Military Embedded Systems

Military AI innovation, SOSA hot topics at Embedded Tech Trends


February 04, 2020

John McHale

Editorial Director

Military Embedded Systems

The COTS Confidential Roundtable gathers experts from the defense electronics industry – from major prime contractors to defense component suppliers. Each Roundtable will explore topics important to the military embedded electronics market. This issue, we discuss how embedded computing suppliers are leveraging artificial intelligence (AI) for military applications, the impact of the Sensor Open Systems Architecture (SOSA) Consortium and other open architecture initiatives, and the outlook for the future of embedded technologies in the defense and aerospace markets with sponsors of the Embedded Tech Trends (ETT) conference, held during late January in Atlanta, Georgia.

In photo: Embedded Tech Trends 2020 covered embedded computing trends such as AI, military open architecture initiatives, and more. Shown is VITA Executive Director Jerry Gipper opening the event. Photo credit: Jena Warren/The Simon Group.

This time, our panelists are Rodger Hosking, Vice President and Co-founder, Pentek; David Jedynak, Chief Technology Officer, Curtiss-Wright Defense Solutions; John Bratton, Director of Product Marketing, Mercury Systems; and Doug Patterson, Vice President, Global Marketing, Aitech Systems.

MIL-EMBEDDED: Artificial intelligence, or AI, was
the topic of many presentations at ETT this year. How is AI making an impact in
military electronics? Which applications are benefitting from the technology
now? Electronic warfare? Radar? Other?

HOSKING: Virtually all military electronics are benefiting from AI, and the technology is moving
quickly. The first applications are “expert systems” that deliver relatively
quick decisions and actions for a relatively narrow task. These include
classification and identification of all objects in the operating theater of
war, and even determining the most effective countermeasures or attack
strategies. Another very important application is extracting critical
intelligence from the glut of electromagnetic spectrum signals and internet
traffic of all types, and then detecting patterns or relationships among those
signals for further action. With continued expansion of deployed unmanned
military vehicles, autonomous AI systems can help boost their survival rate and
mission effectiveness. AI is not just developing smart engines, neural
networks, or algorithms. It requires engineering of hundreds of specialized
systems, each evolving over time to exploit a broader scope of sensor inputs,
and more complex decision-making elements and principles to deliver
increasingly accurate, targeted results.

JEDYNAK: Machine learning, deep learning, and AI are revolutionizing applications that help warfighters
identify threats and objects from afar, detect unseen dangers, and locate and
resolve equipment issues before failures occur. AI is key to the DoD’s Third
Offset Strategy [which seeks to outmaneuver advantages made by top adversaries
primarily through technology]. The specific examples almost don’t matter – we
can take it as a given that it provides a significant leap forward. Think of
the automobile versus horse and buggy: While so much remains extremely
familiar, and on a spec sheet may not look all that different (i.e., four wheels,
room for passengers, leather seats, room for luggage, luxury styling, etc.),
the performance/capability difference is immense. In electronic warfare (EW),
for example, AI enables machines to identify objects and take appropriate
actions in a faster and more accurate way than humans can on their own. In
signals intelligence (SIGINT) applications, machine learning and deep learning
can be used to automate signal classification, which otherwise typically
requires extensive expertise and is prone to human error.

Another key area where machine learning capabilities can be
applied to increase the safety of warfighters and equipment is health and usage
monitoring systems (HUMS). It enables computers to be trained to intelligently
predict when equipment failures are most likely to occur and allows issues to
be addressed before a mission is affected. For example, if a HUMS application
detects that extra power is being applied to a wheel on a Humvee, it could mean
the pressure in that tire has dropped and the tire could collapse. The same
technology can also be used to inspect the physical integrity of air and ground
vehicles before and after field operations. Ultimately, AI is enabling faster,
more accurate identification of threats to today’s military platforms and
helping deliver a competitive edge by accelerating and strengthening functions
traditionally performed by humans.

BRATTON: From an embedded standpoint, our customers are seeking greater processing power and density to
enable their defense systems to execute smarter missions, have increased
autonomy, and make sense of and fuse together ever-wider streams of sensor
data. Many of these applications are requiring processing hardware with
headroom so quickly evolving machine learning, cognitive decision-making and AI
processing capability can be deployed without an immediate tech refresh (AI capability
doubles every three to six months). Today, AI applications usually reside
within the data center. We are seeing a trend towards creating the same
processing architecture closer to the data source, often on mobile, remote
platforms. The ability to scale, make secure, miniaturize, and deploy the
processing power and scalability of the composable data center and its
extensive software ecosystem is being packaged as high-performance embedded
edge computing (HPEEC) solutions that are enabling next-generation defense
systems to be deployed faster and with all the capabilities found in the most
contemporary commercially developed technology.

