Aerospace

22 pages, 7280 KiB

Open AccessArticle

A Multi-Pointer Network for Multiple Agile Optical Satellite Scheduling Problem

by Zheng Liu, Wei Xiong, Chi Han and Kai Zhao

Aerospace 2024, 11(10), 792; https://doi.org/10.3390/aerospace11100792 - 25 Sep 2024

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With the rapid growth in space-imaging demands, the scheduling problem of multiple agile optical satellites has become a crucial problem in the field of on-orbit satellite applications. Because of the considerable solution space and complicated constraints, the existing methods suffer from a huge computation burden and a low solution quality. This paper establishes a mathematical model of this problem, which aims to maximize the observation profit rate and realize the load balance, and proposes a multi-pointer network to solve this problem, which adopts multiple attention layers as the pointers to construct observation action sequences for multiple satellites. In the proposed network, a local feature-enhancement strategy, a remaining time-based decoding sorting strategy, and a feasibility-based task selection strategy are developed to improve the solution quality. Finally, extensive experiments verify that the proposed network outperforms the comparison algorithms in terms of solution quality, computation efficiency, and generalization ability and that the proposed three strategies significantly improve the solving ability of the proposed network. Full article

(This article belongs to the Topic Techniques and Science Exploitations for Earth Observation and Planetary Exploration)

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15 pages, 27831 KiB

Open AccessArticle

Wind Field Reconstruction Method Using Incomplete Wind Data Based on Vision Mamba Decoder Network

by Min Chen, Haonan Wang, Wantong Chen and Shiyu Ren

Aerospace 2024, 11(10), 791; https://doi.org/10.3390/aerospace11100791 - 25 Sep 2024

Viewed by 306

Abstract

Accurate meteorological information is crucial for the safety of civil aviation flights. Complete wind field information is particularly helpful for planning flight routes. To address the challenge of accurately reconstructing wind fields, this paper introduces a deep learning neural network method based on the Vision Mamba Decoder. The goal of the method is to reconstruct the original complete wind field from incomplete wind data distributed along air routes. This paper proposes improvements to the Vision Mamba model to fit our mission, showing that the developed model can accurately reconstruct the complete wind field. The experimental results demonstrate a mean absolute error (MAE) of wind speed of approximately 1.83 m/s, a mean relative error (MRE) of around 7.87%, an R-square value of about 0.92, and an MAE of wind direction of 5.78 degrees. Full article

(This article belongs to the Section Air Traffic and Transportation)

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23 pages, 8683 KiB

Open AccessArticle

MicroGravity Explorer Kit (MGX): An Open-Source Platform for Accessible Space Science Experiments

by Waldenê de Melo Moura, Carlos Renato dos Santos, Moisés José dos Santos Freitas, Adriano Costa Pinto, Luciana Pereira Simões and Alison Moraes

Aerospace 2024, 11(10), 790; https://doi.org/10.3390/aerospace11100790 - 25 Sep 2024

Viewed by 327

Abstract

The study of microgravity, a condition in which an object experiences near-zero weight, is a critical area of research with far-reaching implications for various scientific disciplines. Microgravity allows scientists to investigate fundamental physical phenomena influenced by Earth’s gravitational forces, opening up new possibilities in fields such as materials science, fluid dynamics, and biology. However, the complexity and cost of developing and conducting microgravity missions have historically limited the field to well-funded space agencies, universities with dedicated government funding, and large research institutions, creating a significant barrier to entry. This paper presents the MicroGravity Explorer Kit’s (MGX) design, a multifunctional platform for conducting microgravity experiments aboard suborbital rocket flights. The MGX aims to democratize access to microgravity research, making it accessible to high school students, undergraduates, and researchers. To ensure that the tool is versatile across different scenarios, the authors conducted a comprehensive literature review on microgravity experiments, and specific requirements for the MGX were established. The MGX is designed as an open-source platform that supports various experiments, reducing costs and accelerating development. The multipurpose experiment consists of a Jetson Nano computer with multiple sensors, such as inertial sensors, temperature and pressure, and two cameras with up to 4k resolution. The project also presents examples of codes for data acquisition and compression and the ability to process images and run machine learning algorithms to interpret results. The MGX seeks to promote greater participation and innovation in space sciences by simplifying the process and reducing barriers to entry. The design of a platform that can democratize access to space and research related to space sciences has the potential to lead to groundbreaking discoveries and advancements in materials science, fluid dynamics, and biology, with significant practical applications such as more efficient propulsion systems and novel materials with unique properties. Full article

