Space Situational Awareness & Space Traffic Management

View Video Presentation: https://doi.org/10.2514/6.2023-1118.vid Recent decades have seen increased interest in the Moon and cislunar operations. To ensure safety of flight and peace of operations in the cislunar domain, space traffic management is required, which, in turn, necessitates a dedicated space situational awareness (SSA) system. However, SSA in the cislunar domain is notoriously difficult to achieve due to the inherently large volume and the chaotic nature of orbits in the regime. These characteristics produce challenges in establishing persistent monitoring and limit predictive capabilities. To address these challenges, we detail a trade space for constructing an effective SSA architecture in the cislunar space domain through a tiered radio frequency (RF)/optical sensing architecture. Our results show that a paradigm shift in space operations that achieves on-orbit manufacturing of large precise structures from in-situ resources enables timely and persistent cislunar SSA. Such a paradigm shift removes the launch constraints imposed on sensors, allowing for the deployment of sensors that are 5-10x the size of structures currently available. We show how large, precise optical and RF apertures improve SSA architecture performance in the cislunar domain through improved signal-to-noise ratios, resolutions, and detection ranges.

Strategic Implications of the Proliferation of Space Situational Awareness Technology and Information: Lessons Learned from the Remote Sensing Sector

The outer space domain has become increasingly congested. In order to responsibly operate space systems, owner/operators must track their satellites and maintain awareness of all other tracked space objects, and act to minimize any risks that can be identified. This has spawned an evolution of space systems operational practices. Commercial and other satellite owner/operators rely on space situational awareness (SSA) information needed to reduce the chances of collisions with other spacecraft or orbital debris. The United States (U.S.) Strategic Command (USSTRATCOM) has been authorized to make SSA information and services available to non-U.S. foreign and commercial entities. Responding to the needs, direct private SSA solutions also have been proposed to satisfy perceived needs in the operator marketplace.

Space situational awareness (SSA) plays an imperative role in maintaining safe space operations, especially given the increasingly congested space traffic around the Earth. Space-based SSA offers a flexible and lightweight solution compared to traditional ground-based SSA. With advanced machine learning approaches, space-based SSA can extract features from high-resolution images in space to detect and track resident space objects (RSOs). However, existing spacecraft image datasets, such as SPARK, fall short of providing realistic camera observations, rendering the derived algorithms unsuitable for real SSA systems. In this work, we introduce SpaceDet, a large-scale realistic space-based image dataset for SSA. We consider accurate space orbit dynamics and a physical camera model with various noise distributions, generating images at the photon level. To extend the available observation window, four overlapping cameras are simulated with a fixed rotation angle. SpaceDet includes images of RSOs observed from 19 km to 63,000 km, captured by a tracker operating in LEO, MEO, and GEO orbits over a period of 5,000 seconds. Each image has a resolution of 4418 x 4418 pixels, providing detailed features for developing advanced SSA approaches. We split the dataset into three subsets: SpaceDet-100, SpaceDet-5000, and SpaceDet-full, catering to various image processing applications. The SpaceDet-full corpus includes a comprehensive dataloader with 781.5 GB of images and 25.9 MB of ground truth labels. Furthermore, we adapted detection and tracking algorithms on the collected dataset using a specified splitting method to accelerate the training process. The trained model can detect RSOs from real-world space observations with zero-shot capability.

Space is becoming increasingly congested as the number of on-orbit satellites and debris objects continues to grow. Space traffic management (STM) is critical for ensuring that the expanding orbital population operates safely and efficiently, avoiding collisions and radio-frequency interference while still facilitating widespread space operations. Recent events such as the FCC approval of SpaceX’s ~12,000 satellite constellation, the signing of Space Policy Directive 3 (which moves Space Situational Awareness responsibilities away from the Department of Defense and to a civil agency), and the growth in rideshare and small launch vehicles illustrate the rapidly changing nature of this domain. This paper will describe the concept of operations (ConOps) for a civilian STM research initiative, which has been developed from previous NASA work to enable safe operation of small unmanned aircraft systems. The STM ConOps proposes an architecture to enable efficient data sharing and coordination between participants to facilitate safe spaceflight operations. It is designed to utilize and promote the emerging field of commercial STM services, as a complement to existing government-provided STM services. The concept envisions a phased evolution that would gradually integrate additional capabilities, proposing a first phase architecture and tentative plans for a broader system. Work towards developing an STM research and prototyping platform is also discussed.

