Performance assessment of radio occultation data from GeoOptics by comparing with COSMIC data

Responding to the ever-growing demand for environmental information, the National Oceanic and Atmospheric Administration (NOAA) seeks to enter into contracts to purchase Global Navigation Satellite System (GNSS) radio occultation (RO) observations produced by commercial vendors at a low-cost. GeoOptics is one commercial vendor awarded a contract with NOAA. GeoOptics operates the Community Initiative for Cellular Earth Remote Observation (CICERO) constellation of low-earth-orbiting (LEO) 6U CubeSats. The 6U-sized CICERO will enable the deployment of GNSS array consisting of RO satellites in the Earth&rsquo;s atmosphere to obtain many atmospheric observations which can improve weather forecasting. Applying GeoOptics RO data to reliable weather forecasting requires an assessment of its performance. This study analyzes the performance of GeoOptics CubeSats measurements by comparing it with the Constellation Observing System for Meteorology, Ionosphere, and Climate (COSMIC) missions (COSMIC-1 and COSMIC-2). The performance analysis was carried on data coverage capabilities and measurement quality. The analysis of data coverage confirmed that GeoOptics can acquire global observational coverage with adequate low-altitude penetration capability, while there should be updated in local time coverage. The analysis of RO measurement quality showed that GeoOptics RO measurements are comparable to those of COSMIC-2, even though GeoOptics exhibited a lower signal-to-noise ratio (SNR). The potential of GeoOptics allows for the development of a GNSS array in the Earth&rsquo;s atmosphere and a large amount of effective RO measurements to be obtained for reliable weather forecasting. &nbsp;</p

Past, Present and Future of a Habitable Earth

This perspective of this book views Earth's various layers as a whole system, and tries to understand how to achieve harmony and sustainable development between human society and nature, with the theme of " habitability of the Earth." This book is one effort at providing an overview of some of the recent exciting advances Chinese geoscientists have made. It is the concerted team effort of a group of researchers from diverse backgrounds to generalize their vision for Earth science in the next 10 years. The book is intended for scholars, administrators of the Science and Technology policy department, and science research funding agencies. This is an open access book

AI Tools for Design and Operation of Distributed Spacecraft Missions

With the recent advances in satellite miniaturization, communication and information technologies, there has been a paradigm shift in space exploration missions over the last few decades. This paradigm shift involves the transition from monolithic architectures formed by just one big satellite to a concept of a sensor web for space exploration consisting of heterogeneous sensors hosted on a variety of platforms including space, air and ground assets. These multiple entities share information in real time and make coordinated autonomous decisions to maximize system performance and/or scientific value. In this context, this thesis uses AI and machine learning techniques to overcome two big challenges found in the design and operation of Distributed Spacecraft Missions (DSMs): (1) The combinatorial explosion of feasible Earth observing constellations when not constraining the satellite orbits to symmetrical configurations, such as the Walker pattern. (2) The constant monitoring and ground operations required for node buffer management in Delay Tolerant Networks (DTN), which are governed by a set of standardized internet-like communications protocols robust to long delay and constant disruptions, and used in the communication between nodes in DSMs. The first challenge is approached by creating novel evolutionary formulations to explore large tradespaces of non-Walker hybrid satellite constellations with diversity of orbital parameters. Finally, the second challenge is addressed with the use of deep reinforcement learning, to automate the on-board decision making process in certain aspects of memory buffer management in DTN nodes, with the ultimate goal of optimizing network performance and reducing operational costs

Past, Present and Future of a Habitable Earth

This perspective of this book views Earth's various layers as a whole system, and tries to understand how to achieve harmony and sustainable development between human society and nature, with the theme of " habitability of the Earth." This book is one effort at providing an overview of some of the recent exciting advances Chinese geoscientists have made. It is the concerted team effort of a group of researchers from diverse backgrounds to generalize their vision for Earth science in the next 10 years. The book is intended for scholars, administrators of the Science and Technology policy department, and science research funding agencies. This is an open access book

Air Force Institute of Technology Research Report 2018

This Research Report presents the FY18 research statistics and contributions of the Graduate School of Engineering and Management (EN) at AFIT. AFIT research interests and faculty expertise cover a broad spectrum of technical areas related to USAF needs, as reflected by the range of topics addressed in the faculty and student publications listed in this report. In most cases, the research work reported herein is directly sponsored by one or more USAF or DOD agencies. AFIT welcomes the opportunity to conduct research on additional topics of interest to the USAF, DOD, and other federal organizations when adequate manpower and financial resources are available and/or provided by a sponsor. In addition, AFIT provides research collaboration and technology transfer benefits to the public through Cooperative Research and Development Agreements (CRADAs). Interested individuals may discuss ideas for new research collaborations, potential CRADAs, or research proposals with individual faculty using the contact information in this document

Air Force Institute of Technology Research Report 2019

This Research Report presents the FY19 research statistics and contributions of the Graduate School of Engineering and Management (EN) at AFIT. AFIT research interests and faculty expertise cover a broad spectrum of technical areas related to USAF needs, as reflected by the range of topics addressed in the faculty and student publications listed in this report. In most cases, the research work reported herein is directly sponsored by one or more USAF or DOD agencies. AFIT welcomes the opportunity to conduct research on additional topics of interest to the USAF, DOD, and other federal organizations when adequate manpower and financial resources are available and/or provided by a sponsor. In addition, AFIT provides research collaboration and technology transfer benefits to the public through Cooperative Research and Development Agreements (CRADAs). Interested individuals may discuss ideas for new research collaborations, potential CRADAs, or research proposals with individual faculty using the contact information in this document

