Strengthening JADC2 In The Pacific With Line-Of-Sight Communications
Back in the 1990s, when the U.S. military still relied primarily on line-of-sight rather than satellites for C4ISR and other communications, the Office of Naval Research developed and tested a breakthrough approach—a self-organizing mesh network for Navy line-of-sight communications.
With this network, a ship, for example, can send radar data far beyond the horizon, using ships, planes and Navy stations in a series of line-of-sight relays. Algorithms chart the most efficient path from one line-of-sight platform to the next. Data might travel half a dozen or more “hops” before reaching its ultimate destination.
As innovative as the research was, the mesh network was never put into operation—satellite communications were quickly coming on their own in the Navy and the other services, and there was no longer a pressing demand for line-of-sight relays to go beyond the horizon.
There may be a need for such mesh network again. In the event of a conflict in the Pacific, satellite communications could be degraded or denied, undermining the effectiveness of Joint All-Domain Command and Control (JADC2). If that were to happen, the DoD would need to rely on line-of-site networks for sensor, command-and- control, and other data. Unfortunately, current approaches to line-of-sight networks have significant limitations— such networks tend to be inefficient and unstable over long distances.
However, by bringing back the mesh relay network developed by the Navy in the 1990s—and updating it with AI and infrastructure improvements—the DoD can strengthen its ability to maintain JADC2 in a satellite-denied environment.
Current Approaches To Line Of Sight
One of the weaknesses of current line-of-sight networks is that they try to create a global topology, or map, that shows all the connections between various platforms, as well as the most efficient communications routes. Satellite networks can create such global topologies because every platform can “see” the satellites. However, it is much more difficult to line-of-sight networks to create fully comprehensive maps.
Line-of-sight communications must be conducted at relatively low power to avoid giving away the platforms’ locations to adversaries. But lower power means lower bandwidth, or capacity. And when line-of-sight networks try to create a global topology, they often of end up using most of the available bandwidth just maintaining the map. Each time there’s a change in connectivity—with a ship or plane moving into or out of line-of-sight— the routers and algorithms on the network’s platforms have to completely update the global topology. This intensive router-to-router traffic between platforms not only crowds out intelligence information, sometimes there’s not even enough bandwidth for the router traffic itself. This can be a particular issue for U.S. forces in the Pacific, where airborne and seaborn platforms are constantly moving in and out of sight of one another. A global topology is typically not sustainable in a frequently changing line-of-sight environment.
Advantages Of The Mesh Network
Instead of trying to create a global topology, the mesh network developed by the Navy in the 1990s uses an innovative relay system that moves data from one line-of-sight hop at a time.
Here’s how it works: For example, say a UAV needs to send radar data to a number of ships, planes, and bases beyond the horizon in the Pacific. With the mesh network, the UAV and all of the platforms within its line of sight are using their routers and algorithms to communicate with one another. In essence, they’re creating a highly localized network map.
It wouldn’t be practical for the UAV to send its data to all of its line-of-sight neighbors—that would create too much network traffic. Instead, the UAV determines which neighbors have the most line-of-sight connec- tions of their own and sends its data only to them. In the next step, the platforms that get the UAV’s data relay it to their own line-of-sight neighbors that have the most connections. This process is repeated, from one group of line-of-sight platforms to the next, until the UAV’s data reaches its ultimate destinations.
A major advantage of this approach is that data moves throughout the network with the minimum number of platform-to-platform relays. This makes the most efficient use of line-of-sight’s limited bandwidth, freeing up capacity for intelligence data. And because the fewest possible platforms are relaying the data from one hop to the next, it lowers the risk of detection by adversaries. There’s another benefit: Unlike line-of-sight networks that try to create global topologies, the mesh network is self-healing—it seamlessly incorporates constant changes in connectivity.
The latest advances in AI have the ability to make the mesh network far more powerful than Navy researchers envisioned in the 1990s. In particular, AI can help maximize routing and network efficiency, by determining which platforms, and which data transmissions, have the highest priority based on the operational mission and the commander’s intent.
