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Unified Classification for Distributed Satellite Systems A. Poghosyana*, I. Llucha, H. Matevosyana, A. Lamba, C.A. Morenoa, C. Taylora, A. Golkara, J. Coteb, S. Mathieub, S. Pierottib, J. Graveb, J. Narkiewiczc, S. Topczewskic, M. Sochackic, E. Lancherosd, H. Parkd, A. Campsd

a Skolkovo Institute of Science and Technology, Moscow, Russia b Thales Alenia Space, Cannes, France c Politechnika Warszawska, Warsaw, Poland d Universitat Politecnica de Catalunya, Barcelona, Spain * A.Poghosyan@skoltech.ru Abstract: Recent technological advances spurred the exploration of problems that require multiple spacecraft operating in a synchronized manner, promoting research and development activities in innovative distributed space system concepts including Constellations, Trains, Clusters, Swarms, Fractionated Satellites, and Federated Satellites. The increasing interest in distributed space systems necessitates a unified classification framework. This report provides a detailed classification for different distributed architectures as well as clarifies the distinctions in terms of mission goals, level of cooperation required for accomplishing the mission objectives, level of homogeneity between individual spacecraft or fractions of the distributed spacecraft, inter-satellite distance, and level of autonomy of spacecraft or a fraction of distributed spacecraft. Thus giving a clear outline for consistently defining various distributed architectures independent of the individual mission framework. Introduction Over the past 60 years, the space industry has advanced engineering principles that provide large, expensive and optimal satellites handcrafted by large groups of engineers, based on tightly coupled subsystems and designed to accomplish a set of mission goals satisfying particular user needs. However, recent technological advances spurred the exploration of problems that require multiple spacecraft operating in a synchronized manner. Starting from 1980s numerous multi-spacecraft missions were proposed and implemented including GPS navigation constellation [1], Iridium [2] and Globalstar [3] communication constellations, NASA’s Afternoon Constellation (A-Train) for Earth observation [4] or the COSMIC Constellation for GNSS-Radio Occultations [5] as well as TDRSS [6] and EDRS [7] geostationary data relay satellites. As highlighted by I. Lluch and A. Golkar [8], “the last decade has seen the rise of a variety of novel space system architecture proposals with a focus on distribution”. Distributed Satellite Systems (DSS) are defined as mission architectures consisting of multiple space elements that interact, cooperate and communicate with each other, usually resulting in new system properties and/or emerging functions. Generally, distributed architectures are categorized by a variety of names including Constellations, Trains, Clusters, Swarms, Fractionated Satellites, and Federated Satellites (Table 1). For example, the constellation is a traditional approach, when sporadically distributed satellites are used for maximizing the coverage. On the other hand, clusters are deliberately positioned closely together for enhancing or creating new system capabilities, thus requiring very precise attitude determination and control in order to maintain the formation stability as well as to avoid satellite collisions. Swarms are roughly comparable to clusters except they involve a much larger number of usually smaller and cheaper satellites. Additionally, swarms do not have as stringent attitude determination and control requirements as the clusters [9].

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Fractionated spacecraft [10] and Federated Satellite Systems [11] are relatively novel concepts involving a network of multiple heterogeneous space elements that interact, cooperate and communicate with each other, creating new emerging capabilities. With a notable exception of multistatic radar and distributed aperture missions, these novel DSS architectures provide new system attributes rather than enabling breakthrough functionalities. These attributes come at the cost of increased complexity in terms of interfacing, synchronization and networking, which are more mature or less complex in monolithic systems [8]. Table 1 Types of distributed mission architectures [2, 4, 12-15].

