SHORT COURSES

Presented by:
Francois Laporte, CA senior expert, CNES
Lauri Newman, Conjunction Assessment Program Officer, NASA Headquarters
Matthew Hejduk, Chief Engineer, Satellite Conjunction Assessment, HQ NASA, The Aerospace Corporation

The threat of on-orbit collisions has become an increasing concern to the spacefaring community, both as an increasing mission risk due to a more congested space environment and through wider community awareness of the problem. The operational practice of conjunction assessment in response to this risk has also become more commonplace, evolving from simply predicting close approaches between orbiting objects to sophisticated systems and processes for managing on-orbit collision risk. This short course, organized and taught by industry leaders and subject matter experts in the field, is designed to educate beginners to intermediate-level practitioners on the fundamentals of conjunction assessment

This course provides a three-part overview of Conjunction Assessment. The first part is an extended background theory section that includes all the theoretical components which are needed in order to perform conjunction analysis and associated risk assessment. Topics include relevant astrodynamics basics, orbit determination methodologies, space domain awareness basic concepts, satellite conjunction assessment theory, quantified limitations of the two-dimensional probability of collision calculation, Monte Carlo analysis, cross-correlation between satellite covariances, and collision consequence assessments.

The second part of the course contains a treatment of modern conjunction risk assessment practices. The presenters share their operational experience and lessons learned, including some historical collision and close approach prediction statistics. Topics in this section include using and interpreting satellite probabilities of collision, designing and evaluating collision risk mitigation maneuvers, and understanding and processing the various relevant conjunction assessment data products, including those provided by the 19th Space Control Squadron.

Altogether, several hundreds of satellites are supported by either the NASA Conjunction Assessment Risk Analysis (CARA) or the CNES Conjunction Assessment and Evaluation Service: Alerts and Recommendations (CAESAR) within the EU SST framework, two instances of Middle Man. For both Middle Man examples, operations methods are presented and feedback is discussed. Both organization’s processes regularly evolve in order either to follow 18th Space Control Squadron upgrades or to improve analysis according to operational experience acquired during the past years.

The third and final section of the course contains a treatment of emerging technical and policy challenges for conjunction assessment activities. The space environment has been rapidly evolving, and is expected to continue to do so in the coming years. These changes include:

• large constellations are being proposed and flown
• cubesats are making space accessible to non-traditional space operators
• regulation and best practices are evolving
• efforts continue to define an architecture for a consolidated governmental or international Space Traffic Management (STM) entity
• Cis-lunar space is becoming more populated

This course not only demonstrates that Collision Avoidance is a 2-step process (close approach detection followed by risk evaluation to enable making a sound collision avoidance decision) but also leads to the conclusion that the complicated topic benefits from an experienced Middle Man role to provide expert advice

Presented by:
Aaron J. Rosengren, Assistant Professor, University of California San Diego
Shane D. Ross, Professor, Virginia Tech

