SSA or Space Situational Awareness is without doubt one of the most pressing challenges that the space industry faces. With orbits becoming increasingly crowded and a slew of mega constellations of small satellites either in the process of being lofted or expected in the near future, definitive action is required to manage the risks that so many objects could potentially pose. Spacewatch.Global’s Chairman Dr. John B. Sheldon was fortunate enough to sit down with Dr. Moriba Jah of the University of Texas and a pioneer in Space Situational Awareness to talk about what’s wrong with the current approach and how this growing problem can be tackled.
What’s wrong with the way Space Situational Awareness is currently done, in your opinion, that leads to this lack of transparency and clarity in terms of, for example, precise locations of objects?
I would start off by just loosely defining SSA as the knowledge required to make decisions in space. And that in itself is very subjective, because different people make different types of decisions. Therefore, I think one of the major issues is a lack of standardisation in these types of decisions and a lack of agreement on what those sorts of decisions would be. This is because everybody has their own subjective criteria. We don’t have a lingua franca when it comes to SSA.
The second issue, I feel, is that people are not aware of the ramifications of the information they might provide. Somebody might want to be very forthcoming, but there’s a lot of paranoia that revealing too much might negatively impact their business model, which might also impact upon their ability to behave the way they want to behave in space without everybody knowing every detail of their thought process.
It comes back to this idea of making things 100% predictable in space. Even though people would like that from a safety perspective, they don’t want that from an “concept of operations” perspective. The question is, how do you get one without the other and people still don’t know how to bridge that gap.
So, there is a lack of a standardisation in the types of decisions that need to be made, a lack of a lingua franca. Then there is this unknown element of wanting to be safe but at the same time not wanting to reveal all business plans to others that might provide them with the ability to predict every move with regards to “concept of operations” in other words, proprietary or “competitive” information. The medical community has gotten around many of these issues with protecting client anonymity whilst being able to do meaningful data science. We need to look at that model, in my opinion.
Regarding the second part of the problem, is what is required perhaps of a cultural change in terms of how commercial and governmental operators do things in space?
Let’s look at so-called mega-constellations, for instance. Some people are very reluctant to release the exact information on their thrusters and specific spacecraft models. As someone that studies the motion of things in space, I would want to know all of those things in order to model and predict their behavior. However, instead, if a satellite operator would say give me a reference path where they will fly the satellites, they don’t have to tell me how they will fly these paths but that they will be plus or minus 50 metres off of this path at any given time. That allows them to keep all this proprietary information and it allows me to be able to do my safety planning. I think that there is a way to get around this stuff if people just got in a room and agreed to some terms of reference. Choose reference orbits, and fly these to a prescribed precision, and be done with it! Develop joint or community-wide protocols for what each person will do given a predicted conjunction.
So that would apply not just to companies like SpaceX with Starlink and LeoSAT and so on. But would that say, for example, apply to US government, the US military, the Russian military, the Chinese?
Absolutely. Here’s the thing, and this is what I’ve told to the different Ministries of Defense. Just like initially with GPS, you had selective availability. With dithering the “signal” you can give a reference trajectory and whatever the pluses or minuses you get to choose that it doesn’t have to be based on your actual capability. You know, you can make that error bar slightly larger. Maybe you have a sensor that gets you metre-level knowledge. But that’s not necessarily what you have to provide to the plan. In essence, provide a trajectory with so-called epistemic uncertainty (based upon systematic effects) instead of providing one with aleatory uncertainty (based upon randomness). Probabilities can’t describe all uncertainty, only randomness. Let’s start getting people more used to that fact.
Okay, so really, then it’s not really so much a cultural issue. Although it’s partly that, it then becomes an issue related to the first part of the problem set, which is the lingua franca, and a more Breton, much more tightly defined set of standards that would be required of all operators to adhere to in order to get that level of safety and, if you will, certain amount of transparency that we’re looking for in order to make this work.
Yes. As another example OneWeb approached me and brought up the fact that other constellations that are going to be in similar altitudes and what if their posture for safety and risk is very different from OneWeb’s. Theoretically, OneWeb could spending all their fuel manoeuvring out of somebody else’s way. So even varying levels of risk tolerance affects SSA. And again, there’s no agreement on these things either.
Okay, so and that could potentially become a regulatory issue then.
What are the real risks with these mega-constellations? Obviously, there’s a commercial opportunity, but that’s not a risk-free proposition.
