Video: Vigilant Aerospace on Scaling Integrated Airspace at AIAA 2025

I’m Kraettli Epperson, I’m the CEO and co-founder of vigilant Aerospace. We develop detect-and-avoid Aerospace Management Systems, and this is a presentation that was co-authored with Dr Jamey Jacobs, who’s the executive director of the Oklahoma Aerospace Institute for research and education at Oklahoma State University, and I’m going to be going through a variety of projects. This is a presentation only- no paper. So, a little bit of a briefing from industry is the format of this presentation. Integration of UAS and AAM platforms into the national airspace system is incredibly important right now, and they’re really important technical challenges and gaps, especially around detect and avoid airspace management. There are major regulatory challenges, and there are significant economic Opportunities that can be captured, including a lot of national and international competition taking place.

So, our projects are really focused on overcoming those key technical challenges, so these partners focused on developing scalable, reliable, efficient integration methods, particularly around safety. And we really focused on radar integration, advanced software development, and then did extensive field testing and validation, which will be the bulk of what I’ll talk about. It has implications for safe UAS operations integration, airspace operations, and then development of uncrewed traffic management systems and scalable advanced air mobility. So, that’s our major focus. And these are some of our partners, and I’ll talk about them throughout, primarily focusing on OSU. We’re based in Oklahoma City, OSU is in Stillwater, and OAIR has offices in both Stillwater and in Oklahoma City.

I’m going to go over a little bit of background, talk about the objectives and methodology that we used in these projects to develop this new technology. Talk about some of the key Innovations and findings and then talk a little bit about the implications for the industry, so some context for this. AAM and UAS are poised to really revolutionize the way we use the airspace and are already representing the most takeoffs and landings in the United States, and that’s only likely to grow. But it really requires advanced safety systems to make this possible, and to allow the level of automation that’s really required for the industry to function in traditional air. Traditional air traffic management is designed for predictable, centralized control of the airspace. Making it very inefficient for both UAS and AEM, which are highly decentralized, more point-to-point flights, and involve a high degree of autonomy.

And yet, we are seeing increasing number of aircraft, particularly UAS and drones of various kinds entering the airspace. These projects focus on overcoming the key technical gaps, particularly around safety. Utilizing new sensors, Advanced software development, and then utilizing technical standards, the picture on the right here. This diagram is from the ASTM f-3438.

The two standards are used for detect and avoid systems, and then we also utilize RTCA standards also. The goal is really to enhance safety of these systems. So Vigilant Aerospace is the company that I represent. This is company that develops Advanced DAA systems based on a couple of NASA patents. We worked closely With NASA Armstrong on the initial research and published multiple papers with them, and then we have evolved that into a distributed cloud-based airspace management system with built-in Baseline detect and avoid that is standards compliant, depending on what your Hardware is. There is a user interface picture there, and I’ll provide some more of those. We publish papers about the Icona, which is the NASA, the NASA, MQ-9 Reaper, and the global Hawk, which is pictured there also in NASA aircraft. And then we’ve done onboard systems and ground-based systems, so I’ll talk about both of those. So, OAIR at Oklahoma State University is a central Hub for UAS research in the United States, and especially for Oklahoma. They have a wide range of programs and executive director Jamey Jacobs has been a great partner with our company in the development of this technology. They provide a lot of Outreach, research, and education, and especially they have the uncrewed aircraft flight station in central Oklahoma, which is widely used by a variety of federal programs and local programs and partners like us, who use it for a lot of our testing and it’ll be featured in some of the projects that I’ll highlight here.

We Focused on the series of projects I’m going to talk about on enhanced surveillance capabilities, which is really key to enabling UAS and AAM autonomous functionality. There’s really no way to scale or build this industry without autonomy, and to have autonomy, you must have autonomous safety. So you have to detect, track, warn and avoid. Those are key functions of our software and really key technical capabilities that have to be built into autonomous systems and are going to be critical for AAM. We also Focus on very versatile deployment models and scenarios, so you’ll see in our projects both ground-based systems, large radars, small radars, and onboard systems moving rapidly towards hybrid systems where the technology and the software is in the cloud. The sensing is distributed and is available to all kinds of users and all types of missions at all times.

Next Generation 3D digital Radars in these projects. I’m going to show you some pictures of these, and I’ll go over the specific Radars. These Radars allow us to track multiple Targets in the air. They are mobile. They have their own servers on board. They’re transmitting usually up to our servers in the cloud, and this allows us to begin to build a highly accurate picture of the airspace around where the operations are taking place. They have available power generators on board for backup.

