The electromagnetic spectrum has been a part of the battlefield since WWII. Radar technology was developed by British scientists and engineers in the 1930s, which played a vital role in the Allied victory. More recently, the EM spectrum has had an even more significant and developing role in the last 25 years, and will most likely continue to evolve and increase with the implementation of drone technology. The U.S. has been right there fighting a war on terror, and so far, dominating that EM spectrum, but what happens as our adversaries change, and innovate beyond the U.S.?
Innovating in Real Time
Scott Aken, the innovative CEO of Axellio, joins us to share his expertise on the critical role of the electromagnetic spectrum in modern warfare. As we look back on the evolution of electronic warfare, Scott explains how the focus has shifted, especially in the past two decades due to the war on terror. We dive into the necessity of sensing, ingesting, storing, and analyzing data from the electromagnetic spectrum to counter fast-moving threats like drones. Highlighting the technological advancements in AI, Scott illustrates how these innovations are enhancing our ability to manage and address these challenges efficiently.
Scott opened the discussion with intensity, “[during the War on Terrorism] we owned both the sky and the electromagnetic spectrum. So our adversaries were not the near-peer threats we have today. So we didn’t innovate. You know, we used to own electronic warfare and that kind of started to shift by just lack of funding, lack of innovation. There were other things that we needed to do to fight the war on terror. So, you know, taking years off of innovation gets us to where our near-peer threats didn’t pump the brakes, they kept their foot on the gas and they have caught up and in some cases likely surpassed us, and some of those technologies on being able to use and abuse the electromagnetic spectrum.”
Scott, who has been the CEO for just over two years now, excitedly shared his experiences in the EM field, “the bulk of what I saw was really focused on the cellular right because that’s how we were tracking the adversary is cellular phones. So we got really, really good at that. But guess what? The electromagnetic spectrum is enormous. The cellular bands are relatively small, and so we had good innovation on that end. The equipment you got was stuff that needed to be carried in a Humvee, and evolved to stuff that could be carried in a backpack, the stuff that could be held in your hand. You know that’s innovation. You know they went the role of minimizing because the technology got better and faster and smaller.”
When is innovation not innovative?
Innovation isn’t always what it seems, according to Scott. Yes, the technology was getting smaller and easier to carry around on the battlefield, but what about what was going on in the background? How was the technology improving, widening across the EM spectrum, and capturing and collecting more of that data? Was it? How do you collect, capture, and retain the entire spectrum?
“What most people don’t understand is when you’re looking at large chunks of the electromagnetic spectrum, it is hundreds of gigabits a second and in some cases, if you’re really looking wide, it can be terabits per second of data,” Scott continued. “And you’re trying to do this at the edge, right? That makes things hard in terms of being able to have processing power and analytical capabilities that can look at that much data that fast. Let’s say, I’ve got a fast-moving drone that’s coming into my command and control center. I need to be able to identify it, see it, possibly a frequency on it, and then put up a countermeasure to stop that before it hits my command and control, all in potentially minutes. That’s a different kind of problem than hunting someone down who’s holding a conversation on a cell phone.”
Fundamentals of em
According to Scott, this problem revolves around three fundamentals: you’ve got to sense the technology, you have to be able to ingest all of the data, and you have to be able to store all of that data quickly.
“It’s kind of three things first, you’ve got to sense it, so you’ve got to have sensors, that can handle. You know, either you’re chunking it up in certain chunks of spectrum and have enough sensors to pull it all together. ”
“So it’s the sensing, then it’s the ingestion of all that data, the storage of all that data, and then the analytical capabilities to figure out what’s good, what’s bad, what’s indifferent of that data,” Scott explained.
It’s the sensing of the data, it’s the ingestion of that data, the storage of that data, and then the analytical capabilities of that, which then ultimately leads to an outcome of now, what do we do once we’ve seen that? Do we put up a countermeasure against it? Do we jam it? Do we shoot it? You’ve got the options and dependent upon what you’re seeing in your analysis, now you’ve got to determine your outcome. This is where the innovation comes in. How do we process all of that stored data, and still have time to react to a real-world situation? According to Scott, the answer is coming.
“The innovation is happening, but you know, when you look at the electromagnetic spectrum in general, sensing something that’s in the kilohertz range and sensing something that’s in the gigahertz range, you know is a very different thing,” Scott continues to break it down. “Usually one sensor isn’t going to work across that entire range of frequencies. There are different antennas, different radios and you’ve got to understand where you’re looking at for, what threat you have in that particular frequency range, and then put out the appropriate sensors and the appropriate collectors to be able to grab that off or out of the air, to be able to make sense. But I’ve seen, even in the last couple of years, some real advancements that are happening within the community to quickly catch up, which doesn’t surprise me.”
Near Peer is closer than they appear
This is not an easy thing to accomplish, especially without innovation pushing technology to handle the amounts of data that need to be collected, stored, and analyzed.