DSS architectures Mission goals Cooperation Homogeneity Inter-Satellite

distance Autonomy

Constellations Mission goal

shared (Iridium, GPS)

Cooperation required to support mission

goals

Homogeneous components, some

differences possible (GPS generations)

Regional Autonomous

Trains Independent, but could be shared

Cooperation from optional to required

Heterogeneous components Local Autonomous

Clusters Mission goal shared

Cooperation required to support mission

goals

Homogeneous components Local

Autonomous to completely co-dependent

Swarms Mission goals shared

Cooperation required to support mission

goals

From homogeneous to heterogeneous

components

From local to regional

Autonomous to completely co-dependent

Fractionated Satellites

Mission goals shared

From optional (service areas) to

required (distributed critical functions)

Heterogeneous components Local

Autonomous to completely co-dependent

Federated Satellites

Independent mission goals Ad-hoc, optional Heterogeneous

components From local to

regional Autonomous

Several distributed architectures could be classified as formation-flying missions. Notable examples of formation-flying missions include TerraSAR-X – TanDEM-X [16], GRACE [17], and PRISMA [18]. Formation flight involves some form of tight flight control compared to constellations and it is deployed responding to a cohesive mission need, requiring cooperation to achieve it. Figure 1 shows a notional representation of satellite formations, fractionated spacecraft and satellite federations, compared to monolithic spacecraft and constellations. Detailed descriptions of different DSS architecture types are presented in the Table 1 as well as in the subsequent sections. Homogeneity in Table 1 is defined as the level of similarity between individual spacecraft or fractions of the distributed spacecraft, and Autonomy is defined as the level of operational independence of the spacecraft or a fraction of distributed spacecraft. This work was conducted in the framework of the ONION “Operational Network of Individual Observation Nodes” project supported by the European Union’s Horizon 2020 research and innovation programme. The goal of ONION is to propose a pragmatic, evolutionary and scalable approach, hybridizing fractionated and federated satellite system concepts, and augmenting existing space assets for the development of future space missions and new services. Thus, the objective of this paper is to provide a unified classification framework for consistently defining various distributed architectures independent of individual missions.

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Figure 1 Notional representation of satellite formations, fractionated spacecraft and satellite federations compared to monolithic spacecraft and constellations. A single mission, termed ‘A’ can be performed by a monolithic satellite, or either require a constellation or a formation. A fractionated spacecraft is a breakdown of the components to carry out mission A, while in a Federation different missions (A, B, C, D) cooperate. Constellations Satellite constellations were the first successful implementation of distributed satellite systems, which respond to a functional need such as continuous real time global coverage. In contrast, other novel DSS are generally more oriented to achieve new properties or attributes such as added flexibility or robustness for the overall system. Satellite constellations have multiple applications such as communication, navigation, and Earth science [19]. To date, many constellations successfully accomplished their technical objectives, but some of the commercial constellations have not been financially successful due to increasing competition from terrestrial infrastructure and suboptimal user-base penetration [20] as in the case of Iridium and Teledesic in the 1990s. Prominent examples of satellite constellation include GPS [1], GLONASS [21], Galileo [22] and Beidou [23] global navigation satellite systems, Iridium [2], Iridium NEXT [24], Globalstar [3] and O3b [25] communication constellations, DMC [26] and Flock [27] Earth observation constellations. It is evident that the space industry is experiencing an increased shift of interest from large and expensive satellites handcrafted by large groups of engineers to a smaller, cheaper, mass-produced satellites over the past decades. Such trend has resulted in a revived implementation of ambitious ideas such as megaconstellations. Compared to previous attempts at establishing large in-space constellations (such as the case of Teledesic) new opportunities have been opened due to the increased pervasiveness of Internet to everyday life and business operations, and increased cost efficiency and performance associated with small satellite systems. Currently, megaconstellations are one of the hottest trends in the space communications industry. They are envisioned to make a major breakthrough in affordable global broadband capacity and other services – although no demonstration of the business case and its promises has been yet realized, to the date of writing this report.

