Sensitivity of long-term orbital debris environment evolution to the deployment of nano-satellite swarms

Pergamon

Vol. 5 1, No. 1-9, pp. 439-449, 2002 0 2002 Published by Elsevier Science Ltd Printed in Great Britain 0094-5765/02 $ - see front matter

Acta Asrronoutica

PII: SOO94-5765(02)00095-4

www.clsevier.com/locate/actaastro

SENSITIVITY

OF LONG-TERM ORBITAL DEBRIS ENVIRONMENT EVOLUTION TO THE DEPLOYMENT OF NANO-SATELLITE SWARMS R. Walker, C.E. Martin, P.H. Stokes

Space Department,

QinetiQ Ltd, Cody Technology Park, Farnborough,

Hams., GU14 OLX, UK

H. Klinkrad European Space Operations Centre, Robert Bosch Str. 5, D-64293 Darmstadt, Germany cost way of providing distributed coverage for monitoring, environment applications in space communications, remote sensing, and spacecraft close inspection. The first three applications listed all involve either a classical orbital arrangement of a satellite constellation or swarms of nano-satellites in the same orbit flying in a co-operative formation to create a large ‘virtual’ antenna area.

ABSTRACT Nano-satellites, classified as having a mass in the kilogram range; appear to be emerging as a growing industry in recent years. They offer affordable access to space on only a modest budget, or, due to their smal! size, they can be easily deployed in large numbers or ‘swarms’ in a distributed network for many different civil and military applications. However, if their popularity grows significantly, then the sheer number of nano-satellites added to the most populated regions of low Barth orbit would increase the collision risk and add to the space debris problem in the long-term The current proposals for nano-satellite missions are reviewed in this paper. An overall outlook for the nano-satellite industry and for a nano-satellite launch traffic model is given. Then, a sensitivity study is conducted to analyse the long-term impact of nanosatellite swarms on the orbital debris environment for different generic mission designs. These designs vary in terms of the number of satellites and the satellite mass. It has been found that the deployment of a single nano-satellite swarm consisting of a thousand or more members into the most crowded region of low Earth orbit would have a modest, but observable impact on the future collision rate and debris population growth. Q 2002 Published by Elsevier Science Ltd.

Given the small mass of these vehicles and the ease of manufacture, it is possible that hundreds of nanosatellites may be ‘dispensed’ from a single launch vehicle upper stage or ‘mothership’ in order to perform the function of expensive conventional spacecraft. Hence, potentially over a thousand nano-satellites may be injected into orbit with only a small number of launches. One potential problem is that these nano-satellite swarms might be too small to be tracked,by space surveillance networks. In this scenario, the large operational satellites might not be able to ‘see’ the nano-satellite swarms in terms of tracking data for close approach predictions and collision avoidance manoeuvTes. However, with typical impact velocities of lo-15 km/s in Low Earth Orbit (LEO), the nanosatellites would be sufficient in mass to cause, on impact, the catastrophic fragmentation of a large satellite or launcher upper stage, leading to enhanced collision activity in the long-term Another potential problem is related to how nanosatellites might comply with orbital debris mitigation standard practices, such as de-orbiting at end-of-life in LE@. Some nano-satellites with a low enough altitude would naturally decay due air drag within the specified post-mission lifetime limit (e.g. 25 years). However, other such platforms orbiting at higher altitudes where air drag is much lower may require some form of additional active propulsion system (e.g. cold gas thruster or microthruster array) or an alternative system (e.g conducting tether or inflatable ballute). Many such de-orbit systems will add size, mass, complexity and cost to nano-satellite missions whose success depends upon keeping the design small and simple. However,

INTRODUCTION The development of Micro Elecno-Mechanical Systems (MEMS) technology and miniaturisation of components, sensors, connol systems and computer hardware has led to the concept of manufacturing and launching small ‘nano-satellites’ (mass of I-10 kg) in orbit at a very low cost’. In fact, a whole industry is emerging based in the premise that these small satellites can provide affordable access to space for many who were previously priced out of the space marke?. Nano-satellites appear to be very promising as either cheap technology demonstrators or a much lower

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the cost to the space environment of leaving hundreds of nano-satellites in the already crowded low Earth orbit for extended lifetimes may be non-negligible in the long-term. It is the objective of this paper to make an initial assessment of this long-term impact. REVIEW OF NANO-SATELLITE