(This article belongs to the Section Astronautics & Space Science)

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18 pages, 7423 KiB

Open AccessArticle

A High-Reliability Photoelectric Detection System for Mars Sample Return’s Orbiting Sample

by William F. Church, David Guzman-Garcia, Karina Bertelsmann, Victor A. Ruiz-Escribano, Cesar Ventura, Molly I. Jackson and Eric Waltman

Aerospace 2024, 11(10), 789; https://doi.org/10.3390/aerospace11100789 - 24 Sep 2024

Viewed by 410

Abstract

The Mars Sample Return campaign is an endeavor of unprecedented technological complexity and coordination that attempts to answer fundamental questions about the habitability of Mars by returning the first samples of Martian material to Earth for analysis. The third mission in the campaign consists of the NASA-provided Capture, Containment, and Return System (CCRS) onboard the European Space Agency’s Earth Return Orbiter, which will retrieve the Orbiting Sample (OS) container from its orbit around Mars. Retrieving a passive sample container from a planetary orbit has never been attempted by any spacecraft and requires the development of new technology to succeed in this ambitious task. This paper introduces the high-reliability Capture Sensor Suite (CSS), a novel optical detection system that provides CCRS with the capability to autonomously detect the OS as it is captured. This article will discuss the challenges and requirements for the fault-tolerant design of the CSS. Full article

(This article belongs to the Special Issue Spacecraft Sample Collection)

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23 pages, 3487 KiB

Open AccessArticle

Design and Experimental Validation of an Adaptive Multi-Layer Neural Network Observer-Based Fast Terminal Sliding Mode Control for Quadrotor System

by Zainab Akhtar, Syed Abbas Zilqurnain Naqvi, Yasir Ali Khan, Mirza Tariq Hamayun and Salman Ijaz

Aerospace 2024, 11(10), 788; https://doi.org/10.3390/aerospace11100788 - 24 Sep 2024

Viewed by 385

Abstract

This study considers the numerical design and practical implementation of a new multi-layer neural network observer-based control design technique for unmanned aerial vehicles systems. Initially, an adaptive multi-layer neural network-based Luenberger observer is designed for state estimation by employing a modified back-propagation algorithm. The proposed observer’s adaptive nature aids in mitigating the impact of noise, disturbance, and parameter variations, which are usually not considered by conventional observers. Based on the observed states, a nonlinear dynamic inversion-based fast terminal sliding mode controller is designed to attain the desired attitude and position tracking control. This is done by employing a two-loop control structure. Numerical simulations are conducted to demonstrate the effectiveness of the proposed scheme in the presence of disturbance, parameter uncertainty, and noise. The numerical results are compared with current approaches, demonstrating the superiority of the proposed method. In order to assess the practical effectiveness of the proposed method, hardware-in-loop simulations are conducted by utilizing a Pixhawk 6X flight controller that interfaces with the mission planner software. Finally, experiments are conducted on a real F450 quadrotor in a secured laboratory environment, demonstrating stability and good tracking performance of the proposed MLNN observer-based SMC control scheme. Full article

(This article belongs to the Special Issue Challenges and Innovations in Aircraft Flight Control)

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Aerospace, Volume 11, Issue 10 (October 2024) – 5 articles

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