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Optical Sensors for Space Situational Awareness

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

Deadline for manuscript submissions: 25 May 2024 | Viewed by 5045

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Special Issue Editor

Prof. Dr. Regina Lee

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Guest Editor

Department of Earth and Space Science and Engineering, York University, Toronto, ON, Canada
Interests: nanosatellite technologies; space object tracking; design of micro-sensors and actuators

Special Issue Information

Dear Colleagues,

Today, small satellites are replacing larger satellites for a variety of applications in a form of large constellations like Starlink, Planet and Globalstar. While this trend is promising in terms of low-cost solutions for space-based services like communication, resource monitoring, and weather forecasting, this sudden and rapid growth in space objects has also drawn increased attention to space situational awareness. In response to this issue of the growing population of Resident Space Objects (RSO), there has been significant effort in developing optical sensors to advance SSA capabilities. RSO observations is made through ground- and space-based optical telescopes and radar systems.

In the special edition, we present optical payload design from ground-based systems, low-cost optical imagers, dedicated high resolution cameras and other optical technologies that have been proposed and demonstrated for space situational awareness.

Prof. Dr. Regina Lee
Guest Editor

Manuscript Submission Information

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Keywords

Space Situational Awareness (SSA)
Resident Space Objects
optical camera
space object
space debris
object tracking
RSO detection

Published Papers (5 papers)

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Research

21 pages, 13440 KiB

Open AccessArticle

Stingray Sensor System for Persistent Survey of the GEO Belt

by Tanner Campbell, Adam Battle, Dan Gray, Om Chabra, Scott Tucker, Vishnu Reddy and Roberto Furfaro

Sensors 2024, 24(8), 2596; https://doi.org/10.3390/s24082596 - 18 Apr 2024

Viewed by 199

Abstract

The Stingray sensor system is a 15-camera optical array dedicated to the nightly astrometric and photometric survey of the geosynchronous Earth orbit (GEO) belt visible above Tucson, Arizona. The primary scientific goal is to characterize GEO and near-GEO satellites based on their observable properties. This system is completely autonomous in both data acquisition and processing, with human oversight reserved for data quality assurance and system maintenance. The 15 ZWO ASI1600MM Pro cameras are mated to Sigma 135 mm f/1.8 lenses and are controlled simultaneously by four separate computers. Each camera is fixed in position and observes a 7.6-by-5.8-degree portion of the GEO belt, for a total of a 114-by-5.8-degree field of regard. The GAIA DR2 star catalog is used for image astrometric plate solution and photometric calibration to GAIA G magnitudes. There are approximately 200 near-GEO satellites on any given night that fall within the Stingray field of regard, and all those with a GAIA G magnitude brighter than approximately 15.5 are measured by the automated data reduction pipeline. Results from an initial one-month survey show an aggregate photometric uncertainty of 0.062 ± 0.008 magnitudes and astrometric accuracy consistent with theoretical sub-pixel centroid limits. Provided in this work is a discussion of the design and function of the system, along with verification of the initial survey results. Full article

(This article belongs to the Special Issue Optical Sensors for Space Situational Awareness)

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22 pages, 34478 KiB

Open AccessArticle

Validation of a 3D Local-Scale Adaptive Solar Radiation Model by Using Pyranometer Measurements and a High-Resolution Digital Elevation Model

by Eduardo Rodríguez, Judit García-Ferrero, María Sánchez-Aparicio, José M. Iglesias, Albert Oliver-Serra, M. Jesús Santos, Paula Andrés-Anaya, J. Manuel Cascón, Gustavo Montero García, Alejandro Medina, Susana Lagüela, M. Isabel Asensio and Rafael Montenegro Armas

Sensors 2024, 24(6), 1823; https://doi.org/10.3390/s24061823 - 12 Mar 2024

Viewed by 560

Abstract

The result of the multidisciplinary collaboration of researchers from different areas of knowledge to validate a solar radiation model is presented. The MAPsol is a 3D local-scale adaptive solar radiation model that allows us to estimate direct, diffuse, and reflected irradiance for clear sky conditions. The model includes the adaptation of the mesh to complex orography and albedo, and considers the shadows cast by the terrain and buildings. The surface mesh generation is based on surface refinement, smoothing and parameterization techniques and allows the generation of high-quality adapted meshes with a reasonable number of elements. Another key aspect of the paper is the generation of a high-resolution digital elevation model (DEM). This high-resolution DEM is constructed from LiDAR data, and its resolution is two times more accurate than the publicly available DEMs. The validation process uses direct and global solar irradiance data obtained from pyranometers at the University of Salamanca located in an urban area affected by systematic shading from nearby buildings. This work provides an efficient protocol for studying solar resources, with particular emphasis on areas of complex orography and dense buildings where shadows can potentially make solar energy production facilities less efficient. Full article

