2024 Air, Space & Cyber: Missile Warning

The “Missile Warning” session at AFA’s 2024 Air, Space & Cyber Conference featured Jeff Schrader, vice president of strategy & business development at Lockheed Martin Space; Kelle Wendling, president of Space Systems at L3Harris; and P. Len Orlando III, senior business development executive at Ansys. The session, held on September 18, was moderated by Jennifer Reeves, senior resident fellow for space studies at AFA’s Mitchell Institute for Aerospace Studies. Watch the video below:

Panel Moderator: Jennifer Reeves, Senior Resident Fellow for Space Studies, AFA’s Mitchell Institute for Aerospace Studies:

Good afternoon, everyone. My name is Jennifer Reeves, and I am delighted to welcome you to this afternoon’s panel on missile warning. Today, the United States and its allies are confronting an increasingly multi vector threat environment from various state actors. North Korea continues to advance its ballistic missile program, while Iran pursues both ballistic and cruise missile capabilities, China and Russia are pushing the boundaries of missile technology, developing hypersonic glide vehicles and exploring concepts like fractional orbital bombardment systems. These advancements present significant challenges to our existing missile warning architectures. Hypersonic weapons, with their speed, maneuverability and unpredictable flight paths, are particularly concerning.

They compress decision timelines and challenge our ability to detect and track threats effectively. Moreover, the integration of these new technologies with more traditional ballistic and cruise missile. Cruise Missiles creates a layered threat that demands a comprehensive and adaptable response. Our missile warning systems must evolve to address this complex, multi domain challenge, given this evolving threat landscape, the advancement of missile warning capabilities becomes increasingly crucial for national security. So today, we are joined by an esteemed panel of industry experts to discuss how industry is innovating to meet these challenges. First, we have Jeff Schrader, Vice President strategy and business development from Lockheed Martin Space. Welcome Jeff.

Jeff Schrader, Vice President, Strategy & Business Development, Lockheed Martin Space:

Thank you.

Panel Moderator: Jennifer Reeves:

Next, we are joined by Rob Mitrevski, Vice President and General Manager spectral solutions at L3Harris Technologies. Thanks for being here, Rob.

Rob Mitrevski, Vice President & General Manager, Space Systems, Spectral Solutions, L3Harris:

Thank you.

Panel Moderator: Jennifer Reeves:

And finally, we are glad to welcome Len Orlando, Senior Business Development executive from Ansys. Welcome, Len.

P. Len Orlando III, Senior Business Development Executive, Ansys:

Thank you.

Panel Moderator: Jennifer Reeves:

Okay, so given how much we have to dig into, I am going to jump straight into questions. Okay, so in a data rich battlefield, the challenge often lies not in collecting information, but in synthesizing it effectively in today’s complex threat environment, disparate distributed sensors can lead to gaps in coverage and delayed responses. So how are your companies approaching sensor fusion and together to create a common operating picture for warfighters? And Jeff, you’re right to my left, my friend, we’re going to start with you.

Jeff Schrader:

All right. Thanks. Thanks so much, Jen, and really appreciate being on the panel at Lockheed Space. We look at; we look at the entire view of this in four main areas. I would say advanced algorithms is important, I would say enhanced data fabrics, AIML, because who doesn’t want more AIML across the board? And then open architectures, and that’s probably the one that is likely the one we’re being pushed on the most. There’s a lot out there on, you know, AIML that we’re doing, but, but open architectures to be able to actually pull in multiple sensors and phenomenologies for this threat is really where we’re, where we’re hearing a lot from our customers, and therefore we’re working a lot in our 21st century security models to get after open architectures at Speed, to bring in not just Lockheed or are competitive mates and team partners, but also commercial industry technologies to be able to actually operate within our within our suites of programs. As an example, it’s also not just space. It’s an it’s a hybrid sensor fusion, type of type of environment that we need. And so, when you think about things like the F-35 sensors on the F-35 and sensors to be able to pass things to actually do something about the missile, the missile threats that we have, things like Thad, being able to take, to take data, and be able to actually engage in intercept and both into atmospheric and EXO atmospheric. That’s one thing that we’re doing. And so to your point, I think it’s an it’s a multiple domain, a sensor fusion problem that we’ve actually got to look to space has a ton of it, but we also need to look at that, at the other domains, really, to get after that common, single battle space, to get the right data at the right speeds, with enough precision to understand how to pass, how to pass information through, through the network, Lockheed Space, one of the things we’re doing, you know, funding Express two is an autonomous operating tech demo that was self-funded to be able to actually bring in RF. And so, combining that phenomenology with IR and things. Along those lines, is what we’re doing. And so, we’re proud to we’re proud to actually have that in the wild now, seeing how that could potentially fuse with operational programs or other demos to see how the sensing in the fusion works.