To enable and protect the critical elements of the combined commercial, civil, and military command, control, communications, computer, intelligence, surveillance, and reconnaissance (C4ISR) infrastructure in the cislunar space beyond the geosynchronous belt (xGEO) requires a more fundamental understanding of the multiscale spatio-temporal dynamics in this regime. The nonlinear astrodynamics in xGEO, encompassing secular, resonant, chaotic, close-encounter, and manifold dynamics, is dramatically different than the weakly perturbed Keplerian approach used for over a half century for the detection and tracking of objects near Earth, from low-Earth orbits (LEO) to GEO. This course will review the foundational dynamics in the entire xGEO regime, including lunar mean-motion resonances (MMRs) and secular resonances, as well as the short timescale dynamics of libration-point orbits (LPOs) and and their associated invariant manifolds, and couple this knowledge to the cardinal questions and problems posed by cislunar space domain awareness (SDA). We will discuss the wide variety of dynamical models that are employed to approximate the diversity of trajectories in xGEO space. Whereas circumterrestrial and circumlunar orbits are largely governed by the perturbed two-body problem, in which the effects of the non-spherical gravity field and third-body perturbations on Earth or Moon satellites are often treated in a Hamiltonian formulation, all other cislunar trajectories, including lunar transfers, LPOs, Earth-Moon cyclers, stabile and unstable MMRs, and a wealth of other exotic periodic and non-periodic orbits, are specific applications of the gravitational N-body problem. The mathematical model adopted in the latter case is the restricted three-body problem (R3BP), in which the spacecraft of negligible mass is simultaneously affected by the terrestrial and lunar gravitational forces. This course will review the multiscale astrodynamics of xGEO space and bridge the gap between the perturbative treatment of distant geocentric orbits and the restricted three-body dynamics of LPOs and MMRs. Combining observations, theory, and simulation, this course will showcase the phase-space structure and connectivity of xGEO, identifying both highly stable “graveyard” orbits, as well as chaotic-trajectory regimes that can most easily mask maneuvers. We will discuss how this foundational knowledge can be adapted to processes that support the ground- and space-based surveillance and maintenance of a cislunar catalog, accommodating the complex dynamics in this regime. Our scope covers the wide range of orbital phase space relevant to both historic and current xGEO missions launched by the US (e.g., AMPTE, Chandra X-ray Observatory, several EXPLORER series satellites, ARTEMIS), Europe (e.g., XMM-Newton, Cluster II), Russia (e.g., Prognoz, Spektr-R, Astron), as well as the significant future xGEO missions scheduled or proposed by over a dozen nations or organizations to be launched in this decade. This course assumes a basic understanding of Keplerian two-body orbital mechanics.​

Presented by:
Francis Chun, Professor, USAF Academy, Department of Physics and Meteorology
David Strong, Senior Scientist, Strong EO Imaging, Inc.
Benjamin Roth, Director, Astronomy Research Group and Observatory, USAF Academy, Department of Physics and Meteorology
Anil Chaudhary, Principal Scientist, Applied Optimization, Inc.
Phillip Fishbein, Computer Engineer/Mathematician, Applied Optimization, Inc.

This short course will describe methods for traditional and advanced photometry data collection and image processing, including a hands-on demonstration using data from the USAFA Falcon Telescope Network (FTN). The course will consist of four sessions:

• Session 1: This session will cover the design considerations for establishing a system to collect data, including the range of objects to be observed and the type of data to be collected (i.e. photometry, polarimetry, spectroscopy, etc.). The design of the FTN will be presented as a brief case study; information on collaborating with USAFA to task the FTN for collections will be provided.
• Session 2: This session will cover the processing of broadband photometric data as a baseline for the more advanced EO data processing, including noise reduction methods, streak processing, and source extraction from non-crowded and crowded fields. The extraction techniques will include point spread function (PSF) fitting and aperture photometry for point sources. Finally, methods to calibrate the instrumental fluxes from the data to a standard magnitude system, such as the Johnson-Cousins photometric system, will be covered, including standard error analysis.
• Session 3: This session will illustrate the use of calibrated polarimetry data to compute Stokes parameters, and the challenges therein. The extraction and calibration of spectra from images will be next, including the extraction of the flux from a first-order streak, calibrating the pixel scale to a wavelength scale, and a method to correct for extinction.
• Session 4: This session will comprise hands-on demonstrations using FTN data. The participants will work to design data collection plans with the instructors. Next, the participants will work with FTN data files to extract and calibrate satellite data. Finally, the session will cover two methods of reporting and sharing data: the Electro-Optical Space Situational Awareness (EOSSA) data reporting standard, and the Unified Data Library (UDL).