Space situation awareness (SSA) includes tracking of active and inactive\nresident space objects (RSOs) and assessing the space environment through\nsensor data collection and processing. To enhance SSA, the dynamic data-driven\napplications systems (DDDAS) framework couples on-line data with off-line\nmodels to enhance system performance. Using feedback control, sensor\nmanagement, and communications reliability. For information management, there\nis a need for identity authentication and access control to ensure the\nintegrity of exchanged data as well as to grant authorized entities access\nright to data and services. Due to decentralization and heterogeneity of SSA\nsystems, it is challenging to build an efficient centralized access control\nsystem, which could either be a performance bottleneck or the single point of\nfailure. Inspired by the blockchain and smart contract technology, this paper\nintroduces BlendCAC, a decentralized authentication and capability-based access\ncontrol mechanism to enable effective protection for devices, services and\ninformation in SSA networks. To achieve secure identity authentication, the\nBlendCAC leverages the blockchain to create virtual trust zones and a robust\nidentity-based capability token management strategy is proposed. A\nproof-of-concept prototype has been implemented on both resources-constrained\ndevices and more powerful computing devices, and is tested on a private\nEthereum blockchain network. The experimental results demonstrate the\nfeasibility of the BlendCAC scheme to offer a decentralized, scalable,\nlightweight and fine-grained access control solution for space system towards\nSSA.\n

Resident Space Objects (RSOs) are a collection of both man-made and natural objects in near-Earth space. Given their large orbital velocities and rapidly increasing quantity, they pose a collision threat to space assets, necessitating better Space Situational Awareness (SSA). SSA begins with detecting these objects in the first place and can be accomplished by using space-based optical images, such as images from the Fast Auroral Imager (FAI) on the CASSIOPE satellite. However, these short-exposure images are low in resolution and contain various artifacts and noise, posing challenges to traditional source detection methods. Furthermore, the background stars and RSOs both move due to the satellite’s non-constant attitude, posing a challenge for tracking algorithms. Nevertheless, these images are a valuable source of SSA data, which can be used to develop algorithms to ultimately augment the capabilities of current SSA systems. Such augmentations include performing RSO detection as a simultaneous function on existing spacecraft or allowing dedicated SSA payloads to detect RSOs during slew maneuvers, where background stars will similarly move. This paper proposes a rules-based RSO tracking algorithm tailored for low-resolution, short-exposure, space-based imagery with non-constant spacecraft attitude, addressing the challenge of distinguishing RSOs from background stars that are also in motion. This method consists of a custom thresholding algorithm, along with the Iterative Closest Point (ICP) algorithm to correct the motion of the background stars, followed by a tracking algorithm to finally detect the RSOs within the imagery, returning their pixel positions. The algorithm was tested on an 878-image dataset, achieving 79% precision and 71% recall, while detecting 87% of all RSOs at least once. These results prove that the algorithm is a feasible method for detecting RSOs in non-constant-attitude imagery, providing a means to develop current SSA systems.

More than half a century of space activities has resulted in the placement of thousands of space objects in the Earth’s orbit. Understanding the questions of how, where, and who is moving in orbit is essential for the management of space infrastructure. Since the beginning of space missions, this task as been carried out by Space Situational Awareness (SSA) systems. SSA systems are made up of several subsystems, such as optical recognition instruments, radar and radio. In recent years, these terrestrial systems have also been joined by satellites with similar capabilities. Historically, these systems were maintained by the military. It was only recently that the private sector became a major actor in the field. Consultation, Command and Control (C3) allows for a strong collaboration of civil and military bodies that focus on information sharing and interoperability of the systems. SSA systems have proved critical in collisions between satellites and in preserving the structural stability of the International Space Station several times. The security of these systems hence has a strong impact on space and international security. The growing importance of the space sector and its progressive recognition as a critical infrastructure shows that a model and simulation of the scenario are essential for a centric defence. This paper will identify the areas that pose external threats focussing on the European and Arctic region. Following the threats’ evaluation, their level of disruption will be considered, whether partial or total, permanent or temporary. This approach will enable the development of a European and Arctic scenario analysis of SSA disruption and evaluate the SSA security in the coming years. The scenario will take into consideration environmental, kinetic, electronic, and cyber sources of disruption.