Panel Moderator: Jennifer Reeves:

Super that’s great. Okay, Rob, let’s talk L3Harris.

Rob Mitrevski:

Hi everyone. Thanks for having me. Really appreciate being here on behalf of L3Harris, our answer is pretty simple at L3Harris. We purposefully, for the missile defense mission, have designed common architecture across our payload suite, regardless of whether it’s warning or tracking or fire control. That common architecture has common algorithms, common processing.

Then our customer makes it easy for us, right? The customer says, here’s a standard message format that you have to adhere to, which makes it easy for everyone to talk to each other. That standard message format is then able to go across existing comms links, and get down to the right people, warfighters, et cetera.

Panel Moderator: Jennifer Reeves:

That’s great, awesome. And now to Len.

P. Len Orlando III:

Well, thank you for having me on the panel. I really appreciate being here with the other distinguished panelists.

The first question I actually think of when Ansys is on a panel like this. This is why is Ansys here. And Ansys is a multi-physics company that’s rooted in science, technology, engineering, math. So, we bring a lot of high fidelity, high quality, synthetic data to these types of mission sets. The second piece of Ansys is the federal aerospace and defense component of which we have trusted relationships with many our defense and intelligence branches, so we can work across classification levels to produce that synthetic data. And then the third example really is our ability to work closely with our customers, specifically the Space Force and the Guardians, where we’re building that common operating picture when they go to train in boot camps Wargaming scenarios, using our systems toolkit, or in their mission planning and in the actual mission execution, and then data integration at the back end. And we’re doing that using that high fidelity signatures of infrared, optical and electromagnetic domains, such that they can do that using the high-fidelity data in near real time and evaluate those results so they’re able to practice like they play.

Panel Moderator: Jennifer Reeves:

That sounds great. That sounds great. Okay, so the Space Development Agency has been pushing for a proliferated low Earth orbit constellation for missile tracking as of January, SDA has awarded L3Harris and Lockheed contracts to start producing satellites for its tranche two tracking layer. So, What advantages does this Leo based approach offer over traditional geo based early warning systems when it comes both to sensing and to resilience? Jeff, why don’t we start with you?

Jeff Schrader:

Yeah, great question. And thanks to Space Development Agency for allowing us to be part of the architecture getting after what I would what I would consider a very unique way and a more resilient way to look at, look at missile warning, missile tracking.

There’s pros and cons at each orbit. I think most folks know that, but there are pros and cons to each of those. What Leo provides is, as I would say, I give them grades, if I will, but I would give them an A and revisit rate, so being able to actually be on station and revisit, and they’d get an A on resolution, right? Those are two of their, two of their bigger their bigger things. And when, when you look at the Leo element, those two pieces are really, really two of the main pieces, but also the resilience and quantity that you get with those is another, is another really good thing to have in Leo.

That said, they’ve got to work within the architectures of both what we’re looking at within medium Earth orbit, with programs like missile track, custody, as well as well as in geosynchronous orbit with, with next gen, next gen geo we’ll get into it, I know, in a bit, but that’s really what, what the good takeaway is between what Leo offers is resolution, revisit, rate. Those are the two main elements.

Panel Moderator: Jennifer Reeves:

Okay, super, So Rob, how do you how do you guys see that at all three errors.

Rob Mitrevski:

Well, we like Leo. We’re the only prime that has won all the tranches so far with Space Development Agency on tracking. So, we’ve watched the evolution of this concept, and look GEOS got its advantage and persistence with few.

Or assets certainly, Leo has its advantages in closeness viewing angle, which yields sensitivity and sensitivity for dim objects like hypersonic vehicles are very important in the scheme of things.

Jeff brought up the quantities, right? So, what happens in the Leo environment is you drive a productionization approach. You’re in a low radiation environment. So, you can drive commercialization in, you can drive affordability in, which then lets you create a replenishment mindset, reconstitution mindset in terms of resiliency, and I think that’s where you’ll see the advantages in numbers.