These capabilities are able to track air traffic multiple kilometers away from the central location with the ground-based Radars and then the onboard Radars. I’ll show you some pictures of as well, but so this is one of our field tests. This is not too far from an airport where we can get some air traffic, and this is a system that is networked into a larger system of other other radars and surveillance elsewhere. So, some of the radars that we’re using here would be the DeTect Harrier, which is a brand new.

That’s the older radar it has about a 33 kilometer range. And is very widely used, particularly for light control systems at small airports, wind farms, Other places like that. The brand-new radar is the dtec 7360, which is a 3D radar so. A radar that can give you altitude give you a very high degree of accuracy of the exact location of incoming air traffic, and these are critical to providing air traffic surveillance for safety, and then flight Horizon is the software system that pulls all that data in and turns it into a display that I have showed you some pictures of, and we’ll show you a few more.

This is based on those two NASA patents that we license and then developed our commercial product, which is now a dual use civilian military product. So autonomous EA and the ability of software and systems to interpret traffic data to do the full detect and avoid process automatically is really important for the future of the industry. This is a picture on the right of what the software looks like. When it’s operating, you’ll have your own ship your your drone or UAS aircraft. In the middle, there you’ll have a well clear safety distance that’s based on the regulator’s requirements and the technical standards, and then you’ll have detection of other aircraft using a variety of means radar transponder.

Specific warning. This is based on acas X, which is the FAA’s resolution advisory process to do Collision avoidance, and so that is embedded in the software. We also work with a variety of ground control stations and autopilots to get the information both from the aircraft and back to the pilot or to the autopilot. So, this uses NASA’s Daedalus 2 algorithms to be compatible with a Cass X and with RTCA do365c, which is the standard for DAA systems for larger aircraft. It’s also designed to be compatible with the ASTM f3442 standard, and I serve on that working group, and it’s also designed to comply with some other standards as well. In terms of user interface to provide the remote pilot with a consistent experience.

Moving on to our third objective and some of the work that we’ve done with these projects was to build very versatile configurations. So this is a picture of one of these Radars that’s integrated at a drone port in Tulsa, Oklahoma. This is an active drone port that has a variety of projects ongoing, and we’re able to observe that airspace pull in data and then also network with other Radars that are a little further away to begin to create corridors. This is particularly for something called the Skyway range corridor program.

We also have onboard systems, I’ll show you some diagrams very quickly of those and then cloud-based architecture to collect and do the correlation on all the tracks and then get the information out to distributed airspace managers and remote Pilots. So, for a ground-based system, this is a diagram that represents how those are integrated in our system. Our flight Horizon Tempo software is the cloud-based version of this software. We’ll pull in information from the autopilot from any ground control station that’s connected to the autopilot to a ground-based radar and then any transponders on Cooperative aircraft with the radar, providing coverage for non-cooperative. And then we’ll send that back out to the end user remote pilot or airspace manager. For this case its actually a NASA airspace manager thats using our system for supersonic flights off the coast of Florida, using it to track those aircraft and keep them safe.

This is a diagram representing an onboard configuration. This was actually developed as part of our dual use Flight Horizon pilot product with support from AFRL in the US Air Force. So, we use one or two onboard Radars, much smaller Radars, these are Echodyne Echoflights, integration to the autopilot, and the ability to put all of that software on board and then provide information out either to Ground Control stations or to our own software on the ground. So, here’s some actual equipment that’s used in these types of projects. A couple of those Radars, so you can see what they look like. They’re about 1.8 pounds each. They network into the the onboard flight computer and to the autopilot ADSB receiver and GPS so that the computer can be fully aware of the location of the aircraft and all the surrounding cooperative and non-cooperative aircraft. So, this is, uh, this is. We’re really excited about this. I mean, this is, is the edge of the industry Right now, obviously with those two Radars. It’s really intended for larger aircraft. After we had designed these systems, we began doing field testing. We’ve done a wide variety of field tests with these systems, and so I’ll go through some of those.

This was part of a project with OSU at the unmanned aircraft flight station, where we were using first one radar and then two Radars to do actual monitoring of aircraft tracking with multiple Radars integrated to demonstrate that we could do that to do the correlation to do deduplication to use multiple channels on the Radars to be sure that they were not broadcasting to each other and then testing under real world circumstances where we had aircraft flying around. I’ll talk a little bit more about that, but we had Cessna’s that were flying in to test these radars, and then we had drones that were used both as targets and as ownership.

