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Autonomous Space Navigation (Second Edition)

A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Satellite Missions for Earth and Planetary Exploration".

Deadline for manuscript submissions: 30 September 2025 | Viewed by 997

Special Issue Editors


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Guest Editor
1. Samsung Semiconductor, Inc., San Jose, CA 95134, USA
2. Department of Aerospace, California Institute of Technology, Pasadena, CA 91125, USA
Interests: navigation; positioning; sensor fusion; GNSS; INS; computer vision; robotics; estimation; autonomy; spacecraft; smartphones
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
Department of Industrial Engineering, University of Naples Federico II, Piazzale Tecchio 80, 80125 Naples, Italy
Interests: spacecraft guidance; navigation and control; spacecraft relative navigation; pose determination; electro-optical sensors; LIDAR; star tracker; unmanned aerial vehicles; autonomous navigation; sense and avoid; visual detection and tracking
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Navigation is a key functionality for existing and next-generation space missions. In many cases, due to Earth-to-space communication delays and a lack of coverage, absolute and relative navigation must be directly performed on board and in real-time to enable autonomous guidance and control. To do so, several technologies and algorithms can be used, depending on the specific application, the operational environment, the required accuracy and robustness, the characteristics of the space vehicle, as well as other mission-related constraints.

Although numerous solutions have already been proposed or successfully adopted in actual space missions, next-generation capabilities, such as spacecraft formation flying, highly accurate landings, proximity operations, advanced pointing precision, interplanetary trajectory or advanced robotic surface exploration require further advancements in autonomous navigation. This is especially true when using very small space vehicles, for which the accuracy, robustness and autonomy are typically limited due to on-board constraints such as power, mass, volume and computational resources.

This Special Issue aims to present an overview of recent research trends on this matter. It encourages the submission of original research articles and state-of-the-art reviews from academia and industry that focus on innovative technologies, methods and algorithms for the autonomous navigation of spacecraft when orbiting in proximity of other space objects. The scope of this Special Issue includes, but is not limited to, the following:

Technologies, methods and algorithms for autonomous absolute spacecraft navigation, based on the use of GNSS, IMU, star trackers, and other sensors;

Spacecraft relative navigation and pose determination using GNSS, RF ranging and/or electro optical sensors;

Autonomous navigation and situational awareness in deep space exploration scenarios (e.g., hazard detection and precise landing);

Design, integration, and calibration of innovative multi-sensor-based architectures for spacecraft navigation;

Artificial intelligence and machine learning for autonomous spacecraft navigation.

Dr. Vincenzo Capuano
Dr. Roberto Opromolla
Guest Editors

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. Remote Sensing 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 2700 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

  • spacecraft navigation

  • spacecraft pose estimation
  • autonomy
  • GNSS
  • inertial sensors
  • star trackers
  • autonomous planetary landing
  • computer vision
  • Artificial Intelligence
  • machine learning

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Related Special Issue

Published Papers (2 papers)

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Research

25 pages, 4712 KiB  
Article
Improving Angle-Only Orbit Determination Accuracy for Earth–Moon Libration Orbits Using a Neural-Network-Based Approach
by Zhe Zhang, Yishuai Shi and Zuoxiu Zheng
Remote Sens. 2024, 16(17), 3287; https://doi.org/10.3390/rs16173287 - 4 Sep 2024
Viewed by 373
Abstract
In the realm of precision space applications, improving the accuracy of orbit determination (OD) is a crucial and demanding task, primarily because of the presence of measurement noise. To address this issue, a novel machine learning method based on bidirectional long short-term memory [...] Read more.
In the realm of precision space applications, improving the accuracy of orbit determination (OD) is a crucial and demanding task, primarily because of the presence of measurement noise. To address this issue, a novel machine learning method based on bidirectional long short-term memory (BiLSTM) is proposed in this research. In particular, the proposed method aims to improve the OD accuracy of Earth–Moon Libration orbits with angle-only measurements. The proposed BiLSTM network is designed to detect inaccurate measurements during an OD process, which is achieved by incorporating the least square method (LSM) as a basic estimation approach. The structure, inputs, and outputs of the modified BiLSTM network are meticulously crafted for the detection of inaccurate measurements. Following the detection of inaccurate measurements, a compensating strategy is devised to modify these detection results and thereby reduce their negative impact on OD accuracy. The modified measurements are then used to obtain a more accurate OD solution. The proposed method is applied to solve the OD problem of a 4:1 synodic resonant near-rectilinear halo orbit around the Earth–Moon L2 point. The training results reveal that the bidirectional network structure outperforms the regular unidirectional structures in terms of detection accuracy. Numerical simulations show that the proposed method can reduce the estimated error by approximately 10%. The proposed method holds significant potential for future missions in cislunar space. Full article
(This article belongs to the Special Issue Autonomous Space Navigation (Second Edition))
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26 pages, 3287 KiB  
Article
Assessment of Satellite Differential Code Biases and Regional Ionospheric Modeling Using Carrier-Smoothed Code of BDS GEO and IGSO Satellites
by Xiao Gao, Zongfang Ma, Lina Shu, Lin Pan, Hailong Zhang and Shuai Yang
Remote Sens. 2024, 16(17), 3118; https://doi.org/10.3390/rs16173118 - 23 Aug 2024
Viewed by 317
Abstract
The geostationary earth orbit (GEO) represents a distinctive geosynchronous orbit situated in the Earth’s equatorial plane, providing an excellent platform for long-term monitoring of ionospheric total electron content (TEC) at a quasi-invariant ionospheric pierce point (IPP). With GEO satellites having limited dual-frequency coverage, [...] Read more.
The geostationary earth orbit (GEO) represents a distinctive geosynchronous orbit situated in the Earth’s equatorial plane, providing an excellent platform for long-term monitoring of ionospheric total electron content (TEC) at a quasi-invariant ionospheric pierce point (IPP). With GEO satellites having limited dual-frequency coverage, the inclined geosynchronous orbit (IGSO) emerges as a valuable resource for ionospheric modeling across a broad range of latitudes. This article evaluates satellite differential code biases (DCB) of BDS high-orbit satellites (GEO and IGSO) and assesses regional ionospheric modeling utilizing data from international GNSS services through a refined polynomial method. Results from a 48-day observation period show a stability of approximately 2.0 ns in BDS satellite DCBs across various frequency signals, correlating with the available GNSS stations and satellites. A comparative analysis between GEO and IGSO satellites in BDS2 and BDS3 reveals no significant systematic bias in satellite DCB estimations. Furthermore, high-orbit BDS satellites exhibit considerable potential for promptly detecting high-resolution fluctuations in vertical TECs compared to conventional geomagnetic activity indicators like Kp or Dst. This research also offers valuable insights into ionospheric responses over mid-latitude regions during the March 2024 geomagnetic storm, utilizing TEC estimates derived from BDS GEO and IGSO satellites. Full article
(This article belongs to the Special Issue Autonomous Space Navigation (Second Edition))
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