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OneWeb and LeoSat are two notable examples of communication megaconstellations currently under development [28, 29]. When completed, the OneWeb constellation will consist of 648 satellites with mass of less than 150 kg operating in Low Earth Orbit [30]. LeoSat is another communication constellation consisting of 78-108 satellites operating on six orbital planes with an altitude of 1430 km for offering gigabit rate, low latency space-based internet with global coverage [29, 31, 32]. Recent trends in technology miniaturization also spurred the emergence of nanosatellite constellations. A notable example is 3U CubeSats developed and launched by Planet Labs, to date over 100 3U CubeSats have been launched with a goal of having 150 spacecraft constellation by the end of 2016. This will allow to image the entire land mass of the Earth every day with 3 to 5 m resolution in Red, Green, Blue and Near Infrared wavelengths [27]. Trains

Another distributed satellite proposition is offered by satellite trains such as NASA’s Morning [33] and Afternoon [4] constellations for Earth observation. Trains are coordinated groups of satellites that closely follow each other along the same orbital track. Trains are hybrid architectures featuring mainly heterogeneous components that perform independent missions [34]. When combined, these individual missions produce synergistic measurements thus satisfying overall mission objectives. NASA’s Afternoon constellation (A-Train) [4] satellites were launched on a 705 km Sun-Synchronous, near polar orbit with 1:30 pm ascending node equatorial crossing time and within a few seconds to minutes from each other. This multi-satellite approach provides several benefits by enabling a synthesis of a wide range of observations. A-Train allows multiple instruments to observe the same region of Earth within a short period of time thus eliminating the issues related to the temporal variation in observational conditions such as cloud coverage. Thus, the Afternoon Constellation enhances the science return by allowing to collect more synergistic measurements than could possibly be obtained by individual instruments as well as it improves the quality and accuracy of the results [14]. The train configuration is continuously evolving with satellites joining and leaving the system. Clusters

A cluster is an implementation of the distributed space system featuring two or more satellites flying in a close formation. Spacecraft in a cluster require accurate formation knowledge and control in order to precisely coordinate their activities for accomplishing mission goals. Satellite clusters have multiple potential applications such as space science interferometry and synthetic aperture techniques, which, in some cases, require micrometer and, even picometer knowledge and control [35]. Satellites within a cluster usually need an active control system to maintain and correct their orbits. Notable examples of satellite clusters include the Terrestrial Planet Finder Interferometer concept developed by NASA [36] and the Darwin mission developed by ESA [37]. However, neither of these missions was implemented. NASA’s Terrestrial Planet Finder Interferometer was cancelled in 2011 [38] and Darwin has not been selected in the frame of ESA Cosmic Vision 2015-2025 program [39]. Despite not being selected as part of 2015-2025 program, Darwin is still considered as a potential future mission, possibly in cooperation with NASA. Darwin is a cluster of four or five satellites designed to detect and characterize Earth-like planets. The aim was to perform high resolution imaging using aperture synthesis and nulling interferometry, requiring a control of the formation with a millimeter accuracy and with 15 m and 170 m range between the satellites [37].

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Swarms

Some implementations of distributed space systems such as constellations and satellite trains are relatively well established, whereas satellite swarms containing tens to even thousands of small spacecraft are still in an active research and development phase [40]. The strength of satellite swarms is in their enormous size; they are envisioned to contain hundreds and even thousands of individual spacecraft operating together to achieve their objectives analogous to animal swarms. Each individual space system in the swarm will undoubtedly have restricted capabilities but large swarm of small spacecraft could potentially produce a very capable network of space systems, which will allow to address questions of a local and global scale [40], it could enable some mission concepts that would be impractical, and even impossible, with current monolithic or multi-satellite missions [15]. Swarms are envisioned to contain nanosatellites and even femtosatellites with a mass of a few grams. The use of such small satellites are gaining increasing popularity promoted by recent advances in technology miniaturization and the ability to mass produce cheap spacecraft with commercially available components. The swarms could have numerous applications at much lower cost such as missions to characterize planetary atmospheres, to estimate the composition of asteroids, and to investigate the Earth’s ionosphere [15, 41]. One notable example is KickSat technology demonstration mission developed at Cornell University [15]. Fractionated Satellites Fractionated Spacecraft were proposed in the 1980s [42], but went largely unnoticed until 2006 when the U.S. Department of Defense started an ambitious research and prototyping program on this architecture, denominated F6 (Future, Fast, Flexible, and Fractionated, Free-flying Spacecraft United by Information Exchange) [10] but it was canceled in 2013 after about $200 million investment despite its ambitious goals [43]. Fractionated Spacecraft are the disaggregation of a monolithic satellite into heterogeneous, free-flying subsystems (Figure 2). This enables de-coupling of system functions such as for instance pointing, which allows to optimize pointing on the ground station thus maximizing the efficiency of the data transfer without compromising the welfare of the overall system. Decoupling is one of the main advantages of fractionated architectures, which allows the deployment of individual sensors independent from each other, thus enabling the customer to launch the most mature sensors and start the mission immediately instead of waiting for the development of the least mature sensors [12].