In my opinion, one of the examples that I’ve given before is this idea of air traffic, and how air traffic has gotten a lot more dense because we have more accuracy and precision in that domain. All the decisions about what happens in space are also based on some measure of uncertainty (precision) because we don’t know the truth. When there’s large uncertainty, it’s very difficult to make decisions.
Imagine if you had a number of vehicles on the autobahn – and people like to drive fairly quickly on the Autobahn – but all of a sudden, you go from a clear day to dense fog. What happens? People get into accidents, not because the traffic has changed in any way and not because the number of cars has changed in any way; but it’s just the uncertainty of where the road is and where other things are in relation to each car. The introduction of uncertainty leads people to panic and to make decisions that can lead to bad outcomes. To me, this is very similar in space. There’s just a cloud of ambiguity in terms of what’s up there, where it’s going, how it’s behaving, and that permeates in the decision making process…our ability to predict is significantly hindered! If space were really transparent and predictable, even so far as major constellations, we would probably be saying, “there’s so much space we should be packing the skies with objects.” But because we have all this ambiguity, this orbital information entropy, as I call it, that’s the thing that really prevents informed decision making.
To me, the biggest risk of constellation management is ignorance of the environment (large epistemic uncertainty) and this lack of this lingua franca. The risk is less physical and more statistical. It’s this epistemic uncertainty of orbital space that needs to be properly managed.
Okay. And, presumably, of course, you and your team have a solution to this?
We have ideas, right.
You have ideas? Okay.
Yeah, we have ideas that need to be implemented. They need to be tested rigorously, comprehensively. I have no solutions. I have ideas that need to be tested.
Okay. And this is the work of your laboratory?
Yes. At the University of Texas at Austin, we have this programme called ASTRIA which has several components to it. One of it is completely computational. We have the Texas Advanced Computing Center (TACC), one of the world’s largest high performance computing platforms. We have a graph database (ASTRIAGraph), where we’re carrying out crowdsourcing of information related to space. We try to bring all these disparate sources of information together and combine them into a common framework, a “common operating picture” for military types. Then, when you go to the website, there’s an application that at least queries the database for orbital locations and displays that to the user.
We actually have an API that we’ve developed, and we’re allowing people to get to get accounts on the TACC. We can give them API permission to interact with the graph database itself because what we want to get to the point where people can input information and make queries that can obtain information out of the graph. The interesting thing is that nothing gets overwritten. So our graph is like entropy in the universe, it’s always increasing. Whatever the source of information, we don’t necessarily try to constrain veracity or any of these things. We just say, hey, we’re getting information and here are all these opinions.
We’re also looking at the policy side of things. We have the Robert Strauss Center for International Security and Law at the University of Texas in Austin where I’ve been designated the lead of a Space Security and Safety program. We have an annual space traffic management conference at the end of UN COPUOS STC here in Austin at the end of February to bring policy and scientific-type people together.
There are several things that we’re trying to do. There’s a soft science policy piece to this puzzle that’s critical. We can’t fix this problem without the lawyers and the policymakers and even the geography. You know, people have said, there’s no geography in space. And I say there is geography in space – you just don’t know how to look for it. There are geographical signatures.
These are all things that we’re doing at the University of Texas at Austin.
And on the policy side, is it an ambition of yours and your team’s that you might trigger some sort of amendments to the Outer Space Treaty or some additional international instrument that can help provide at least parameters in which national legislators, for example, can start bringing about this lingua franca in terms of common regulatory frameworks?
Absolutely. This morning alone, I got an email from the US State Department regarding a proposal for the next Working Group, within COPUOS to look at implementation of the 21 guidelines that were adopted by consensus. For instance, I know that there are organizations that have observer status at COPUOS, like the International Institute of Space Law, like ISO and I belong to a few of these organisations.
One of the things that I learned living on Hawaii is that you need to be part of the community (work the aina), or else you don’t make it. And so my thing with the space community is to be part of it. I have students and researchers that are part of this. We need to participate to start shaping these things. One of the things that I want to bring to the table is evidence-based policymaking – bringing in real evidence to back up effective policy.
Congratulations on the Space Sustainability Rating, by the way, I know you’re a big part of can you tell us more about the initiative and what you expect to come out of it?
This was a very pleasant activity.
In order to encourage good behaviour in space, the World Economic Forum announced in early May, that a team from the Massachusetts Institute of Technology (MIT) Media Lab and a team from the European Space Agency will work together on a Space Sustainability Rating (SSR) which will serve as a metric to define how well an individual satellite or system follows guidelines to ensure space sustainability. The University of Texas at Austin will provide the technical and space law/policy considerations components of the SSR and we will work together as a cohesive team.
