Track Detection of Resident Space Objects

A special issue of Aerospace (ISSN 2226-4310). This special issue belongs to the section "Astronautics & Space Science".

Deadline for manuscript submissions: closed (31 January 2024) | Viewed by 1489

Special Issue Editor


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Guest Editor
Institute of Space Sciences and Astronomy, University of Malta, L-Università ta' Malta, Msida MSD 2080, Malta
Interests: radio astronomy; space surveillance and tracking; signal and image processing; high performance and GPU computing

Special Issue Information

Dear Colleagues,

As humanity’s endeavours in space continue to expand and evolve, the space around our planet is becoming an increasingly vital and contested domain. The burgeoning population of Resident Space Objects (RSOs), including operational satellites, defunct satellites, rocket bodies, and debris, poses a considerable challenge to the safety and sustainability of space operations. This edition invites submissions on cutting-edge techniques and technologies focused on track detection of RSOs in Earth's orbit. With the escalation of space activities and the consequent growth in the number of RSOs, precise tracking is paramount for collision avoidance and mission safety. We encourage submissions that explore advancements in a wide spectrum of instruments, including phased array radars, optical telescopes, in-orbits systems and others. We are particularly interested in studies on the incorporation of machine learning algorithms in data processing for faster and more reliable tracking of RSO trajectories. Through this Special Issue, we aim to foster a deeper understanding and stimulate further innovation in the field of RSO tracking.

Prof. Dr. Alessio Magro
Guest Editor

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Keywords

  • track detection
  • streak detection
  • resident space objects
  • space debris
  • low earth orbit
  • machine learning
  • satellite tracking
  • space surveillance
  • space situational awareness
  • space safety
  • orbit determination
  • radar systems
  • optical systems

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Published Papers (1 paper)

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Research

25 pages, 2095 KiB  
Article
Operational Angular Track Reconstruction in Space Surveillance Radars through an Adaptive Beamforming Approach
by Marco Felice Montaruli, Maria Alessandra De Luca, Mauro Massari, Germano Bianchi and Alessio Magro
Aerospace 2024, 11(6), 451; https://doi.org/10.3390/aerospace11060451 - 1 Jun 2024
Viewed by 1169
Abstract
In the last few years, many space surveillance initiatives have started to consider the problem represented by resident space object overpopulation. In particular, the European Space Surveillance and Tracking (EUSST) consortium is in charge of providing services like collision avoidance, fragmentation analysis, and [...] Read more.
In the last few years, many space surveillance initiatives have started to consider the problem represented by resident space object overpopulation. In particular, the European Space Surveillance and Tracking (EUSST) consortium is in charge of providing services like collision avoidance, fragmentation analysis, and re-entry, which rely on measurements obtained through ground-based sensors. BIRALES is an Italian survey radar belonging to the EUSST framework and is capable of providing measurements including Doppler shift, slant range, and angular profile. In recent years, the Music Approach for Track Estimate and Refinement (MATER) algorithm has been developed to retrieve angular tracks through an adaptive beamforming technique, guaranteeing the generation of more accurate and robust measurements with respect to the previous static beamforming approach. This work presents the design of a new data processing chain to be used by BIRALES to compute the angular track. The signal acquired by the BIRALES receiver array is down-converted and the receiver bandwidth is split into multiple channels, in order to maximize the signal-to-noise ratio of the measurements. Then, the signal passes through a detection block, where an isolation procedure creates, for each epoch, signal correlation matrices (CMs) related to the channels involved in the detection and then processes them to isolate the data stream related to a single detected source. Consequently, for each epoch and for each detected source, just the CM featuring the largest signal contribution is kept, allowing deriving the Doppler shift measurement from the channel illumination sequence. The MATER algorithm is applied to each CM stream, first estimating the signal directions of arrival, then grouping them in the observation time window, and eventually returning the target angular track. Ambiguous estimates may be present due to the configuration of the receiver array, which cause spatial aliasing phenomena. This problem can be addressed by either exploiting transit prediction (in the case of cataloged objects), or by applying tailored criteria (for uncatalogued objects). The performance of the new architecture was assessed in real operational scenarios, demonstrating the enhancement represented by the implementation of the channelization strategy, as well as the angular measurement accuracy returned by MATER, in both nominal and off-nominal scenarios. Full article
(This article belongs to the Special Issue Track Detection of Resident Space Objects)
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