Presented by:
Brandon Jones, Associate Professor, The University of Texas at Austin

This short course will present the fundamentals of Uncertainty Quantification (UQ) through the lens of SSA to help attendees understand the implications of how uncertainty may be represented and correctly interpreted.  Accurate UQ is a fundamental driver for timely and accurate SSA.  Broadly, UQ is the science of quantifying, reducing, and understanding sensitivity to uncertainty in our experiments, computer simulations/models, and algorithms.  The use of UQ in SSA extends beyond orbit prediction and covariance realism.  It can determine how we interpret knowledge extracted from data and computer simulations, what potential data may help to reduce uncertainty, and ultimately influences operator decisions.  The primary goal of this course is to introduce attendees to the rich and broad field of UQ, which they may use in their work and research after this course.

Topics will include definitions of key components of UQ, sources of and how to interpret uncertainty in estimators and resulting estimates, an overview of existing tools for uncertainty prediction through computer models, and various methods of analyzing sensitivity to sources of uncertainty.  Concepts will be illustrated through both simple examples and real-world applications such as orbit uncertainty propagation and sensor tasking.  Several open-source tools for UQ will be used in these illustrations so that attendees may leverage them and correctly interpret results in their future work.  Finally, attendees will be introduced to the latest areas of research in UQ, including multi-fidelity methods and the intersections of UQ and machine learning.

This course is intended for those looking to improve their understanding on how to quantify, interpret, and use uncertainty.  While anyone working in SSA will benefit from this course, it will be especially useful to those using or implementing software tools for simulation and data analysis.  Attendees familiar with basic probability and statistics will have the foundation necessary for this short course.

Presented by:
Yvette Rodriguez, Research Director / Professor, Defense Acquisition University

The evolving landscape of space, characterized by increasing actors and potential threats, necessitates innovative space surveillance and domain awareness approaches. The Modular Open Systems Approach (MOSA) emerges as a strategic solution, promoting the development and acquisition of space systems with enhanced flexibility, adaptability, and interoperability. By integrating technical and business practices, MOSA enables the efficient insertion of cutting-edge technologies, effective management of component obsolescence, and streamlined responses to emerging threats and security challenges.

This course will delve into the innovative integration of technical and business strategies through a MOSA methodology designed to streamline development timelines, incorporate cutting-edge technologies, spur innovation, and the need for data to enhance space surveillance and domain awareness interoperability.

Participants will explore acquiring and deploying platforms and systems comprised of severable components, facilitating technology insertion at critical junctures. This approach isolates high-risk elements in replaceable modules, safeguarding intellectual property within “black boxes” and ensuring adaptability in the face of emerging technologies or evolving threats. The course curriculum encompasses a holistic system engineering framework, employing key practices such as Modular Open Systems Approach, Mission Engineering, Digital Engineering, Modeling & Simulation, and Intellectual Property and Technical Data Rights management.

This comprehensive course will cover critical aspects of MOSA, including its foundational principles, technical frameworks, and application in Space Situation/Domain Awareness (SSDA). Participants will gain insights into designing systems with modularity at their core, facilitating seamless technology upgrades and ensuring systems can adapt to changing mission requirements without extensive overhauls. The curriculum will delve into practical applications of MOSA in space surveillance, highlighting how modular design and open standards can significantly enhance the detection, tracking, cataloging, and management of space objects.

Through a session of collaborative of lectures, case studies, web-based polling activities, and interactive discussions, attendees will explore the multifaceted benefits of MOSA, from cost savings and reduced sustainment burdens to increased competition among suppliers and improved warfighting capabilities. The course will emphasize the importance of digital engineering in supporting MOSA implementations, showcasing how digital tools and models can aid in the lifecycle management of space systems from concept through disposal.

Moreover, the course will address the challenges and considerations in adopting MOSA within the Department of Defense (DoD) and wider space community, including stakeholder interdependencies, acquisition processes, and cultural behaviors. By fostering a deep understanding of these dynamics, the course aims to equip participants with the knowledge and skills to advocate for and implement MOSA and SSDA principles within their organizations effectively.