Building A Mature Line-Of-Sight Infrastructure
Mesh networks alone, however, are not enough. In order for them to operate efficiently—even with AI—they need to be part of an infrastructure that is geared toward line-of-sight communications, not just satellites. For example, in recent years sensors have been increasingly designed to stream data through satellite communications. However, it is difficult for lower bandwidth, line-of-sight communications to manage and consume streamed data. Too much data from too many sensors will bog down a line-of-sight network.
This means that sensors will need to operate differently in a satellite degraded or denied environment— instead of streaming oceans of data, they will only be able to send the most relevant bits of information. Here again AI can help, by selecting the most relevant sensor data based on mission, evaluating network conditions, and determining how much data can be sent at a given time.
In addition, sensors will need to be specifically designed to accommodate line-of-sight communications. One example of the way this is being done now: With some small UAVs, the resolution on the cameras is intentionally lower, and the frame rates are intentionally slower, so that the video can be processed more easily through line-of-sight communications.
A line-of-sight infrastructure also calls for changes to the routers and algorithms that communicate with one another to form a mesh network. The DoD now largely relies on commercial, proprietary routers and algorithms that are specifically designed for global topologies. With open operating systems and other open approaches, the DoD can develop routers and algorithms tailored to line-of-sight communications.
U.S. forces in the Pacific may someday need to transition from satellite to line-of-sight communications in order to maintain JADC2. By leveraging the mesh relay network the Navy developed in the 1990s, updating it with the latest AI, and developing a mature line-of-sight communications infrastructure, the DoD can help meet that challenge.
Mike Morgan ([email protected]) is a principal at Booz Allen who leads the firm’s NAVAIR line of business. He has over 20 years of experience supporting NAVAIR programs with a focus on systems development and cybersecurity for unmanned systems and C4ISR solutions.
Steve Tomita ([email protected]) is a principal and director of technology and digital engineering at Booz Allen, where he has been driving innovation and capability delivery to the Navy and DoD for 20 years.
Cliff Warner ([email protected]) is a chief engineer at Booz Allen. He led the research on the mesh rely network for the Office of Naval Research in the 1990s when he was with what is now Naval Information Warfare Center Pacific. He currently develops and analyzes system-of-system architectures for Navy clients.
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Making Digital Engineering For Unmanned Systems More Open
Unmanned maritime systems (UMS) are poised to become a leading-edge capability for the Navy in potentially contested environments in the Western Pacific. As this unfolds, China will likely respond by aggressively introducing new methods and solutions to blunt the UMS’ effectiveness. The Navy will then need to introduce even more advanced sensors, analytics and other technologies – which the Chinese in turn will seek to counter as quickly as they can.
The result may be a supercharged, ongoing technology race between the Navy’s unmanned capabilities and China’s countermeasures. If the Navy is to win that race, it is crucial that new capabilities be developed and fielded with digital engineering—but not the way digital engineering for the Navy is commonly practiced today. A new approach is needed, one that takes digital engineering out of the mostly exclusive realm of original equipment manufacturers (OEMs), and makes it more open to the Navy, and to a wider range of industry and other partners.
The Problem: Limited Insight Into Design Data
Currently, most digital engineering practiced for major Navy programs of record and other projects is conducted by OEMs in their own digital environments. Because these environments are largely closed, the Navy lacks real-time insight into the design data. The OEMs typically do their design work in their own digital environments, and then extract limited data points and present them to the Navy in contractual artifacts like spreadsheets, PowerPoint presentations, and pdf files. These artifacts are usually delivered only at major milestone design reviews.
This makes it difficult for the Navy to flag problems or gain detailed insight before a design goes to testing. Not only does the Navy have to wait until the end of a design phase to obtain the artifacts, the artifacts themselves may not have all the data Navy engineers need to fully evaluate and influence the design. This often results in extensive rework and other delays. Much of the speed that digital engineering offers the Navy is simply lost.
Closed OEM digital environments also hamper the ability of the Navy to tap innovation within the wider technology development community. Other providers normally have limited access to the information they might need—including design and configuration data, system architectures and key interfaces—to determine whether they might possess new solutions to offer the Navy. While some of this information may be contained in legacy documents, it could take weeks or months to sort out—and even then it might not be enough. Here again, the Navy loses out on the potential of digital engineering.
