors for Space Situational Awareness and Object Tracking
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Sensors for Space Situational Awareness and Object Tracking

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Physical Sensors".

Deadline for manuscript submissions: 31 December 2025 | Viewed by 782

Special Issue Editor

Prof. Dr. Regina Lee

E-Mail Website
Guest Editor
Department of Earth and Space Science, York University, Toronto, ON M3J 1P3, Canada
Interests: satellite technologies; SSA; small satlelites
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Space situational awareness (SSA)—to detect, track, identify, and characterise resident space objects (RSOs)–has been recognised in the research community as one of the top priorities for space activities in Canada. Damage to space systems has a significant and immediate impact on the technologies we all rely on daily, including navigation, communication, resource management, climate monitoring, and severe weather forecasting. According to NASA, there are more than 22,000 objects that are larger than 10 cm in diameter orbiting today, with a total number of 500,000 under 10 cm; only 86% of the objects have been identified. The remaining 14% are uncatalogued and unidentified objects (such as debris) that pose threats to space assets like the International Space Station. SSA brings attention to the infrastructures of space that are increasingly central to our earthly existence and sites of concern for the future. As such, it is imperative to enhance the technologies and further develop the capabilities that identify both active satellites and debris.To meet the growing demand for SSA missions, several sensor technologies have been proposed to be suitable for both ground-based and space-based object imaging including SWIR, neuromorphic cameras, wide FOV cameras, and more. This Special Issue is dedicated to featuring innovative and cutting-edge sensor technologies for SSA applications.

Prof. Dr. Regina Lee
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sensors is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • space situational awareness
  • object tracking
  • RSO detection

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Published Papers (2 papers)

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Research

14 pages, 2045 KiB  
Article
Efficient Multi-Threaded Data Starting Point Matching Method for Space Target Cataloging
by Jiannan Sun, Zhe Kang, Zhenwei Li and Cunbo Fan
Sensors 2025, 25(8), 2367; https://doi.org/10.3390/s25082367 - 8 Apr 2025
Viewed by 208
Abstract
Currently, multi-target survey telescope arrays play an important role in the build-up and maintenance of space object catalog databases, collecting massive observational data without attributing information. However, the matching process of massive observational data poses significant challenges to traditional prediction methods. To address [...] Read more.
Currently, multi-target survey telescope arrays play an important role in the build-up and maintenance of space object catalog databases, collecting massive observational data without attributing information. However, the matching process of massive observational data poses significant challenges to traditional prediction methods. To address the issues of low matching success rates and prolonged computation times in traditional methods, this paper proposes a multi-threaded data starting point matching method. First, orbital elements from the Space Surveillance and Tracking (SST) database are extracted for two days before and after the observation moment. A set of orbital elements closest to the observation epoch is filtered to form the primary candidate catalog containing the maximum number of objects. A matching error threshold is set. Second, multi-threaded traversal of the primary candidate catalog is performed to calculate observation residuals with the data starting point using an orbit prediction procedure. Orbital elements meeting the triple matching error threshold are selected to form the secondary candidate catalog, which is used in the entire data arc segment-matching calculation. Finally, the root mean square error (RMSE) of observation residuals for the entire data arc segment is computed point by point. The orbital elements satisfying the matching threshold are identified as matching results based on the principle of optimality. Experimental results demonstrate that with a matching error threshold of 1°, the proposed method achieves an average matching success rate of 97.62% for data arc segments with nearly 10,000 passes per day over 8 consecutive days. In the SST database containing an average of 25,720 targets, this method processes an average of 2164 data arc segments per minute, improving matching efficiency by 115 times compared to traditional prediction methods. Full article
(This article belongs to the Special Issue Sensors for Space Situational Awareness and Object Tracking)
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30 pages, 11088 KiB  
Article
Space Surveillance with High-Frequency Radar
by Brendan Hennessy, Heath Yardley, Rob Debnam, Tristan A. Camilleri, Nicholas K. Spencer, David A. Holdsworth, Goeff Warne, Brian Cheung and Sergey Kharabash
Sensors 2025, 25(7), 2302; https://doi.org/10.3390/s25072302 - 4 Apr 2025
Viewed by 408
Abstract
High-Frequency (HF) radar is well suited to the surveillance of low-earth-orbit space. For large targets, a small deployable HF radar is able to match the detection performance of much larger space surveillance radar systems operating at higher frequencies. However, there are some unique [...] Read more.
High-Frequency (HF) radar is well suited to the surveillance of low-earth-orbit space. For large targets, a small deployable HF radar is able to match the detection performance of much larger space surveillance radar systems operating at higher frequencies. However, there are some unique challenges associated with the use of HF, including the range–Doppler coupling bias, coarse detection-level localisation, and the presence of meteor returns and other unwanted signals. This paper details the use of HF radar for space surveillance, including signal processing and radar product formation, tracking, ionospheric correction, and orbit determination. It is shown that by fusing measurements from multiple passes, accurate orbital estimates can be obtained. Included are results from recent SpaceFest trials of the Defence Science and Technology Group’s HF space surveillance radar, achieving real-time wide-area surveillance in tracking, orbit determination, and cueing of other space surveillance sensors. Full article
(This article belongs to the Special Issue Sensors for Space Situational Awareness and Object Tracking)
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