“The idea of looking at the entire electromagnetic spectrum is a daunting one and it’s a problem that we’re certainly seeing across the industry,” continued Scott. “On how you go about doing that, at least at Axellio, we definitely have done some innovation on our side that will significantly help that issue. By letting people know that there are solutions out there that can help in doing a large collection of data, it can help others who don’t understand that that innovation is out there. Axellio is a small company and I promise I won’t do a big pitch here, but we’re a small company and our marketing is pretty small. We’re one of these companies where they talk about within DoD, where the innovation comes from these small companies. To help people understand that we have some solutions that can offer a step function in getting them to look at larger and larger and larger chunks of data, which then will help them be able to analyze larger and larger and larger chunks of data within the electromagnetic spectrum.”
Scott is no amateur when it comes to innovation, that is clear. He understands that this is a problem that isn’t going to be solved overnight; it is going to take a concerted effort to solve this problem.
“Not one company is going to solve this,” Scott stated. “You know, I just went through five different pieces of things that have to happen to make this happen. No one is doing all of them. We have to work together as an industry to be able to put this stuff together and we think we have one of those pieces and trying to get the word out to let folks know that, hey, we can help. So, when I took over as CEO at Axellio a couple of years ago, the technology we had, we were primarily focusing on network packets, so focusing really on the cybersecurity market. My previous nine years were spent at a company that made a lot of RF acquisition products and in my head I knew that with the systems that I used to build, just recording even a few seconds of electromagnetic spectrum would fill up our hard drive. And so when I was talking to my CTO and I said, hey, this is really great on the network packet side, what other data can we store? And he’s like any time series data, the light bulb immediately went off in my head and I said, oh, we’ve got to go after RF. There is a massive need for this in the marketplace, and so that’s exactly what we’ve done. We’ve crafted a solution that is targeting, specifically allowing the folks with lots of sensors out there to hoover as much data as they can possibly get and pass that to us, because, we’ll never slow them down.”
As Scott continues to explain what technology piece Axellio has in this game, he gets more excited, “You know, we can ingest and store faster than anything on the planet, and I’m pretty confident that I can say that. I haven’t seen everything, but I’m pretty confident I can say that. We are allowing them to make sure they’re getting the maximum usage out of the sensors they have in the field. If you’re up on a collection mission, you never have to worry about saying, hey, I’m going to run out of storage. I can’t store data fast enough. I can’t look at my widest bandwidth. We can help with all those things. So that’s what we’re trying to do. I saw the need from living in the industry for a while, and then we’re trying to make sure that we can help those folks in between the collection piece, the sensors that are in the satellites, on the planes, in the ships, on the Humvees, and the folks that are doing the analysis. We can help bridge that gap and make sure that they’re both better by putting us in the middle because we can take all the data from the sensors and store it at speeds that would boggle your mind and then pass it to multiple analytic tools so it doesn’t have to just be one and they can grab the same data at the same time. We’ve decoupled the collection from the distribution because we can store it on disk. So, our fundamental innovation is we figured out how to simultaneously write and read to disk. I would say that Axellio has innovated the storage industry to allow for extremely high-speed, multi-petabyte simultaneous read and write performance, to capture, and distribute any time series data, but in this case, RF. That innovation alone will allow us to redefine how we do our collection and analysis at scale.”
What is the goal for EM and the Spectrum?
But what is the ultimate goal? Is it to analyze the data in real time? Is it to collect and store the data? The answer is all of the above.
“I think ultimately our goal is to work with as many of those sensor companies and as many of those analytic companies too,” Scott stated. “The military can’t scrap all their sensors and build brand new sensors. We’ve got to work with what we have as new ones are developed. The capabilities will continue to grow, but we’ve got to make sure that with the sensors that are out there and the analytic tools that are out there, we can get the best performance possible for them. So our job is to make sure A) that we integrate with a lot of those folks and then we’re going to do some deep integrations with some of them to allow for really getting the AI in there. And I’ll say it’s more machine learning. I know AI/ML confuses a lot of people. Machine learning is a subset of AI Machine learning to really look at the waveforms themselves, to be able to not have to store as much data. So passing, you know, through our database, all those waveforms, to an AI platform, allowing them to do real-time analysis on it, figuring out what’s good, what’s bad, what’s indifferent, and then if for the stuff they say, hey, this is not a problem, let it go right, and you can then even increase your storage volume more because you can let some of that go. I think deeper integrations with AI and ML is our next big move, and we’ve got some pretty good innovations already working on that side from the Axellio Corporation.”
It was interesting to speak with Scott and have him share the inspiring journey of a small tech company that is achieving remarkable success by innovating in data storage and analysis. To learn about Axellio initially focusing on cybersecurity, and then the company pivoting to address the need for rapid ingestion and storage of RF data, developing a unique solution that supports extreme high-speed, multi-petabyte performance was an educational experience, to say the least.
This technology has transformed and will continue to push and evolve the capabilities of sensor companies, enabling continuous real-time data streaming and enhanced signal detection, revolutionizing the capture and analysis of electromagnetic spectrum data. It will be a truly exciting ride to see where Scott and his team continue to push the technology and EM practices and where innovation will continue to inspire them to go.