There’s recently been a meeting in Vienna that basically attempted to bring more of the community into the idea of the SSR. The SSR is going to be much like a rating for restaurants and hotels, which is trying to incentivise behaviours that operators and launchers can take that lend themselves towards improved sustainability.
I tell people that we don’t want to be making the rules. It’s our job to take things that have been currently adopted or currently accepted by the community and to try to implement those within the rating.
We need to identify which of these guidelines is measurable by which what means. It needs to be independently verifiable because the rating is not going to be a static thing. They will change based on the behaviour of the operator from one week to the next. We need to be able to monitor activity and then the rating can be adapted based on evidence. Again, the foundational piece is the measurement. You can’t know what you don’t measure! But taking what the community is already accepted as these are things that we believe, by consensus leads to sustainability. Companies such as SpaceX and OneWeb say that they don’t believe these guidelines are good enough and that there should be more stringent rules and constraints. To these people I say, I don’t disagree with you but there needs to be community acceptance. The community needs to say, “yes we agree.” And so I think vehicles like the UN are good mechanisms. It will take time but these mechanisms enable us to get “buy-in” from everybody because the rating is only as useful as the community that actually implements and makes use of it. People need to see what the benefit is to them.
One last question. We’ve already discussed ASTRIA and your new lab and what they’re doing but what are your future plans in terms of the research you’re doing? Where’s your current research leading you and what was interesting you for the foreseeable future?
Even though I’m an engineer at heart, meaning that I’m all about solving problems, there is an aspect to me that’s very much a scientist and about growing the knowledge base. There’s just so much that’s unknown about what’s going on in space. There’s a lot that still unknown about what are the effects and impacts of the space environment on space object behaviour.
Here’s the thing. People keep on talking about wanting to know what normal behaviour is in space. We are very far from knowing that, from a physics perspective. There are still big scientific gaps in understanding based on size, shape, material properties. It’s like a piece of plastic in the ocean and being able to predict where that’s going to go and how that’s going to behave. Space is just much more challenging in many ways and so the equivalent of tracking the plastics in the ocean.
I want to be able to have global space environment models that let me track the pieces of garbage in space and maybe there’s some benefit that can come from that. But I would say the more challenging thing above and beyond that is looking at how to bring semantic information to complement the physics-based information. Just as radars and telescopes are sensors of physical things in space, natural language processing is a sensor of semantic things. There’s this whole body of semantic information with tweets, with Space News reports with your own magazine and activities.
I’d like to use natural language processing to sense relevant information there and to couple it with the physics to have a better understanding of what’s going on in space. Even when it comes to the 21 UN COPUOS Long term Sustainability guidelines, implementing those is different based on culture. What is Sharia interpretation of the guidelines? Do Jewish people manoeuvre their satellites on Shabbat? The thing is, there’s no standard implementation across the globe. That cultural lens is another thing that I’m trying to bring into my research because all of this needs to be computational. We can’t physically have human beings in a room trying to manage all this information. You have to bring the soft science piece into a computational framework. So I can represent an astrodynamicist with algorithms. How do I represent political scientists with algorithms? I don’t know that. That seems like a tough one for me. So these are the major challenges that I’m looking at trying to solve and discover ways to solve deal with that in the in the near term.
Moriba Jah is an Associate Professor in Aerospace Engineering and Engineering Mechanics as well as the director for Computational Astronautical Sciences and Technologies (CAST), a group within the Oden Institute for Computational Engineering and Sciences at The University of Texas at Austin. Moriba came to UT Austin by way of the Air Force Research Laboratory and NASA’s Jet Propulsion Laboratory prior to that, where he was a Spacecraft Navigator on a handful of Mars missions.
Moriba is a Fellow of multiple organizations: TED, American Institute of Aeronautics and Astronautics (AIAA), American Astronautical Society (AAS), International Association for the Advancement of Space Safety (IAASS), Royal Astronomical Society (RAS), and the Air Force Research Laboratory (AFRL). He has served on the US delegation to the United Nations Committee On Peaceful Uses of Outer Space (IUN-COPUOS), is an elected Academician of the International Academy of Astronautics (IAA), and has testified to congress on his work as related to SSA and Space Traffic Management. He’s an Associate Editor of the Elsevier Advances in Space Research journal, and serves on multiple committees: IAA Space Debris, AIAA Astrodynamics, IAF Astrodynamics, and IAF Space Security.