Presented by:
Roberto Furfaro, Professor and Director of Space4 Center, University of Arizona
Richard Linares, Associate Professor, Massachusetts Institude of Technology
Weston Faber, Senior Scientist, L3Harris

Over the past decade, the field of machine learning has experienced incredible improvements in the applicability and accuracy of its techniques. These advances present huge opportunities for the SDA community as it faces ever-increasing scope, sensing modalities, and data volumes. The short course will survey recent advances in deep learning and associated applications to SDA. The first portion of the course will cover a broad overview of modern deep learning techniques with an emphasis on those areas that seem most directly relevant to SDA. The second portion of the course will examine a set of case studies of the techniques being applied to real SSA problems, including code examples in Python with Tensorflow and Pytorch.

Course Objectives: In this short course you will:

1. Get introduced to the theory and practice of Deep Learning (Dense & Convolutional Neural Networks, Variational Autoencoders)
2. Get introduced to the theory and practice of Deep Reinforcement Learning (Q-learning, Policy Gradient)
3. Analyze SSA-relevant case studies via development of python-based codes for deep nets Jupyter notebooks walk-through

Presented by:
Thomas Schildknecht, Director of Swiss Optical Ground Station, University of Bern, Astronomical Institute

The proliferation of space debris and the increased probability of collisions and interference raise concerns about the long-term sustainability of space activities, particularly in the low-Earth orbit and geostationary orbit environments. During recent years governments, space agencies and civilian research organizations increased their efforts to build space object catalogues and to investigate the space debris population in different orbit regions. Understanding the nature and the sources of debris is a prerequisite to provide the scientific foundation for a sustainable use of near-Earth space.

This course will provide a general introduction to the space debris problem, give an overview on the current space debris research activities to detect and characterize space debris, followed by a presentation of the efforts to model the future space debris population and the international efforts to protect and remediate the space environment. Particular focus will be put on optical techniques to detect, track and characterize space objects including small-size debris. The techniques will be illustrated with examples from the long-standing observation programs of the Astronomical Institute of the University of Bern (AIUB).

Presented by:
Peter Zimmer, Research Scientist, J.T. McGraw and Associates, LLC

This course will provide those new to the space domain awareness (SDA) community (as well as  those seeking a refresher) an introductory-level understanding of the tools and techniques used for detecting and tracking earth-orbiting satellites with ground-based optical instruments. The course begins with an overview of optical telescopes and includes a discussion of many of the key terms and buzzwords one might encounter when reading about ground-based optical telescopes. From there, the course presents an overview of how these components are assembled into a sensor package for nighttime optical SDA and can be optimized to suit various mission goals. This includes a discussion of satellite visual magnitudes, terminator viewing, sensitivity, search rate and related topics. Finally, the course presents a brief look at the challenges and differences of optical systems for daytime optical and cislunar SDA.

Presented by:
Moriba Jah, Professor Aerospace Engineering & Engineering Mechanics, The University of Texas at Austin

Welcome to “Navigating the Cosmos,” a short course on space environmentalism aimed at a diverse audience including space law and policy experts, spacecraft operators, and space situational awareness researchers and practitioners. Led by Dr. Moriba Jah, a pioneer in space environmentalism and astrodynamicist, this course will delve into the complexities of managing the space environment and mitigating the risks associated with space activities.

Course Overview:

Understanding Space Environmentalism:

• Introduction to space environmentalism and its significance in contemporary space exploration.
• Exploration of the interplay between human activities and the space environment.
• Discussion on the challenges posed by space debris, orbital congestion, and space weather.

Space Law and Policy Perspectives:

• Examination of international treaties and agreements governing space activities.
• Analysis of legal frameworks addressing space debris mitigation, space traffic management, and liability issues.
• Case studies highlighting the role of space law and policy in promoting sustainable space practices.

Spacecraft Operations and Risk Mitigation:

• Overview of spacecraft design considerations for improved survivability and maneuverability.
• Strategies for collision avoidance and debris mitigation during spacecraft operations.
• Real-world examples illustrating the importance of proactive risk management in space missions.