MISSIONS

The nano-satellite missions already launched into orbit and those planned for deployment are listed in Table 1. The authors bear no responsibility for the accuracy or completeness of this data, since much of the information was taken from the world wide web. There are also a number of smaller satellites with a mass of 0.1 to 1 kg (pica-satellites) and larger satellites with mass of 1 to 30 kg (micro-satellites), so these were also included in the tables. As we can see from Table 1, the present overall status of the nano-satellite industry is still very much at the early technology demonstration stage. There are many proposals and projects, consisting of single or several satellites, which probably will get into orbit due to the extremely low costs involved. However, to date there have been no firm plans for large-scale nano-satellite constellations and swarms, although they may be deployed in large numbers after more extensive inorbit testing of prototypes and standardised manufacturing processes are established. Launch costs can be very low by taking advantage of a ‘piggyback’ launch on a larger rocket (e.g. Delta or Zenit) along with a large primary satellite. Alternatively, there are also a number of small launch vehicles which can offer a dedicated launch of a few micro-satellites or nano-satellites at a low cost (e.g. Shtil, Minotaur and Dnepr, which are essentially converted ballistic missiles, Cosmos 3M and Soyuz U). Given the extremely affordable access to space and commonly available microelectronic components, we may expect the nano-satellite market to mature and grow in the next decade. This should be especially the case when the advantages of low cost, distributed networks in space are clearly demonstrated, and host platforms accomodating many nano-satellites are used for the deployment of single swarms. However, due to the lack of any firm large-scale nanosatellite constellation/swarm proposals at this early market development stage, it was concluded that a general nano-satellite launch traffic model could not be produced. Therefore, the next best option was to conduct a sensitivity study describing the long-term impact of nano-satellite swarms on the orbital debris environment for a limited number of generic spacecraft

and mission designs. The European Space Agency (ESA) Debris Environment Long Term Analy& (DELTA) model was used for this purpose. THE ESA DELTA DEBRIS MODEL The DELTA model is developed by QinetiQ (a company with origins in the former UK government Defence Evaluation & Research Agency) in Famborough, UK, for the European Space Operations Centre. DELTA has been proven to be a robust, reliable tool for the long-term prediction of the orbital debris environment and its associated mission collision risks. It is currently being heavily utilised to provide analysis data for the update of the ESA Space Debris Mitigation Handbook4”. The model allows the user to investigate the long-term environmental effects of a wide variation of satellite constellation deployment scenarios and realistic debris mitigation measure strategies, such as explosion prevention, and postmission disposal. This latter option includes atmospheric drag de-orbiting within a given orbital lifetime limitation and re-orbiting to a given storage orbit altitude band6.‘. Based on any of the future debris environments generated for debris larger than 1 mm over the lOOyear evolution period, DELTA is able to provide predictions of collision risk over the lifetime of any user-defined, Earth-orbiting space mission. This includes the impact direction, impact velocity, orbit revolution angle and mission time dependencies of the debris flux with respect to the target orbit. DELTA version 1 uses the ESA MASTER-99 model reference population as inpm allowing the inclusion of all major sources of debris larger than 1 mm in size, such as launch-related objects, explosion f&ments, collision fragments, sodium-potassium liquid coolant droplets, and slag particles from solid rocket motor (SRM) ftigs*. The evolving population within DELTA is defined by individual representative objects. A fast, analytical orbit propagator is used to propagate the orbits of these objects taking into account geopotential, air drag, luni-solar and solar radiation pressure perturbations during the loo-year simulation. The individual representative objects have full classification and origin information available so that the model is transparent to the user, thus enabling the identification of population histories for any simulated constellation, breakup cloud or debris source type. Additionally, the spatial density and mission collision risk results can be given for different source types.

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Table 1. Launched and planned satellite missions with mass ~30 kg