Panel Moderator: Jennifer Reeves:

So, that’s great still, though, I think the Space Force is still interested in having this a warning at both mio and GEO. So why do you think this is and what advantages are there to having this hybrid architect, architecture approach. So, Rob, why don’t you keep going? Tell me what you think about all three regimes.

Rob Mitrevski:

I like to keep going ask my friends. Look, I think multi layer architecture is the right thing to do. If you look at the resiliency calculations in some of the areas where we’re concerned about one or another layer faltering, you’ll know that Emil and Leo layer together, working together in concert, is the right approach to this mission, particularly when there’s a bit of overlap within the two missions, and one can take the reins from the other as necessary.

I do think based on the evolving threat, the imminent threat, the continuing to advance threat, there’s a lot of room for us to have this capability to double down on protecting our nation.

Panel Moderator: Jennifer Reeves:

Super. And so Jeff, your thoughts?

Jeff Schrader:

Yeah, Rob, I agree with you. I think there’s a there’s a couple main things I see. I see a lot of military members in the room. So if I were to say CR, you probably think continuing resolution.

I actually bucketized the hybrid architecture of opir missile warning and a similar thing. I use CR squared, so that stands for coverage resolution and then revisit. Okay, so those three things, and I think with the with the hybrid architecture, what you get with both Geo, Mio and Leo, is all three of those having A’s. And so, what, what that puts on our adversaries, what are puts on our threats, IS, and IS a more costly way to take out one of those, one of those areas, you can’t just target one satellite. You can’t just target one orbital, one orbital regime. Okay, so that’s, that’s one thing. The other things that you get with a geo based, geo-based scenario like ngG, is, is effectively the consistent stare over an over an area of responsibility. So, you know, with fidelity, what is going on from pre boost to post boost? Once, once you actually, once, you actually integrate that with Leo and Mio. So, I think those are the main takeaways.

Panel Moderator: Jennifer Reeves:

I think that’s great. Okay, so let’s, let’s talk a bit about, a bit about a challenge, and that is, traditional ballistic missile warning systems are increasingly challenged by new hypersonic weapons that can maneuver at extreme speeds. This is really changing the paradigm for how we think about our missile defense architecture, what innovations are being developed to effectively detect and track these threats. And I think we’re going to ask each of you, and why don’t we start with Len at Ansys to talk about what you guys are thinking?

P. Len Orlando III:

Sure, no, thank you. So, the way I envision this is really being an all-domain problem, right? Ballistic missiles have a very calculated, predictable pattern to the way that they operate, and using the plethora of Leo, Geo, Mio, the space systems to be able to track and detecting tip and Q, I think is very well understood. I think hypersonic provide one. It’s a continuum of advancements, both from what those systems will look like? Do look like? What looks we have on them? And so, there’s huge opportunities for simulation to augment those data collections and provide robust models of what those systems are system capabilities look so that we can evaluate our system development and system integration.

Question. I think there’s opportunities around how we communicate across those system layers, both in the sensing, there’s the modeling of the atmospherics and how that project itself and the sensors that needs to be evaluated. So, what I would love to see is actually more simulation driven into the analysis framework, such that we’re doing this a priori, and enhancing those systems, both in hardware and software. And this is going to be a very challenging threat because of what you mentioned, the high speed, the maneuverability and crossing multiple domains of sensor tracks that we have to coordinate across organizational boundaries. One thing I didn’t mention earlier, which I think is actually applicable here, is we’ve seen many customers establish common infrastructure which actually allows them to move more efficiently and faster in this space, in particular, when they’re flowing down requirements other contractors, they’re doing continuous integration of these sensor platforms through simulation so they’re able to evaluate them and guide their contractor base more effectively than if you’re using milestone based approaches that are pretty consistent today.

So having that common infrastructure is a huge tactical and strategic advantage for these that entities that need to move quick.

Panel Moderator: Jennifer Reeves:

Oh, nice. Okay, super. So, Rob, what are your thoughts?