PATTERSON: AI is impacting nearly every area of the military, including some that weren’t even discussed
at Embedded Tech Trends (ETT). GPGPU technology is critical to these
advancements. Truly, AI is now today only scratching the surface of the
potential applications, defense included. The analogy of the “tip of the
iceberg” is perfectly applicable here – less than 10% of AI applications are
visible; the rest has yet to surface. As AI technology continues to advance and
line geometries shrink, even more raw horsepower will be at the applications
developers’ fingertips.

One major area is cybersecurity. Adaptive heuristics (and deep learning) have been developed and are being refined to monitor cloud
traffic, looking for key words and phrases that can then be placed in context
to help thwart and mitigate cyber hacks that threaten military platforms and reduce
the level of harm our troops are exposed to, mitigating collateral damage and
ultimately saving lives.

Another key area is surveillance and reconnaissance. This is
where AI implemented in GPGPUs really shines, as it’s the perfect mix of
parallel processing on literally hundreds of cores, tied to video capture and
image processing and display (if/when needed), all in the highest-definition
video standards.

Another application area is neural networks, where tens to
hundreds of cores can be networked together to potentially hundreds of similar
subsystems, each with hundreds of cores all addressing one or multiple
strategic or tactical situations in parallel. Today, through the technical
hardware and software tool innovations brought to the market by companies like
NVIDIA, Intel, and others – and adapting these for true defense and rugged
applications – teraflops of processing power can be applied at 15 to 30 per
node instead of kilowatts per node. This has been a dream of systems designers
and engineers for decades, and is now within reach. Imagine the raw compute
power of systems containing 500 to 1,000 parallel cores, each with from 1 to 30
TOPS [Tera Operations per Second], all networked and freely communicating to
other nodes in the system. AI and GPGPUs specifically are essentially hugely
parallel DSP engines all interconnected by crossbar matrices to memory and I/O
resources with Gb/sec pipes. The applications are truly endless, limited only
by the imagination.

MIL-EMBEDDED: Immediately following ETT, the Army,
Navy, and Air Force held the Tri-Services Open Architecture Interoperability
Demonstration at the Georgia Tech Research Institute showcasing the advantages
of SOSA and other open architecture efforts. Why does this effort seem to be so
different in terms of momentum than past initiatives? Military participation?
Passion among the industry players? Economics?

HOSKING: All of the above, for sure! Over the years, we all have seen standards and initiatives come and
go. Solidly founded upon sound objectives, the Sensor Open Systems Architecture
(SOSA) initiative goes well beyond a hardware or software specification. All
three services demonstrate commitment to aggregate their own standards into a
single standard to benefit from scale, availability, and life cycle support of
products. Vendors finally see a way to protect their costly IP development
efforts, by competing on innovation and technology instead of simply hardware
costs. Primes see more sources of new technology products to enhance systems
performance. DoD is already issuing request for proposals for systems, with
vendor selection based heavily on open standard architecture content.

JEDYNAK: The main difference is cultural – there’s a very different culture in DoD now, one that
is much more focused on doing and deploying fast rather than “silo”-ed thinking
– and again, that cultural change is also driven by the Third Offset Strategy.
The new culture is driving the fast transition of technology to the field, and
helping to overcome what some – only half-jokingly – call the Chinese
military’s greatest asset, the DoD’s famously cumbersome acquisition process.
Last month, for example, Secretary of Defense Mark Esper, speaking about U.S.
competition with China, said, “Our success is contingent upon a cohesive
approach across public and private sectors. For the department, this means
overhauling our policies and reshaping the culture within the department;
between the department and industry; and among our allies and partners around
the world."

Military participation in the open architecture and
interoperability effort has certainly impacted the momentum. Developers of
defense and aerospace solutions have been leveraging open standards to improve
interoperability for a number of years now; however, 2019’s Tri-Service
“Memorandum for Service Acquisition Executives and Program Executive Officers”
drove home the point that these initiatives are no longer optional – they are
vital and they are mandatory.

Support from industry players that have long endured the
challenges of limited interoperability is likely playing a critical role as
well. A true open standards approach offers systems integrators increased
flexibility to choose the solution that makes the most sense for their needs,
regardless of vendor. It reduces the costs and complexity of upgrading systems
and minimizes the SWaP [size, weight, and power] ramifications of adding new
functionality to a platform. What’s more, it creates a more fair and
competitive marketplace for COTS components – a benefit for vendors and
customers alike.

BRATTON: The Tri-Service demonstration illustrated how the SOSA approach is influencing the development
and deployment of low-risk, high-performance defense computing systems. SOSA
builds in multiple key differentiators that deliver the capabilities required
to maintain a technological separation between our defense systems and those of
our competitors. SOSA has:

· Tri-Service support and increasing alignment from industry and
prime contractors for scalability and affordability

· Security that is built-in and not bolted on and uses a single (12 V) power distribution rail

· Leverages a commercial business model enabling all stakeholders
to achieve what they require for success

· Common OpenVPX profiles and console ports for greater

· Ubiquitous common system manager and off-the-shelf software

· Compatibility with VICTORY [Vehicular Integration for C4ISR/EW
Interoperability], MORA [Modular OpenRF Architecture], CMOSS [C4ISR/EW Modular
Open Suite of Standards], and other major embedded modular open system
architectures for program velocity

The Tri-Service compatibility demonstration showed how these
commercial and technical attributes are driving the SOSA-aligned ecosystem,
efficiently putting the best commercially developed technology into the hands
of our service members faster.