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The DELTA model is able to generate a highresolution representation of the evolving debris flux environment. This comprises yearly snapshots with the dimensions of altitude (25 km bins), declination (5” bins), size (7 logarithmically-spaced bins covering lmm to 10 cm and larger), and debris source type. The model employs the same techniques as MASTER to determine these flux environment snapshotsg. In order to maintain this high-resolution aspect, a very detailed future launch traffic model is used. This is based on historical launch data to ensure that the known orbit and mass distribution of the launch-related source is extrapolated in the future projections. Achieving a declination dependency in the debris flux environment snapshots requires that the orbital inclination distibution of mtrure collision brealltp activity is correctly modelled. The DELTA model utilises a novel ‘target-cenned’ approach to collision event prediction, in order to stochastically predict catastrophic impacts for large target objects in the evolving DELTA population. This technique allows the inclination of the target object to be fed into the inclination breakup model, so that the correct distribution of collision fragments can be simulated for each predicted event. Additionally, the technique has been extended to analyse the type of impactor causing the collision breakup. Hence, DELTA has the capability to distinguish between different types of future collision activity, such as background and feedback collisions. Thus, the analysis of feedback collisions can allow conclusions to be made on the collision cascading process and long-term environment stability. A further, more detailed account of the DELTA model and its methodologies can be found in the DELTA contract fmal report”. Most recently, the DELTA model has been upgraded to version 1.3 and now incorporates SRM slag particles as a future source of debris. The generation of slag particles has been harmomsed with the approach used to produce the MASTER 99 SRM slag population’. The overall performance of the model has been enhanced (whilst retaining the same high resolution) in order to enable the prediction of long-term debris environment evolution in LEO, Medium Earth Orbit (MEO) and Geosynchronous Earth Orbit (GEO) simultaneously. Three separate control volumes are used for this purpose, with the GE0 control volume having a third dimension in right ascension, in addition to altitude and declination. The simulation of reorbiting to storage regions is now possible for LEO, ME0 and GEO. The fast orbit propagator has been upgraded by the addition of the Jzz tesseral harmonic geopotential perturbation, and an improvement to the solar radiation pressure perturbation accuracy. A low

impact-velocity breakup model has also been added in order to simulate the generation of fragments horn collisions in GEO”. SENSITIVITY

ANALYSIS

Study Deftition In evaluating the potential long-term impact of nanosatellite swarms, we have chosen to perform loo-year projections of the LEO debris environment using the DELTA model for three different future spaceflight scenarios: 1.

of recent historical Reference - continuation launch and explosion activity into the long-term tutme, with no future satel!ite constellations deployed or mitigation measures implemented.

2.

Nanosat Swarm 1 - same as Reference, but with additional deployment of 1000 nano-satellites in a circular orbit at 800 km altitude with 98” inclination; each nano-satellite is a 10 cm sphere with mass of 1 kg.

3.

Nanosat Swarm 2 - same as Reference, but with additional deployment of 100 nano-satellites in a circular orbit at 800 km altitude with 98” inclination; each nano-satellite is a 30 cm sphere with mass of 10 kg.

In both of the nano-satellite swarm deployment scenarios, the chosen deployment year is 2010. We have assumed that the nano-satellites have no on-board propulsion for station-keeping and hence, they are left to undergo orbital decay due to atmospheric drag. The area-to-mass ratio is approximately 0.008 m*/kg. The stochastic nature of modelling future debris sources such as collisions, explosions and launches requires DELTA to be used in a Monte Carlo mode to represent different statistical permutations of long-term evolution. In order to obtain a reasonable statistical average of the long-term evolution trends, 10 Monte Carlo simulations were run for each of the three scenarios. This leads to a standard deviation of approximately +/- 10% in the DELTA results. All cases use the ESA MASTER-99 model reference debris population of objects larger than 1 mm. Longterm evolution is predicted by DELTA from 1 August 1999 to 1 January 2100 with a 6-month frequency of collision event prediction and yearly output of the debris flux environment snapshots. A fragmentation threshold of 40 Jig impactor energy-to-target mass ratio has been used to determine collision-induced breakups.

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The future launch traffic model has been derived from historical launch activity between 1990 and 1998. Overall, the model predicts an average of approximately 330 launch and mission-related objects per year to be added to the evolving population in DELTA. The future explosion traffic model has been derived from analysis of the MASTER-99 model’s historical fragmentation events data tile between the years of 1991 and 1999. Geopotential, atmospheric luni-solar, and solar radiation pressure drag, perturbation models are used to propagate the debris population with g-day timesteps in these study cases. Reference Scenario The DELTA model has been updated to incorporate future SRM slag particles and the Reference scenario is subtly different from that employed in previous publications containing DELTA rest&“. Namely, communications future satellite constellation deployments have been removed. Tbis omission was mainly due the current uncertainty concerning the commercial viability of such large space projects. Given these changes, this section presents a detailed view of the updated DELTA long-term LEO debris environment projections for the Reference scenario.