Shared Digital Engineering Environments
If the Navy is to take full advantage of digital engineering for unmanned systems, the design work needs to be conducted in common, or shared digital environments. Shared digital environments can take several different forms, but in essence they provide multiple parties with common access to design data. They might be sponsored or managed by the Navy, by OEMs, or by other entities. The Navy is already moving toward shared digital environments, and now has the opportunity to build on that progress.
In a shared digital environment, the Navy can see the same design data the OEM is working with, and so can spot potential problems in real time, without needing to refer to artifacts at a later date. For example, if an OEM is developing a new side-scan sonar for an unmanned underwater vehicle, the Navy can provide much faster review, analysis and feedback across the entire lifecycle of the design—all of which would help get the sonar integrated, tested and fielded more rapidly.
Opening up digital engineering environments also fosters competition and innovation, by bringing in the wider community of technology providers, including academia and non-traditional defense contractors. Shared digital environments give providers earlier and deeper insight into what the Navy needs. And the more providers that can look at the problem, the greater chance that one of them will say, “We know how to solve it.”
More Open Architectures, Less Vendor-Lock
One of the keys to rapid technology insertion in unmanned systems is the ability to plug-and-play the best new technologies from across the provider community. This requires open architectures, so that any provider can build solutions that will seamlessly integrate with current systems. Shared digital engineering environments do much to encourage these open architectures. That’s because shared environments aren’t effective unless the architectures let everyone in. Shared digital engineering environments and open architectures go hand-in-hand; each promotes the other.
At the same time, this approach substantially reduces vendor-lock. When other providers have direct insight into design data—rather than just legacy documents—the Navy is less dependent on the OEMs for system updates and upgrades. And with open architectures, the Navy is no longer locked into an OEM’s proprietary approaches. Naturally, all of this must occur under appropriate levels of cybersecurity to prevent intrusions, manipulations, and theft of cutting-edge technical data—even as we reap the benefits of open architectures.
Faster Adoption Of Digital Engineering
Shared digital environments are the key to digital engineering not only for emerging platforms such as unmanned systems, but also for the Navy’s transformational technologies for critical priorities, including Project Overmatch. Shared digital environments speed this wider. adoption of digital engineering.
Currently, each OEM typically has its own set of digital engineering tools and techniques, which are often not compatible with others. Common digital environments encourage common approaches, making it easier. for the Navy to take digital engineering out of isolated pockets, and scale it across any number of projects.
Building On The Navy’s Progress
The Navy is already moving toward shared digital environments. One example is the planned Rapid Autonomy. Integration Laboratory (RAIL), which will test new autonomous capabilities for unmanned maritime vehicles. Another example is The Forge, where the Navy can rapidly develop, test and distribute software upgrades to the Aegis and the Ship Self-Defense. System (SSDS) platforms.
Both RAIL and The Forge are Navy sponsored shared digital environments. This model of government-industry collaboration gives the Navy full. access to the digital environments, and taps the innovation of the wider community of technology providers.
By building on the successes of these and other shared digital environments, the Navy has the opportunity to unlock the full power of digital engineering for unmanned vehicles on the leading edge in the Pacific, and for initiatives across the Navy.
BRIAN ABBE ([email protected]) is the client service officer for Booz Allen’s Navy/Marine Corps business. He leads the development of solutions and technologies for the Navy and Marine Corps in areas such as unmanned systems; information warfare; biometrics; antitamper; air traffic control; position, navigation, and timing; augmented reality/virtual reality; and fabrication and prototyping.
COMMANDER ERIC BILLIES ([email protected]) a retired surface warfare officer, leads Booz Allen’s
business in the Pacific Northwest helping Navy clients chart innovative approaches for USV/UUV employment, and driving immersive tech (VR/AR/XR) across Booz Allen’s Global Defense Group.
MIKE LAPIERRE ([email protected]) is a senior systems engineer at Booz Allen specializing in
developmental engineering and platform HW/SW integration using MBSE and digital engineering-based
analyses.
BOOZALLEN.COM/DEFENSE
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