PATTERSON: The key is the attraction of the Tri-Service adoption, which today is truly reaching across
the aisles and breaking down the old, once stovepiped, separation of the
military services, moving towards some form of commonality and potential unity.
It’s now gained passion and momentum in the industry itself and is being
thoroughly reinforced in the press as becoming the next motherhood and apple
pie idiom, dare I say, achieving nirvana. Whether or not it will actually
reach nirvana is another thing; it could be also be a groupthink mentality, all
nodding and chanting that SOSA is great. So, at the moment, the jury is still
out, but hope springs eternal in the current market. In terms of military
participation, it is being mandated by conformance (compliance) to the
standards and, once published by the program offices, there will literally be
no other option-- your products either conform or not.

MIL-EMBEDDED: What will be the next big thing for
military embedded technology five or ten years down the road? Predict the

HOSKING: Maintaining military superiority will require special attention to cybersecurity,
space-based weapons, hypersonic weapons, surface fleet protection, and
autonomous systems. Funding for all has certainly gained traction in the last
several years. Essential capabilities in imaging, recognition, detection,
classification, and identification will continue to be refined through advances
in sensors, AI, and machine learning. The greatest leverage against government
and military adversaries is our ability to deter aggression though overwhelming
advantages in these critical capabilities.

JEDYNAK: On the hardware front, future roadmaps will be smaller and more ubiquitous, more like Lego
bricks than cellphones. A good goal concept, recently briefed by the U.S. Army,
is the Iron Man/J.A.R.V.I.S. model, to provide seamless integration of
intelligent systems with warfighters via always-on/resilient networks. This
approach will enable situational awareness across multiple battle domains
(physical, electromagnetic, cyber) and leverage AI to appropriately triage, decimate,
route, fuse, and present actionable data to the warfighter in real time. It
will also provide the warfighter with the ability to easily control their
unmanned assets in a natural manner (e.g., natural language commands, gestures,
biofeedback). And once again, all of this is part of the Third Offset Strategy
emphasis on “man-machine teaming.” From the hardware perspective, it means an
emphasis on mixed-signal intelligent systems – physical sensors plus RF sensors
plus network communications plus AI, all cyber hardened with easy scalability
and extensibility from the smallest of systems (little drones) to big HPEC
(armored supercomputers), and everything in between.

AI will continue to automate and improve defense
applications, evolving the intelligent and connected battlefield. The increase
in unmanned platforms will have a positive impact in protecting human lives
from danger. Even better, the proliferation of autonomous vehicles and unmanned
air taxis in the commercial space will likely accelerate technology
advancements in unmanned defense platforms.

BRATTON: The rate of technological advancement has never been higher. With initiatives like SOSA,
the conditions are set where defense system development and deployment can also
progress at the speed of technology itself. Consider the commercial digital
convergence that created converged media, information systems, smartphones, and
autonomous vehicles. This commercial digital convergence is seen all facets of
our lives, has a proven roadmap, and is enabling new technology breakthroughs
in processing domains everywhere. This capability will drive the military
digital transformation enabling platforms to shrink and become more capable and
adaptable for mission autonomy. Early adoption is underway within unmanned
land, sea, and air platforms, including unmanned aerial vehicles. The latter is
where the military digital convergence is accelerating the fastest, as
extreme-SWaP performance, proven system integrity, and processing power, among
other requirements, are the prerequisite to success. If trends continue, then
the commercial domain will deliver autonomous smart ground and air taxis;
within the defense and aerospace domains, equally capable smart platforms will
be deployed that maintain a capability gap between our systems and those of
other great powers and competitors.

PATTERSON: The future, it seems, is limited only now by our imaginations. As newer semiconductor
technologies continue to advance and lithographies continue to shrink, power
and performance mount while memory capacities continue to grow. Add to the mix
the advances in AI software and advanced programming tools and languages, and
the future is, indeed, limitless. I do, however, hope we keep the “Terminator”
movies in mind and stay far away from a “Skynet” that becomes self-aware. Isaac
Asimov’s three rules of robotics are as valid today and into the future as when
he penned “I, Robot” in 1950:

· A robot may not injure a human being or, through inaction, allow
a human being to come to harm.

· A robot must obey orders given it by human beings except where
such orders would conflict with the First Law.

· A robot must protect its own existence as long as such protection
does not conflict with the First or Second Law.