Rob Mitrevski:

Well, in terms of innovations, I mean, the sensing part is physics, right? It’s infrared. It’s a certain set of channels. It’s a certain sensitivity. The innovation is in portability, commercialization, proliferation on the sensing side. But really the biggest breakthrough in the hypersonic glide vehicle, particularly phases, is the advanced algorithms. Right? The advanced algorithms are everything about tracking an unpowered object that’s just being warmed up by the atmosphere, and in the past, having that on board with the real time capability has been limited by our technology, and our current technology now allows it. It allows it in a great way. It’s now being shown on orbit with some of our assets, and I think that that that is exactly what we need to keep pushing from our innovation standpoint, advanced processing to be able to take on more and more advanced threats and then further algorithm development that can be demonstrated on orbit, as we have,

Panel Moderator: Jennifer Reeves:

Oh, that’s great. Okay, so from Lockheed, we’d like to hear from you.

Jeff Schrader:

Jen, yeah, yeah, quickly on this piece. This is, if something doesn’t get you up in the morning, like, like reading that you could hear from a bunch of industry folks on missile warning talking about hypersonic should that? Should get you up? The enemy gets a vote, and they are, they are expressing that vote with what they’re doing on their hypersonic glide vehicles and putting us in an arena where we need to get after that in a unique way. I think you; I think you said it best. I think this is a multi-domain challenge that we’ve got to look at. We’ve got to look at things from, from the initial, like I said, Boost Post boost, what it’s doing. Being able to track with the sensors in a multi phenomenology way will be, will be important to us. Luckily, you know, I get to sit at Lockheed Martin, which I think is a blessing, to be able to see the space side of what we’re doing on this hypersonic missile tracking, missile warning, missile defense side, but also I do get to see what we’re doing within the other domains, particularly within the air domain and others, both with some of our other business areas. So hypersonics should get you excited. Hypersonics should see if it should allow you to really question how much budget is going to that threat. And I think it’s, it’s something that I’m, I’m happy to get up and go to work and think about and help, help secure, with my partners, and with our, within our company. So, I think the last thing on hypersonics is we talked about the hybrid architecture. And I think there’s a hybrid architecture and a cross-domain architecture that needs that we all need to stitch together. Infrastructure is one piece. Technology is one piece, also our mission, and CONOPS on how we go about protecting that as another.

Panel Moderator: Jennifer Reeves:

Yeah, absolutely. And so actually, Len, I want to follow up with you. You had started briefly talking about modeling and sim, and I’d like to learn more about that from what I understand even the baseline physics and aerodynamics of how of hypersonics, as we’re all admitting here, is different from what we were normally dealing with. So how does that change our approach to modeling and sim when we were thinking about both hostile red and friendly blue hypersonic capabilities, right? We’re looking at both.

P. Len Orlando III:

Yeah, no, that you make a great point. The reality is, is that, there’s multiple dimensions in which you can try and solve this problem in modeling and simulation.

You know, if you’re looking at it from a right perspective, you’re trying to model adversarial threats. You’re typically looking through the lens of the sensor application, because you’re trying to build the algorithms and build the ability to detect and track and that’s a different classification of problems than, say, if you’re working on the hypersonic platform, and you’re looking at the plasma or laminate flow that gets generated by the weapon system, and how that might affect or change the weapons platform design or sensor suite it needs.

Comms blackout is a great example of some of the challenges that exist with the development hypersonic weapons. And maybe there’s even a third class, which is the integration and test and evaluation right? These are all major these are all gaps that we’re trying to fill today in terms of our own development of hypersonic weapons, and they provide and present different physics challenges and different engineering challenges that we’re trying to overcome because of the desire and need to have capability in place to Protect the war fighter and have hypersonic deterrence as well as our ballistic backstop, awesome, and

Panel Moderator: Jennifer Reeves:

There’s a lot going on there. There’s no doubt. So, let’s shift gears ever so slightly, Jeff, I have a question for you, and that is that future conflicts may not have the luxury of fixed, hardened sites for missile warning, right? Because, let’s be honest, a bad guy might find targeting a fixed radar very tempting. So what advancements are being made in mobile and rapidly deployable missile warning systems to improve our ground-based sensor resilience?

Jeff Schrader:

Thanks for the question. You know, we’ve looked at missile warning missile defense architectures for very long time, and the mobility aspect has been, has been involved in that since, since I’ve been working in at least and for at least a couple to three decades, we’re fortunate enough to have what we call the sibbers, survivable and durable evolution program that we work with, with our customers and we just did, and we’re really excited to just complete a follow on that was really important to that mobile, mobile piece. So happy to happy to be able to deliver that now, where we’re at is working with not only our customer and the space warfighting Analysis Center on what’s next. So, there’s a bunch of different ways that this could go. You could do another follow on. You could maintain that, or add something, something different, or we could go and go and consult, you know, go and look at what commercial has available. And so, we’re waiting on the swag to look at what that force design looks like. And Lockheed Martin stands ready to address that and keep that part of the part of the architecture as we, as we look to continue to deter the threat.