Figure 1 shows the predicted future LEO collision activity, with the total mean number of catastrophic collisions broken down into the three categories of background collision, feedback collision and constellation-related collision. A background collision is defined as a collision &agmentation involving objects in the background population, for example satellites, rocket bodies, and explosion fragments. A as a collision feedback collision is defined fragmentation caused by the impact of a collision fragment (generated during an earlier collision event). A constellation-related collision is defined as a collision tiagmentation of a constellation satellite caused by the impact of any other object. As we can see from the exponential trend in the figure, the overall LEO collision rate is predicted to continuously increase over the next century. This is due to the steady accumulation of objects from continued launch and explosion activity. Most of this collision activity would involve members of the background population of large objects, but feedback collisions start to become increasingly common in the latter half of the next century in this case. This is a sign that the so-called collision cascading process’* or collision chain reaction’3 has been initiated. The constellation-related collisions are negligible in this case because only the currently operating constellations

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Year Figure 2. Predicted long-term evolution of the ~10 cm debris population in LEO for the Reference scenario such as Iridium, Globalstar and Orbcomm have been included from the MASTER-99 reference population. No new constellations have been simulated. Figure 2 shows the predicted long-term evolution trend of the LEO population of objects larger than 10 cm in size for the Reference scenario. The total average number of objects has been broken down into the debris source types of launchmission related objects (satellites, rocket bodies, operational debris), explosion fra,oments and collision fragments. The linear increase in the total population is mainly due to the dominance of explosion fragments in DELTA at decimetre debris sizes over the period of the simulation. Launch/mission related objects also show a linear increase due to the constant overall launch rate used. However, we can see that the increasing level of collision activity induces exponential growth in the collision fragment population, eventually reaching similar levels as the other debris sources by the end of the century. In turn, this leads to the increasing rate of feedback collisions and so on. The modulating effect of the 1 l-year solar cycle on the population can also been seen here. Figure 3 presents trend of the LEO than 1 cm in size. been broken down

the predicted exponential evolution debris population of objects larger The total population curve has again into the different debris source type

contributions, so that we can observe the underlying influences. The non-fragmentation sources of sodiumpotassium droplets and solid rocket motor slag particles are also relevant for this size threshold. These two sources both appear to be second-order components of the initial population, although both are known to have more significant localised contributions in certain altitude bands8*‘4. The NaK droplet population reduces over time to zero, since we assume that this source has already ceased and the existing droplets decay under the influence of air drag. The SRM slag particle population is projected to increase slightly over the next century, since we assume in the simulation that SRM firings continue at the same rate as recent activity in this scenario. Significant growth is not predicted for this source, since most of the firings are related to the injection of payloads into a Geostationary Transfer Orbit (GTO). This process generates SRM slag particles on similar GTOs with low perigee altitudes, and hence subject to removal via air drag decay. The explosion fra,ment population is the most srgniticant contributor to the initial population at centimetre sizes, but is predicted to have a similarly slow growth as the SRM slag particle population over time. This is because the rate of high intensity

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Year Figure 3. Predicted long-term evolution of the >l cm debris population in LEO for the Reference explosions has slowed over recent years and is mainly limited to low altitudes where atmospheric drag constrains the lifetime of the fragments. This trend is continued into the future projections. The collision fragment population is negligible for the present day. However, the increasing rate of future collisions in the unmitigated Reference scenario induces an exponential growth in the centimetre-sized collision fragment population. This population is predicted to surge above the slow-growing explosion fragment population in the latter half of the next century to become the dominant source of the hazardous centimetre-sized debris in LEO. This is the main reason for the introduction of mitigation measures that can stabilise and bring mture collision activity under control. Recent studies have corrfinned that the post-mission disposal of LEO space vehicles into orbits with limited lifetime (e.g 25 or 50 years) would be an effective measure in this respect’VL5*16. Imnact of Nano-satellite

Swarms

The orbit chosen for the introduction of the two swarm designs is very much a worst case scenario in terms of the highest collision risk. However, it is still realistic that nano-satellites may be deployed there in the future

scenario

for the various applications mentioned earlier. The long-term environment projections in the Reference scenario have been explored and explained in detail. We can now determine the long-term impact of nanosatellite swarm deployment by observing any deviations in the results Tom those presented in the Reference scenario. Before addressing their impact on the overall projections, it is useful to analyse any localised increase in the large object population induced by each nano-satellite swarm design. Figure 4 displays the predicted evolution of the spatial density distribution over altitude for objects >lO cm in the Nanosat Swarm 1 scenario. The deployment of 1000 nano-satellites at 800 km altitude in the year 2010 can be clearly observed. The swarm deployment more than doubles the spatial density of large objects at 800 km Thereafter, the peak in spatial density generally rises over time, due to underlying growth in the background population and any extra collisions involving the nano-satellites. The three sharp drops in the spatial density peak over the loo-year projection period are associated with points in time where the nano-satellite swarm transits into a lower altitude bin (with lower spatial density) due to natural air drag decay. In total, the swarm only decays by about 100 lan in 90 years.