The basic components and complex property of SSA (space situational awareness) system is introduced. It is elaborated that the reason and method of researching SSA system based on parallel control theory. Specific idea and steps of modeling and simulation are proposed through ACP method of parallel control theory, and a simple simulated instance was used as a prototype of achieving artificial system of SSA.

The space environment has become highly congested due to the increasing space debris, seriously threatening the safety of orbiting spacecraft. Space-based situational awareness, as a comprehensive capability of threat knowledge, analysis, and decision-making, is of significant importance to ensure space security and maintain normal order. Various space situational awareness systems have been designed and launched. Data acquisition, target recognition, and monitoring constituting key technologies make major contributions, and various advanced algorithms are explored as technical supports. However, comprehensive reviews of these technologies and specific algorithms rarely emerge. It disadvantages the future development of space situational awareness. Therefore, this paper further reviews and analyzes research advancements in key technologies for space situational awareness, emphasizing target recognition and monitoring. Many mature and emerging methods are presented for these technologies while discussing application advantages and limitations. Specially, the research prospects of multiagent and synergetic constellation technologies are expected for future situational awareness. This paper indicates the future directions of the key technologies, aiming to provide references for space-based situational awareness to realize space sustainability.

From the Seas to Outer Space: The Reverse Dynamics of Civil-Military Situational Awareness Information and Responsibility Sharing

The space around the Earth is becoming increasingly populated with a growth in number of launches and proliferation of debris. Currently, there are around 44,000 objects (with a minimum size of 10cm) orbiting the Earth as per the data made publicly available by the US strategy command (USSTRATCOM). These objects include active satellites and debris. The number of these objects are expected to increase rapidly in future from launches by companies in the private sector. For example, SpaceX is expected to deploy around 12000 new satellites in the LEO region to develop a space-based internet communication system. Hence in order to protect active space assets, tracking of all the objects is necessary. Probabilistic tracking methods have become increasingly popular for solving the multi-target tracking problem in Space Situational Awareness (SSA). This thesis studies one such technique known as the GM-PHD filter, which is an algorithm which estimates the number of objects and its states when non-perfect measurements (noisy measurements, false alarms) are available. For Earth orbiting objects, especially those in Geostationary orbits, ground based optical sensors are a cost-efficient way to gain information.In this case, the likelihood of gaining target-generated measurements depend on the probability of detection (pD) of the target.An accurate modeling of this quantity is essential for an efficient performance of the filter. pD significantly depends on the amount of light reflected by the target towards the observer. The reflected light depends on the relative position of the target with respect to the Sun and the observer, the shape, size and reflectivity of the object and the relative orientation of the object towards Sun and the observer. The estimation of the area and reflective properties of the object is in general, a difficult process. Uncontrolled objects, for example, start tumbling and no information regarding the attitude motion can be obtained. In addition, the shape can change because of disintegration and erosion of the materials. For the case of controlled objects, given that the object is stable, some information on the attitude can be obtained. But materials age in space which changes the reflective properties of the materials. Also, exact shape models for these objects are rare. Moreover,, area can never be estimated with optical measurements or any other measurements, as it is always albedo-area i.e., reflectivity times area that can be measured. The purpose of this work is to design a variation of the GM-PHD filter which accounts for the uncertainty in pD as the original GM-PHD filter designed by Vo and Ma assumes pD as a constant. It is validated that the proposed method improves the filter performance when there is an uncertainty in area(hence uncertainty in pD) of the targets. In the tested cases, the uncertainty in pD was modeled as an uncertainty in area while assuming that the targets are spherical and that the reflectivity of the targets is constant. It is seen that a model mismatch in pD affects the filter performance significantly and the proposed method improves the performance of the filter in all cases.