Figure 2 Block diagram comparing traditional and Fractionated Spacecraft.

PayloadModule

InfrastructureModules

FractionatedSatellites

PayloadModule

BusModules

TraditionalSpacecraft

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Additionally, fractionated spacecraft allow replacement or addition of particular subsystems and payloads in case of failures or mission goal changes, which will potentially extend the mission lifetime and significantly improve the system product quality as well as increase the overall system value for a relatively small investment. Contrary, monolithic systems need, in general, to be completely replaced in these events requiring much larger investment [19]. Although, a promising concept for improving system welfare and bringing efficiency and economies-of-scale to space [42] no fully fractionated system has been launched to date. Federated Satellites

Federated Satellite Systems (FSS) paradigm is one of the latest distributed space system concepts featuring opportunistic collaboration among fully independent and heterogeneous spacecraft analogous to peer to peer networks and cloud computing [13]. FSS paradigm envisions exceedingly dynamic and continuously evolving in-orbit infrastructure incorporating variety of missions (Figure 3), which will create a space-based resource market where individual missions act as a supplier or a customer depending on their particular needs. The space-based resource market could offer to the federation any underutilized capabilities such as downlink bandwidth, storage, processing power, and instrument time. Design margins built in spacecraft and changing operational schedules mean that some large spacecraft do not use 100% of their capabilities constantly, thus creating unused resources that the satellite operator could sell to other satellites in the federation and generate additional revenue during sub-peak performance periods consequently diminishing the financial risks of the mission. On the other hand, participating satellites could be deliberately designed with lower capabilities such as having smaller storage capacity and relaying on the federation for some of their functions, consequently reducing the total mass of each unit spacecraft. Additionally, participating satellites can increase their overall downlink capabilities via data relay through the federation. The use of the space-based resources could relax the spacecraft design constraints as well as reduce the total spacecraft development cost [11, 13]. FSS concepts also create opportunities to deploy software-based virtual missions [13].

Figure 3 FSS concept, where missions perform relays and distributed processing for others while retaining operational independence.

FSS is envisioned to improve the overall welfare of the federation by creating benefits such as improved performance and reliability as well as enhanced cost-effectiveness through networking multiple independent and heterogeneous elements. One of the advantages of FSS

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is its closeness with current space industry practices compared to other advanced DSS concepts – federated missions are still independent, posing a less dramatic transition compared to fractionated spacecraft. FSS also enhance the overall sustainability of the missions by allowing the utilization of small satellite platforms for Earth Observation and interplanetary exploration missions that would not be achievable without FSS infrastructure. In summary, FSS is a promising concept for enhancing the reliability, affordability, sustainability, scalability, and flexibility of space-based assets [11]. Conclusion

This study has surveyed the state of the art in distributed satellite systems including historic and current research and development efforts for providing a unified classification for the widely explored distributed architectures specifically Constellations, Trains, Clusters, Swarms, Fractionated Satellites, and Federated Satellites thus enabling consistency in defining various distributed architectures independent of the individual mission framework. Acknowledgments This study was part of the ONION “Operational Network of Individual Observation Nodes” project and it has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 687490. References [1] C. G. Green, P. Massatt, and N. Rhodus, "The GPS 21 primary satellite constellation", Navigation, vol. 36, pp.

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