(This article belongs to the Special Issue Optical Sensors for Space Situational Awareness)

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15 pages, 1200 KiB

Open AccessArticle

Classification of Low Earth Orbit (LEO) Resident Space Objects’ (RSO) Light Curves Using a Support Vector Machine (SVM) and Long Short-Term Memory (LSTM)

by Randa Qashoa and Regina Lee

Sensors 2023, 23(14), 6539; https://doi.org/10.3390/s23146539 - 20 Jul 2023

Cited by 3 | Viewed by 1289

Abstract

Light curves are plots of brightness measured over time. In the field of Space Situational Awareness (SSA), light curves of Resident Space Objects (RSOs) can be utilized to infer information about an RSO such as the type of object, its attitude, and its shape. Light curves of RSOs in geostationary orbit (GEO) have been a main research focus for many years due to the availability of long time series data spanning hours. Given that a large portion of RSOs are in low Earth orbit (LEO), it is of great importance to study trends in LEO light curves as well. The challenge with LEO light curves is that they tend to be short, typically no longer than a few minutes, which makes them difficult to analyze with typical time series techniques. This study presents a novel approach to observational LEO light curve classification. We extract features from light curves using a wavelet scattering transformation which is used as an input for a machine learning classifier. We performed light curve classification using both a conventional machine learning approach, namely a support vector machine (SVM), and a deep learning technique, long short-term memory (LSTM), to compare the results. LSTM outperforms SVM for LEO light curve classification with a 92% accuracy. This proves the viability of RSO classification by object type and spin rate from real LEO light curves. Full article

(This article belongs to the Special Issue Optical Sensors for Space Situational Awareness)

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18 pages, 5177 KiB

Open AccessArticle

Weak Spatial Target Extraction Based on Small-Field Optical System

by Xuguang Zhang, Yunmeng Liu, Huixian Duan and E Zhang

Sensors 2023, 23(14), 6315; https://doi.org/10.3390/s23146315 - 11 Jul 2023

Cited by 1 | Viewed by 873

Abstract

Compared to wide-field telescopes, small-field detection systems have higher spatial resolution, resulting in stronger detection capabilities and higher positioning accuracy. When detecting by small fields in synchronous orbit, both space debris and fixed stars are imaged as point targets, making it difficult to distinguish them. In addition, with the improvement in detection capabilities, the number of stars in the background rapidly increases, which puts higher requirements on recognition algorithms. Therefore, star detection is indispensable for identifying and locating space debris in complex backgrounds. To address these difficulties, this paper proposes a real-time star extraction method based on adaptive filtering and multi-frame projection. We use bad point repair and background suppression algorithms to preprocess star images. Afterwards, we analyze and enhance the target signal-to-noise ratio (SNR). Then, we use multi-frame projection to fuse information. Subsequently, adaptive filtering, adaptive morphology, and adaptive median filtering algorithms are proposed to detect trajectories. Finally, the projection is released to locate the target. Our recognition algorithm has been verified by real star images, and the images were captured using small-field telescopes. The experimental results demonstrate the effectiveness of the algorithm proposed in this paper. We successfully extracted hip-27066 star, which has a magnitude of about 12 and an SNR of about 1.5. Compared with existing methods, our algorithm has advantages in both recognition rate and false-alarm rate, and can be used as a real-time target recognition algorithm for space-based synchronous orbit detection payloads. Full article

(This article belongs to the Special Issue Optical Sensors for Space Situational Awareness)

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25 pages, 14584 KiB

Open AccessArticle

Angle-Only Cooperative Orbit Determination Considering Attitude Uncertainty

by Yishuai Shi, Junkui Wang, Chuankai Liu, Yangjun Wang, Qingchao Xu and Xingyu Zhou

Sensors 2023, 23(2), 718; https://doi.org/10.3390/s23020718 - 08 Jan 2023

Viewed by 1403

Abstract

In this paper, a novel concept for cooperative orbit determination (OD) using inter-spacecraft angle-only measurements is proposed. Different from the conventional cooperative OD that only estimates orbit states, the attitude of the observer spacecraft is considered by incorporating the attitude into the estimated vector. The observability of a two-spacecraft system is analyzed based on the observability matrix. Observability analysis reveals that inter-spacecraft angle-only measurements are inadequate to estimate both the attitude and the orbit states in two-body dynamics. The observability of the two-spacecraft system can be improved by considering high-order gravitational perturbation or executing an attitude maneuver on the observer spacecraft. This is the first time that we present the observability analysis and orbit estimation results for a two-spacecraft system considering attitude uncertainty for the observer. Finally, simulation results demonstrate the effectiveness of the proposed method. The results in this paper can be potentially useful for autonomous managements of a spacecraft constellation and formation. Full article

(This article belongs to the Special Issue Optical Sensors for Space Situational Awareness)

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