Advances in Space Situational Awareness:

• Introduction to space situational awareness (SSA) and its role in monitoring the space environment.
• Exploration of SSA technologies, including ground-based sensors and satellite tracking systems.
• Discussion on data sharing and collaboration among stakeholders to enhance SSA capabilities.

Course Objectives:

Gain a comprehensive understanding of the key principles and challenges of space environmentalism.

Explore the intersection of space law, policy, and operational practices in ensuring sustainable space activities.

Acquire practical knowledge and tools for mitigating risks associated with space debris and orbital dynamics.

Learn about the latest advancements in space situational awareness and its implications for space operations and policy-making.

Presented by:
Ralph Dinsley, Founder/Managing Director, 3S Northumbria Ltd
Christopher Newman, Professor of Space Law and Policy, Northumbria University
Lauren Napier, Lecturer In Law, Space, Cyber, Telecommunications, AI and Robotics, Northumberia University

This half-day course will provide participants with an opportunity to challenge the lessons which other domains of operation bring to the regulation of space. It will address the complexities of this intersection, aiming to provide participants with insights into the applicability and limitations of cross-domain learning in the realm of space law. In the rapidly evolving landscape of space operations and activities, the relationship between law and technology has become increasingly intricate. Looking to maritime, cyber, and other domains of operation for solutions is tempting, especially when considering the creation of a circular economy for space.

This course will first examine the benefits of establishing a circular space economy, examine some of the barriers and provide a vital and timely critical examination of the strengths, limitations, and pitfalls of cross-domain learning in the context of space law. Participants will engage in discussions surrounding the inherent challenges of applying principles from the maritime and cyber domains to address legal issues pertaining to space activities. Factors such as jurisdictional conflicts, environmental differences, and technological disparities are explored, shedding light on the complexities that may impede the effectiveness of cross-domain approaches in certain scenarios.

Participants will discuss and evaluate the different methods of regulatory oversight that could be utilized to increase the flow of data both to and from all stakeholders. The workshop will also provide opportunities to explore and explode some commonly held misconceptions about how useful analogies from maritime, cyber and AI could be used to solve some of the wicked problems associated with the management and governance of outer space. Participants will gain a nuanced understanding of how interdisciplinary perspectives can enhance regulatory frameworks, foster innovation, and promote responsible space exploration leading to a true circular economy for space.

Presented by:
Mark Abrams, Principal, Cognitive Learning Systems
Steve Stennett, Principal, Cognitive Learning Systems

Intelligence situational awareness can be built around five essential tasks: (a) receipt of real-time data from a plurality of data sources, (b) ingest of the real-time data, (c) persistence of some of the real-time data, (d) analysis of the real-time data to derive at least one relevant insight, and (e) generation of an output associated with the insight for real-time visualization and decision making.

Cognitive learning expands the process into four essential functions: description, diagnosis, prediction, and prescription. Descriptive analytics condenses data into smaller, more useful pieces of information; diagnostic analytics provide a deeper level of analysis that indicates the root cause of events and trends. Predictive analytics identify probable future outcomes of an event by analyzing recent and historic data; prescriptive analytics go beyond predictions by suggesting options for taking advantage of a future opportunity or mitigating a future risk. In this end state, a cognitive learning ecosystem illustrates the implications of each decision option for the mission director.

The current deployment of mega-constellations of satellites allows us to develop human-machine collaboration environments to build patterns of life, or normalcy models, to detect outliers and anomalies (black swans or unicorns). Autonomous maneuvering is a perfect example of autonomy creating a complex situation that lies outside of normal human situational awareness (and space domain awareness). Cognitive learning enables intelligent space traffic management with an anticipatory model that predicts automated maneuvers. In a semantic sense, we are teaching machines to anticipate the behavior of other machines so that they can autonomously co-exist in the same space on a pre-defined non-interference basis, and at the same time, the same system mitigates the risk of autonomy interfering with human-controlled systems as well, with the caveat that human-controlled systems have a level of creativity that machine systems do not.

