Situational Awareness Using Space-Based Sensor Networks

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

Deadline for manuscript submissions: 31 December 2025 | Viewed by 236

Special Issue Editors


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Guest Editor
School of Automation, Northwestern Polytechnical University, Xi’an 710129, China
Interests: data fusion; path planning; belief propagation; multi-armed bandits; sensor management

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Guest Editor
Qian Xuesen Laboratory of Space Technology, China Academy of Space Technology, Beijing 100094, China
Interests: swarm intelligence of spacecraft; navigation; control of distributed satellites

Special Issue Information

Dear Colleagues,

The rapid advancement of space-based sensor networking has significantly enhanced our ability to monitor and understand ground, maritime, air and space targets. Situational awareness, the ability to perceive, comprehend, and predict events in complex operational domains, is now increasingly reliant on the capabilities provided by satellites and other spaceborne platforms. This Special Issue, "Situational Awareness Using Space-Based Sensor Networks", seeks to explore the latest developments and innovations in this critical field.

Space-based sensor networks provide unparalleled vantage points for observing various targets and terrestrial, atmospheric, and space environments. From environmental protection and monitoring climate change to enhancing defense systems and air traffic management, these technologies play a vital role in ensuring security, sustainability, and operational efficiency. Advances in sensor fusion, artificial intelligence, and real-time data analytics have further enhanced the ability to derive actionable insights from diverse data sources.

This Special Issue welcomes contributions addressing various aspects of situational awareness using space-based sensor networks, including network system design, task planning, data processing, and resource scheduling. Research focused on innovative constellation designs, multi-sensor data fusion, and the application of emerging technologies, such as artificial intelligence, is particularly encouraged.

Through this Special Issue, we aim at highlighting cutting-edge research and fostering interdisciplinary collaboration, paving the way for transformative solutions in situational awareness using space-based sensor networks.

Dr. Zengfu Wang
Dr. Qingrui Zhou
Guest Editors

Manuscript Submission Information

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Keywords

  • space-based sensor networks
  • multi-source heterogeneous information fusion
  • target tracking
  • sensor resource management
  • distributed fusion
  • task planning
  • earth observation
  • space surveillance
  • satellite constellations

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Published Papers (1 paper)

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Review

36 pages, 6529 KiB  
Review
A Review of Wavefront Sensing and Control Based on Data-Driven Methods
by Ye Zhang, Qichang An, Min Yang, Lin Ma and Liang Wang
Aerospace 2025, 12(5), 399; https://doi.org/10.3390/aerospace12050399 - 30 Apr 2025
Abstract
Optical systems suffer from wavefront aberrations due to complex atmospheric environments and system component errors, leading to systematic aberrations and significantly degrading optical field quality. Therefore, the detection and correction of optical aberrations are crucial for efficient and accurate observations. To fully utilize [...] Read more.
Optical systems suffer from wavefront aberrations due to complex atmospheric environments and system component errors, leading to systematic aberrations and significantly degrading optical field quality. Therefore, the detection and correction of optical aberrations are crucial for efficient and accurate observations. To fully utilize the capabilities of observation equipment and achieve high-efficiency, accurate imaging, it is essential to develop wavefront correction technologies that enable ultra-precise wavefront control. The application of data-driven techniques in wavefront correction can effectively enhance correction performance and better address complex environmental challenges. This paper elaborates on the research progress of data-driven methods in wavefront correction from three aspects: principles, current research status, and practical applications. It analyzes the performance of data-driven methods in diverse real-world scenarios and discusses future trends in the deep integration of data-driven approaches with optical technologies. This work provides valuable guidance for advancing wavefront correction methodologies. Full article
(This article belongs to the Special Issue Situational Awareness Using Space-Based Sensor Networks)
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