Panel Moderator: Jennifer Reeves:

Okay, I love it. I love it. My personal experience with s2 e2 as you know, we chatted about that, so I’m very excited to hear as it continues to progress. So, Len, let’s go back, if we could really quick and chat about, you mentioned briefly, simulation and testing. Let’s talk a little bit more about that. The complexity and scale of missile warning systems make comprehensive live testing incredibly difficult. So how are advanced simulation technologies being used to validate and improve system performance?

P. Len Orlando III:

Yeah, so let me start by saying that Mercedes Benz today, if we’re drawing from the commercial sector, has achieved layer three autonomy. So, layer three autonomy means that you can effectively take your hands off the wheel and let the car drive itself for long periods of time. And they’re able to achieve that using simulation data. Now, granted, they’re looking at commercial applications. They’re in. They’re not in a contested environment, the same contestant environment the DoD or defense would operate in. However, it does signal that there is an increased reliance on simulation data to augment real world, right? They’re not going to drive millions of miles of that vehicle in operation, they have to backfill it with simulation and that really attests to the quality of data that can be generated synthetically today to drive those systems and use of them. And we’re seeing that within the Test and Evaluation community as well the increased adoption of simulation data to augment. Real world test because of the complexities of the systems that are being designed and have to be fielded for all Domain systems, we’re crossing multiple dimensions. We’re seeing the use of synthetic data to augment what would be basically augment the good looks that we have in our portfolio that give comprehensiveness to those looks. The challenge is, is that you get a look from a certain perspective, but you need all the perspectives, because you may not see that vehicle that again, that adversarial element again, and so you need to backfill it somehow. And synthetic data is a great, great way to do that. And so, then it becomes a modeling challenge, like, how do we model this? What are the right fidelities of the model? What is the processing capability necessary to generate that model and how much of it represents that real world system. And then that also leads us into right the sensing algorithms, the artificial intelligence, the ability to use machine learning and other layers of software to help us predict, identify and track. So Ansys is actively working in that area with our defense customers, to backfill with synthetic data to help augment real world.

Panel Moderator: Jennifer Reeves:

I mean, that’s great. And you actually brought up the magic language that I that I know everyone is always interested in, and that is AI and machine learning. So, I’m going to ask you to continue on with this question, and that is the sheer volume of data that comes from various sensors, as well as perhaps, you know, synthetic data that we’re using and testing can overwhelm human operators, of course, and lead to some decision paralysis. So, in what ways is, are you using AI and machine learning to incorporate into missile warning systems to improve threat detection and reduce false alarms? That’s the question.

P. Len Orlando III:

Yeah. So, because of our broad depth of portfolio of physics solvers and our regions the commercial space, we’re seeing drivers already in these other domains that the Defense Department can draw against and use to accelerate adoption and use of artificial intelligence. Really it ends up being the ability to reduce these complex data sets, both in synthetically generated simulation, real world test. And the combination of those two things to produce to high quality data, and we’re applying artificial intelligence and machine learning to do that for these types of operations and operators. And the value add is, is you get significant speed up, reducing of that complexity of those models into things that can be run in the orders of 10s of seconds versus days or weeks that you might need for a high performance or a long simulation. The other piece of that is there’s a lot of manipulation, meaning you can stretch that model quite significantly and still maintain that high degree of accuracy. And that’s where I think there’s opportunities to address that simulation space into and transition to these reduced order models for the operator.

Rob Mitrevski:

That’s great. Really, great. So Rob from L3Harris, what are your thoughts?

Rob Mitrevski:

Sure, the good news is the missile defense mission isn’t an Intel mission or a weather mission, where you have to dump every last bit of data to the ground as part of the mission. So, the customer and the nature of the mission make it easy on us. In that regard, in that the algorithms on board, the processing on board, has to do its job, and it has to do its job to detect, to track, to identify and to minimize those false detects. And the way we do that is we also have an in-house simulation suite that has flight algorithms on it. It has flight hardware on it, and we continually test and tailor and tweak those algorithms and advance them as part of our just ongoing campaign for this mission. So, you know, those algorithms have autonomy built in. They have machine learning built in. They have an ability to understand false tracks and eliminate them. They have an ability to send that message that is necessary on a position in a velocity that’s really what we care about in missile defense.