As an emerging approach to space situational awareness and space imaging, the practical use of an event-based camera (EBC) in space imaging for precise source analysis is still in its infancy. The nature of event-based space imaging and data collection needs to be further explored to develop more effective event-based space imaging systems and advance the capabilities of event-based tracking systems with improved target measurement models. Moreover, for event measurements to be meaningful, a framework must be investigated for EBC calibration to project events from pixel array coordinates in the image plane to coordinates in a target resident space object’s reference frame. In this paper, the traditional techniques of conventional astronomy are reconsidered to properly utilise the EBC for space imaging and space situational awareness. This paper presents the techniques and systems used for calibrating an EBC for reliable and accurate measurement acquisition. These techniques are vital in building event-based space imaging systems capable of real-world space situational awareness tasks. By calibrating sources detected using the EBC, the spatiotemporal characteristics of detected sources or “event sources” can be related to the photometric characteristics of the underlying astrophysical objects. Finally, these characteristics are analysed to establish a foundation for principled processing and observing techniques which appropriately exploit the capabilities of the EBC.

This paper introduces a parallel-compiled tool that combines several of our recently developed methods for solving the perturbed Lambert problem using modified Chebyshev-Picard iteration. This tool (unified Lambert tool) consists of four individual algorithms, each of which is unique and better suited for solving a particular type of orbit transfer. The first is a Keplerian Lambert solver, which is used to provide a good initial guess (warm start) for solving the perturbed problem. It is also used to determine the appropriate algorithm to call for solving the perturbed problem. The arc length or true anomaly angle spanned by the transfer trajectory is the parameter that governs the automated selection of the appropriate perturbed algorithm, and is based on the respective algorithm convergence characteristics. The second algorithm solves the perturbed Lambert problem using the modified Chebyshev-Picard iteration two-point boundary value solver. This algorithm does not require a Newton-like shooting method and is the most efficient of the perturbed solvers presented herein, however the domain of convergence is limited to about a third of an orbit and is dependent on eccentricity. The third algorithm extends the domain of convergence of the modified Chebyshev-Picard iteration two-point boundary value solver to about 90% of an orbit, through regularization with the Kustaanheimo-Stiefel transformation. This is the second most efficient of the perturbed set of algorithms. The fourth algorithm uses the method of particular solutions and the modified Chebyshev-Picard iteration initial value solver for solving multiple revolution perturbed transfers. This method does require “shooting” but differs from Newton-like shooting methods in that it does not require propagation of a state transition matrix. The unified Lambert tool makes use of the General Mission Analysis Tool and we use it to compute thousands of perturbed Lambert trajectories in parallel on the Space Situational Awareness computer cluster at the LASR Lab, Texas A&M University. We demonstrate the power of our tool by solving a highly parallel example problem, that is the generation of extremal field maps for optimal spacecraft rendezvous (and eventual orbit debris removal). In addition we demonstrate the need for including perturbative effects in simulations for satellite tracking or data association. The unified Lambert tool is ideal for but not limited to space situational awareness applications.

This paper recalls the history of sodium guide star laser systems used in astronomy and space situational awareness adaptive optics, analyzing the impact that sodium laser technology evolution has had on routine telescope operations. While it would not be practical to describe every single sodium guide star laser system developed to date, it is possible to characterize their evolution in broad technology terms. The first generation of sodium lasers used dye laser technology to create the first sodium laser guide stars in Hawaii, California, and Spain in the late 1980s and 1990s. These experimental systems were turned into the first laser guide star facilities to equip mediumto- large diameter adaptive optics telescopes, opening a new era of Laser Guide Star Adaptive Optics (LGS AO)-enabled diffraction-limited imaging from the ground. Although they produced exciting scientific results, these laser guide star facilities were large, power-hungry and messy. In the USA, a second-generation of sodium lasers was developed in the 2000s that used cleaner, yet still large and complex, solid-state laser technology. These are the systems in routine operation at the 8 to 10m-class astronomical telescopes and 4m-class satellite imaging facilities today. Meanwhile in Europe, a third generation of sodium lasers was being developed using inherently compact and efficient fiber laser technology, and resulting in the only commercially available sodium guide star laser system to date. Fiber-based sodium lasers are being or will soon be deployed at three astronomical telescopes and two space surveillance stations. These highly promising systems are still relatively large to install on telescopes and they remain significantly expensive to procure and maintain. We are thus proposing to develop a fourth generation of sodium lasers: based on semiconductor technology, these lasers could provide a definitive solution to the problem of sodium LGS AO laser sources for all astronomy and space situational awareness applications.