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Figure 5 presents a similar plot for the Nanosat Swarm 2 scenario. Here, we can see that the deployment of a 100 nano-satellite swarm (each with a mass of 10 kg) would have a negligible impact on the large object spatial density at 800 km in the year 2010. There is already an average of 800 or more large objects in the 25 ion altitude bin centred around 800 km by the year 2010. Therefore, the introduction of the swarm is barely noticeable. The predictions of the overall collision activity in LEO for the three future scenarios are compared in Figure 6. Only catastrophic collisions are considered. It can be seen that the 100 nano-satellite swarm is predicted to have no influence on future collision activity. This result is not surprising, considering the small number of swarm members compared to the background population at the orbital altitude of the swarm However, the 1000 nano-satellite swarm does produce a small, observable increase in collision activity, which is just beyond the +/- 10% standard deviation in the results. There is an average of 5 collisions more, compared the Reference scenario after 100 years of evolution, representing an increase of 13%. The effects of the extra collision activity caused by the 1000 nano-satellite swarm can be seen in Figures 7 and 8, which compare the >lO cm and >l cm population

projections respectively. In Figure 7, there is a step increase of 1000 objects in 2010 when the swarm is introduced. By the end of the simulation, the gap has grown to nearly 3000 objects >lOcm higher than the Reference scenario. A similar proportional increase in the >l cm population level is also evident from Figure 8. The extra collision activity produces an additional 50,000 objects >l cm on average, after 100 years of evolution. CONCLUSIONS A preliminary sensitivity analysis has been performed with the upgraded DELTA model (version 1.3) in order to predict the long-term impact of nano-satellite swarms on the orbital debris environment. The results from this analysis show that the deployment of a nanosatellite swarm consisting of a thousand or more members into the most crowded region of low Earth orbit would induce a modest, but observable impact on the future collision rate and debris population growth. This is due to the large number of objects orbiting in a narrow altitude band, which significantly increases the localised destructive collision risk to larger objects.

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52nd IAF Congress Such a swarm can be deployed from a small number of launches at a relatively low cost by government (civil or military), academia (for scientific research) or purposes). commercial industry (for private Additionally, nano-satellites tend not to have on-board propulsion systems to minimise size and mass, thus preventing their removal from orbit by conventional means. With long orbital lifetimes of a hundred years or more at higher orbital altitudes, novel cost-effective de-orbit solutions may have to be devised in order to remove nano-satellite swarms from orbit within the post-mission lifetime constraints specified in orbital debris mitigation guidelines. Measures to improve the visibility of these small satellites to space surveillance networks may also be needed, so that larger conventional satellites can take evasive action during a close conjunction event. The sensitivity analysis conducted in this paper was a fust step, since it was based on only two different generic swarm designs and an unmitigated future debris environment. Our next step in this research is to extend the variety of swarms designs (in terms of satellite numbers, orbit, mass etc.) and determine the long-term impact of nano-satellite swarms on mitigated future debris environments. ACKNOWLEDGEMENTS The work presented of the ESA/ESOC Debris Mitigation the ESA Handbook

in this paper was performed as part contract ‘Update of the ESA Space Handbook’. The second edition of is planned for release in 2002. REFERENCES

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10. Walker, R., G.G. Swinerd, J.E. Wilkinson, C.E. Martin, Long Term Space Debris Environment Prediction, Final Report of ESAlESOC Contract 12808/98/D/IM, March 2000. 11. Martin C.E., Stokes, P.H., Walker, R, Khnkmd, H., The Long-term Evolution of the Debris Environment in High Earth Orbit Including the Effectiveness of Mitigation Measures, paper IAA-Ol-IAA.6.5.07, 52”d International Astronautical Congress, Toulouse, France, October l-5,2001. 12. Kessler, D.J., Collisional Cascading: The Limits of Population Growth in Low Earth Orbit, Adv. Space Rex, Vol. 11, No. 12, pp. 63-66, 1991. 13. Eichler, P., Rex, D., Debris Chain Reactions, AIAA AIAANASADOD Orbital Debris 90-1365, Conference: Technical Issues & Future Directions, Baltimore MD, April 1990. 14. Kessler, D., Johnson, N., Stansbery, E., Reynolds, R., Siebold, K., Matney, M., Jackson, A., “The Importance of Nonf?agmentation Sources of Debris to the Environment”, Adv. Space Res., Volume 23, Issue 1, pp. 149-160, 1999. 15. Krisko, P.H., Johnson, N.L., EVOLVE 4.0 Orbital Debris Mitigation Studies, Adv. Space Res., 2001. 16. Anselmo, L., Cordelli, A., Jehn, R., Pardini, C., Rossi, A., Effect of Mitigation Measures on the Long-term Evolution of the Debris Population, Adv. Space Rex, 2001.