Panel Moderator: Jennifer Reeves:

That’s great. Okay, Jeff?

Jeff Schrader:

Yeah, there’s a couple things on the SDA program tracking Tranche 2 that you talked about, we were running something called Smart set. It’s effectively just like your phone picking an application that you didn’t produce, but actually being able to run the third-party software on board. So as that’s flying around once it’s fielded, you can actually upload perhaps some AI and machine learning algorithms on that. As an example. We’re developing AI ml algorithms for next generation geo that we could ultimately port over to the SDA program or in a missile track custody format, to actually approach specifically dem targets. That’s one area that we’re looking at, specifically on how to utilize AIML to actually look at and track dem targets, to be able to provide that back to our warfighters. I would also say that from an AI ml perspective, one thing that was great walking in Purdue had a Purdue University had a had a commercial up. We’re working with Purdue University on, on some of their on some of their AIML algorithms to actually pull into our missile warning Architecture Framework and software tools. Which is great Colorado. University Colorado, at Boulder, is also another, another university that we’re working with to see what’s out there. So, it doesn’t have to always be Lockheed Martin stuff to pull in, to pull in good, good algorithms. So those are just a couple examples and a couple programs we’re moving we’re moving forward with to bring AIML to this mission space, which is very much needed, specifically for tracking them, targets, right?

Panel Moderator: Jennifer Reeves:

Absolutely, so much data. So, this has been a wonderful conversation, and we’re wrapping up. And so, I want to give our panelists here who have this great experience coming from great technology, the opportunity to leave the audience with something. And so, Len, let’s start with you, and what would you like this audience to walk away with?

P. Len Orlando III:

So, I think my core nugget, I think I’ll leave the audience with, is to think of simulation as the fourth offset. As we’re considering what is the next evolution of the Offset Strategy? I think simulation plays a key role in that. And what we’re hearing today on this panel, and I’ve heard through others is simulation adds a lot of value to those mission sets. The piece I’ll add on to that is, if I was in the commercial land, which I work a lot with, commercial they come to the realization that they need as much simulation capability as they can have, that the limiter in the system development isn’t simulation. It’s the people that drive simulation. So as much as you can automate, reproduce and generate using simulation, you can the better off you are.

Panel Moderator: Jennifer Reeves:

That’s awesome. Thank you so much, and we’ll pass it to rob thoughts for this great audience as they head.

Rob Mitrevski:

Sure. Thank you again for having me and us in this session. I would say, look at L3Harris, where we’ve been a proud disrupter. I think in this space, the hypersonic mission was new when we first started thinking about it, and we’ve been proud to now participate with Missile Defense Agency, Space Development Agency, Space Force, SSC, in solving these hard problems. The problems aren’t going to get any easier, so it’s incumbent on us in industry to work with our government customer and together to solve the problem for the nation. I think it’s been an interesting collaboration, I would say within industry, one that I haven’t often seen before, which is great, because I do think there’s a greater good there. While we serve our own corporate needs. We’re also serving the nation in a mission of need, and I think that’s a great thing for us. So, you know more to come.

Panel Moderator: Jennifer Reeves:

Yeah, I’m with you. I may be biased, but miss a warning is where it’s at. So Jeff?

Jeff Schrader:

Yeah, thanks. And Rob, I appreciate you saying that about partnerships holistically throughout this mission. You know, we talk about partnerships in industry, we talk about partnerships in government. We’re really proud to be a provider of capability across all layers. What I would leave you with is, you know, I’ll probably date myself a little bit, but you know, Goldilocks and the Three Bears, when she picked the different size chairs. This is a mission where you don’t get just, just get one chair. This is something where she needs all the chairs, and she needs the chairs to maybe have a different flag behind them. So, I would actually say this is an international type of need as well. So, when we look at our partnerships across both industry, government and international, that’s the call to arms that we need within I would say missile warning, missile tracking, missile defense, holistically. And it is not just a space thing, it is a multi-domain element. So, Goldilocks doesn’t get one chair. She gets three.

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