Then we had drones that were used both as targets and as ownship. So, here are some of those aircraft. This was supported by both OSU and afrl, a couple of Radars up in the air. I’m testing all of those integration systems, a little bit of picture of the people actually using the system. This is a project field test that we did for NOAA, where we were tracking drones as part of a weather collection program that they’re working on. So, using those Radars in the field and actually tracking small UAS, potentially at longer ranges, this was all at very short range, and this is us using cessna’s to perform what’s called a wagon wheel flight test around a fixed ground-based radar. This is to establish the range of the radar and to provide validation that the radar can see what you say it can see and that it has good tracking over that time period. So the red tracks here are the truth data.

The tracker on the aircraft, and then you have the detections that are occurring, as that aircraft flies around you can actually see where the radar picks it up and where it loses it. We had excellent experience with that dtac 7360 doing this type of testing, and that allows you to begin to calculate risk ratios on the contribution of your safety system, which is critical to being able to fly UAS and get FAA authorizations. We’ve also done testing with systems on board. This was done for the FAA under contract with acuasi, which is the uas test site in Fairbanks, Alaska. This is an onboard system in which we have the radar ADSB receiver own chip integration to autopilot all on that small UAS. This is primarily a prototype. We would typically put it on a larger aircraft with greater payload capabilities, but this aircraft was actually flown multiple miles Beyond visual line of sight along the transalaska pipeline.

We were able to bring all these systems together, and we’ve expanded this since then with the two Radars. I showed you in the prior diagram. And then, finally, in our field testing. Now, we’ve moved on to real world deployment and implementations. This is a picture from a recent project just a few weeks ago, in which we’re rolling out large radars. Both the 3D Radars, the smaller ones, and the large 2D radar with the much longer range to provide surveillance for the Oklahoma Spaceport at Burns flat in which they are flying a variety of developmental. military UAS and advanced Aircraft of all kinds has about 10 000 square kilometers of coverage by the end of the year. With the variety of these Radars which we’re rolling out. It’s all cloud-based software that manages this information, and we’ll be doing ongoing testing and validation for future authorizations through this year and part of next year. So, we have lots of aircraft flying around this system, which we’re really excited about.

So integration of heterogeneous radar models is really important. We have a little bit of that going on. There’s a lot more that can go on, particularly because there are new and smaller Radars emerging, development of hybrid systems with both on board and ground-based tracking integrated into a single system. This is especially important for development of UTM as a universal system that can be used by all types of missions and aircraft, increased autonomy with the onboard system, able to do all of its own Maneuvers. The current system is capable of doing that but its not typically authorized to do that so usually there’s a pilot in the loop.

And then obviously increase the utilization of. Of AI and machine learning, particularly for classifications, strategic deconfliction, and other things. That can be automated. Overall, the implications of this research for the UAS and the AEM industry is really the advancement of multi-radar, integrated, detect, and avoid systems across much larger areas, highly autonomous DAA, so we have that full DAA and compliant avoidance process built in, which can build towards regulatory Compliance, which is critical to getting this stuff into the air and the FAA, allowing you to use it, and ultimately, the military also using it for a variety of missions. So large-scale long-range air traffic management is in reach with systems like this, and ultimately, it supports this Advanced infrastructure where you can build ranges, corridors, other things as a steppingstone into fully autonomous on-board DAA and safety. These are really key building blocks to the future of the industry that we’re really focused on, and we’re really excited, particularly, to be building out these large-scale systems to enable things that are really rare at this point in the United States. Most of these conclusions I’ve already discussed, but the key technical capabilities are around autonomy and having all of these systems talking to each other to solve what’s a really critical problem, without this kind of system, the industry simply cannot Advance. So, this really sits on the critical path these systems are inherently going to be distributed. They’re going to be smart. They’re going to be smart at the edge and all these digital systems, both onboard and ground-based are going to have to be integrated for the system to be scalable. We built with a Cloud-Based infrastructure so that we can distribute all of the data as needed. Do the skilled up computational power needed to deliver all of the DAA. And then this field testing can ultimately lead to adoption of new standards. Use of those standards in field testing and authorizations with the FAA and others. And that’s really what we’re focused on with all of these projects. So OAIR was a major contributor to that, I just want to call that out, and then we are the industry partner on these projects, and you can find more information at the websites provided there at the bottom. Thank you all very much.