For the purpose of this short course, we examine the challenge of parsing the Starlink constellation into “active,” “inactive,” “derelict,” and “debris” for the purposes of defining a co-orbital constellation management plan that ensures safe traffic management in congested space with a minimum number of maneuvers and expenditure of fuel.”

Presented by:
Richard L. Lachance, President & CEO, RLL Consulting

This course will be given by a space scientist who will present and discuss the physical science for the modeling and simulation of satellite orbits through a targeted introduction to astrodynamics. It serves as a foundational base into the principles of celestial mechanics through the science of spacecraft motion.

The goal is to develop in the student a deeper understanding of the mathematical models and computational techniques used to analyze and predict the behavior of objects in space. Participants will be able to program their own basic numerical simulations and better use advanced software tools in astrodynamics analysis, such as Ansys STK (Systems Tool Kit), NASA’s GMAT (General Mission Analysis Tool) as well as Matlab and Python-based libraries (e.g. orekit, poliastro, etc.) for orbital simulations and trajectory optimization.

Following a short historical perspective introduction, the course will explore the analytical formulations behind Kepler’s laws of planetary motion and Newton’s law of universal gravitation, followed by presentation of perturbation models like Cowell’s, Encke’s, Gauss’ methods, while also covering the ubiquitous SDP4 propagator. Specific instances will be provided illustrating the various modeling and simulation approaches, exploring their differing levels of accuracy and performance considerations.

Emphasis will be given on visual demonstrations through a series of interactive animations to understand the different reference frames and orbital regime, in order to comprehend at an intuitive level the astrodynamics relationships of the classical orbital elements (COEs) with their effects on the shape, size, and orientation of an orbit.

Through hands-on exercises of different case studies, students will learn the fundamental principles of orbit propagation and gain an insight into the challenges and complexities of planning and executing spacecraft missions. Practical sessions will use a provided computer simulation program (“Orbit101”) to analyze and visualize the dynamics of various scenarios. Adjustment of classical orbital elements in real time allows to experience and understand how changes in these parameters affect trajectories over time.

As part of the handouts, the main equations and key formulas will be summarized and a startup Matlab/Python kit in the form of a series of code examples will be provided. A synthesis summary of relevant literature will also be given to direct students through a selection of “must-have” books, papers and web sites.

Presented by:
David Gerwe, Scientist, Boeing
Steven Griffin, Boeing Chief Engineer, Boeing

Use of image data on commercial and military derivative aircraft is becoming more and more important, especially with the emphasis on autonomy and multirotor aircraft. How are all of these autonomous vehicles going to keep from running into each other? The processes of forming a good image, tracking a target and object detection are all critical ingredients for safety in the future. As the skies become more and more crowded, visual feedback will become even more pervasive. Unfortunately, the right camera is not always available for a given visual need. Images may become blurred due to motion or indistinguishable due to poor lighting. Also, the use of relatively inexpensive cameras, with relatively small apertures for many tasks makes the likelihood of getting good, raw image data less likely. Learn about some techniques that are available to select the right camera, clean up images obtained under suboptimum conditions, track on a portion of an image and detect objects in an image. The course will be roughly half lecture and have active learning using hardware to implement algorithms discussed in lecture.

Presented by:
Thomas Johnson, CEO, Exa Research, LLC

The course is targeted towards groups that are trying to understand system architecture considerations for designing and operating enterprise scale SSA systems. The goal is to understand the fundamental requirements and implementation details that support a scalable, analyst friendly system. The emphasis is on understanding best practices for:

• Managing all the inputs (not just observations), conflicts, and how they will change.
• What real-world data quality and other issues that must be addressed.
• Debugging, testing, and traceability.
• Security considerations.
• Analyst expectations.