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Sensing for Space Applications (Volume II)

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

Deadline for manuscript submissions: closed (21 March 2024) | Viewed by 4814

Special Issue Editor


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Guest Editor
Department of Computer Science, North Dakota State University, Fargo, ND 58102, USA
Interests: artificial/computational Intelligence; autonomy applications in aerospace; cybersecurity; 3D printing command/control and assessment; educational assessment in computing disciplines
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

This Special Issue is a continuation of our previous Special Issue, “Sensing for Space Applications”.

Many space missions are launched specifically for remote sensing purposes. Some missions conduct Earth sensing, while others are launched to identify distant planets, moons, and asteroids. Some seek to conduct sensing far beyond the reach of mankind’s current spacecrafts. Even missions in which sensing is not the primary purpose use sensors for mission operations. This Special Issue focuses on the sensing needs, sensing solutions, and sensors used for these space applications, whether in orbit or on the surface of a distant celestial body.

Dr. Jeremy Straub
Guest Editor

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Keywords

  • space
  • orbit
  • sensing
  • deep space
  • moon
  • Mars
  • asteroid
  • sensing systems
  • sensors

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Published Papers (2 papers)

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Research

18 pages, 680 KiB  
Article
Comparative Analysis of Resident Space Object (RSO) Detection Methods
by Vithurshan Suthakar, Aiden Alexander Sanvido, Randa Qashoa and Regina S. K. Lee
Sensors 2023, 23(24), 9668; https://doi.org/10.3390/s23249668 - 7 Dec 2023
Cited by 5 | Viewed by 2311
Abstract
In recent years, there has been a significant increase in satellite launches, resulting in a proliferation of satellites in our near-Earth space environment. This surge has led to a multitude of resident space objects (RSOs). Thus, detecting RSOs is a crucial element of [...] Read more.
In recent years, there has been a significant increase in satellite launches, resulting in a proliferation of satellites in our near-Earth space environment. This surge has led to a multitude of resident space objects (RSOs). Thus, detecting RSOs is a crucial element of monitoring these objects and plays an important role in preventing collisions between them. Optical images captured from spacecraft and with ground-based telescopes provide valuable information for RSO detection and identification, thereby enhancing space situational awareness (SSA). However, datasets are not publicly available due to their sensitive nature. This scarcity of data has hindered the development of detection algorithms. In this paper, we present annotated RSO images, which constitute an internally curated dataset obtained from a low-resolution wide-field-of-view imager on a stratospheric balloon. In addition, we examine several frame differencing techniques, namely, adjacent frame differencing, median frame differencing, proximity filtering and tracking, and a streak detection method. These algorithms were applied to annotated images to detect RSOs. The proposed algorithms achieved a competitive degree of success with precision scores of 73%, 95%, 95%, and 100% and F1 scores of 68%, 77%, 82%, and 79%. Full article
(This article belongs to the Special Issue Sensing for Space Applications (Volume II))
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17 pages, 8965 KiB  
Article
Timepix3: Compensation of Thermal Distortion of Energy Measurement
by Martin Urban, Ondrej Nentvich, Lukas Marek, David Hladik, Rene Hudec and Ladislav Sieger
Sensors 2023, 23(6), 3362; https://doi.org/10.3390/s23063362 - 22 Mar 2023
Viewed by 2037
Abstract
The Timepix3 is a hybrid pixellated radiation detector consisting of a 256 px × 256 px radiation-sensitive matrix. Research has shown that it is susceptible to energy spectrum distortion due to temperature variations. This can lead to a relative measurement error of up [...] Read more.
The Timepix3 is a hybrid pixellated radiation detector consisting of a 256 px × 256 px radiation-sensitive matrix. Research has shown that it is susceptible to energy spectrum distortion due to temperature variations. This can lead to a relative measurement error of up to 35% in the tested temperature range of 10 °C to 70 °C. To overcome this issue, this study proposes a complex compensation method to reduce the error to less than 1%. The compensation method was tested with different radiation sources, focusing on energy peaks up to 100 keV. The results of the study showed that a general model for temperature distortion compensation could be established, where the error in the X-ray fluorescence spectrum of Lead (74.97 keV) was reduced from 22% to less than 2% for 60 °C after the correction was applied. The validity of the model was also verified at temperatures below 0 °C, where the relative measurement error for the Tin peak (25.27 keV) was reduced from 11.4% to 2.1% at 40 °C. The results of this study demonstrate the effectiveness of the proposed compensation method and models in significantly improving the accuracy of energy measurements. This has implications for various fields of research and industry that require accurate radiation energy measurements and cannot afford to use power for cooling or temperature stabilisation of the detector. Full article
(This article belongs to the Special Issue Sensing for Space Applications (Volume II))
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