Manoeuvre Planning Architecture for the Optimisation of Spacecraft Formation Flying Reconfiguration Manoeuvres

Formation flying of multiple spacecraft collaborating toward the same goal is fast becoming a reality for space mission designers. Often the missions require the spacecraft to perform translational manoeuvres relative to each other to achieve some mission objective. These manoeuvres need to be planned to ensure the safety of the spacecraft in the formation and to optimise fuel management throughout the fleet. In addition to these requirements is it desirable for this manoeuvre planning to occur autonomously within the fleet to reduce operations cost and provide greater planning flexibility for the mission. One such mission that would benefit from this type of manoeuvre planning is the European Space Agency’s DARWIN mission, designed to search for extra-solar Earth-like planets using separated spacecraft interferometry. This thesis presents a Manoeuvre Planning Architecture for the DARWIN mission. The design of the Architecture involves identifying and conceptualising all factors affecting the execution of formation flying manoeuvres at the Sun/Earth libration point L2. A systematic trade-off analysis of these factors is performed and results in a modularised Manoeuvre Planning Architecture for the optimisation of formation flying reconfiguration manoeuvres. The Architecture provides a means for DARWIN to autonomously plan manoeuvres during the reconfiguration mode of the mission. The Architecture consists of a Science Operations Module, a Position Assignment Module, a Trajectory Design Module and a Station-keeping Module that represents a multiple multi-variable optimisation approach to the formation flying manoeuvre planning problem. The manoeuvres are planned to incorporate target selection for maximum science returns, collision avoidance, thruster plume avoidance, manoeuvre duration minimisation and manoeuvre fuel management (including fuel consumption minimisation and formation fuel balancing). With many customisable variables the Architecture can be tuned to give the best performance throughout the mission duration. The implementation of the Architecture highlights the importance of planning formation flying reconfiguration manoeuvres. When compared with a benchmark manoeuvre planning strategy the Architecture demonstrates a performance increase of 27% for manoeuvre scheduling and fuel savings of 40% over a fifty target observation tour. The Architecture designed in this thesis contributes to the field of spacecraft formation flying analysis on various levels. First, the manoeuvre planning is designed at the mission level with considerations for mission operations and station-keeping included in the design. Secondly, the requirements analysis and implementation of Science Operation Module represent a unique insight into the complexity of observation scheduling for exo-planet analysis missions and presents a robust method for autonomously optimising that scheduling. Thirdly, in-depth analyses are performed on DARWIN-based modifications of existing manoeuvre optimisation strategies identifying their strengths and weaknesses and ways to improve them. Finally, though not implemented in this thesis, the design of a Station-keeping Module is provided to add station-keeping optimisation functionality to the Architecture

Manoeuvre planning architecture for the optimisation of spacecraft formation flying reconfiguration manoeuvres

Formation flying of multiple spacecraft collaborating toward the same goal is fast becoming a reality for space mission designers. Often the missions require the spacecraft to perform translational manoeuvres relative to each other to achieve some mission objective. These manoeuvres need to be planned to ensure the safety of the spacecraft in the formation and to optimise fuel management throughout the fleet. In addition to these requirements is it desirable for this manoeuvre planning to occur autonomously within the fleet to reduce operations cost and provide greater planning flexibility for the mission. One such mission that would benefit from this type of manoeuvre planning is the European Space Agency’s DARWIN mission, designed to search for extra-solar Earth-like planets using separated spacecraft interferometry. This thesis presents a Manoeuvre Planning Architecture for the DARWIN mission. The design of the Architecture involves identifying and conceptualising all factors affecting the execution of formation flying manoeuvres at the Sun/Earth libration point L2. A systematic trade-off analysis of these factors is performed and results in a modularised Manoeuvre Planning Architecture for the optimisation of formation flying reconfiguration manoeuvres. The Architecture provides a means for DARWIN to autonomously plan manoeuvres during the reconfiguration mode of the mission. The Architecture consists of a Science Operations Module, a Position Assignment Module, a Trajectory Design Module and a Station-keeping Module that represents a multiple multi-variable optimisation approach to the formation flying manoeuvre planning problem. The manoeuvres are planned to incorporate target selection for maximum science returns, collision avoidance, thruster plume avoidance, manoeuvre duration minimisation and manoeuvre fuel management (including fuel consumption minimisation and formation fuel balancing). With many customisable variables the Architecture can be tuned to give the best performance throughout the mission duration. The implementation of the Architecture highlights the importance of planning formation flying reconfiguration manoeuvres. When compared with a benchmark manoeuvre planning strategy the Architecture demonstrates a performance increase of 27% for manoeuvre scheduling and fuel savings of 40% over a fifty target observation tour. The Architecture designed in this thesis contributes to the field of spacecraft formation flying analysis on various levels. First, the manoeuvre planning is designed at the mission level with considerations for mission operations and station-keeping included in the design. Secondly, the requirements analysis and implementation of Science Operation Module represent a unique insight into the complexity of observation scheduling for exo-planet analysis missions and presents a robust method for autonomously optimising that scheduling. Thirdly, in-depth analyses are performed on DARWIN-based modifications of existing manoeuvre optimisation strategies identifying their strengths and weaknesses and ways to improve them. Finally, though not implemented in this thesis, the design of a Station-keeping Module is provided to add station-keeping optimisation functionality to the Architecture.EThOS - Electronic Theses Online ServiceGBUnited Kingdo