April 13, 2021 | International, Aerospace, Naval, Land, C4ISR, Security
Raytheon names new CFO
Raytheon CFO Toby O’Brien has stepped down.
December 20, 2018 | International, C4ISR
DARPA Awards Six Teams During Final Spectrum Collaboration Challenge Qualifier
On December 12, DARPA held the second preliminary event of the Spectrum Collaboration Challenge (SC2) – the world's first collaborative machine-intelligence competition to overcome spectrum scarcity. Fifteen teams represented by members from across the academic, commercial and defense landscapes gathered at Johns Hopkins University Applied Physics Laboratory (APL) to pit their intelligent radio designs against each other in a head-to-head competition. At the event's conclusion, six of the eight top-scoring teams walked away with $750,000 each in prize money. While not all competitors received interim prizes, all 15 teams have an opportunity to move on to the next stage and compete in the 2019 Spectrum Collaboration Challenge grand finale, which will be held in conjunction with MWC19 Los Angeles, in partnership with CTIA, on October 23, 2019.
The six prize-winning teams from the second preliminary event are:
- Zylinium, a team of independent researchers
- MarmotE from Vanderbilt University
- Sprite from Northeastern University
- Erebus, a team of independent researchers
- Gator Wings from University of Florida
- SCATTER from IDLab, an imec research group at Ghent University and University of Antwerp, and Rutgers University
"During the second preliminary event we witnessed a technological shift," said Paul Tilghman, the DARPA program manager leading SC2. "For the first time, we saw autonomous collaboration outperform the status quo for spectrum management."
Starting in early December, each team's radio participated in 105 matches against competitors in the Colosseum, a massive RF testbed that was developed specifically for SC2. The matches were held in a round-robin fashion where each radio network – working in groups of threes, fours or fives – had multiple opportunities to compete against every other radio design in the competition. Roughly 400 matches were held in total to determine the final team rankings and the prize recipients.
During the PE2 matches, teams were put through six different RF scenarios designed to mimic the challenges that collaborative, autonomous radios will face in the real world. These scenarios challenged the radios to collaboratively mitigate interfering with an incumbent radio system, sense and adapt to the spectrum demands of high-traffic environments, handle the data demands of the connected soldier of the future, and beyond. Each scenario was designed to pressure test various elements of the teams' approaches and, in particular, their ability to successfully collaborate with the other radios operating within the same environment.
“The six different scenarios were closely aligned to actual situations that our defense and commercial systems face in the field. The Wildfire scenario, for example, replicates the complex communications environment that surrounds an emergency response situation, while the Alleys of Austin scenario was designed to mimic what's needed to help dismounted soldiers navigate and communicate as they sweep through an urban environment. This real-world relevance was critical for us as we want to ensure these technologies can continue to develop after the event and can transition to commercial and/or military applications,” said Tilghman.
The sixth scenario of the competition was used to determine the six prize winning teams. This scenario explored the essential question of the SC2 competition: can the top teams' collaborative SC2 radios outperform the status quo of static allocation? Each of the six teams that received awards at PE2 demonstrated that their radio was capable of carrying more wireless applications without the aid of a handcrafted spectrum plan, while simultaneously ensuring four other radio networks operating in the same area had improved performance. In short, each of these six radio networks demonstrated the autonomous future of the spectrum.
To aid with decision making, teams applied AI and machine learning technologies in various ways. Some leveraged the current generation of AI technologies like deep learning, while others used more conventional optimization approaches. There were also a few teams that used first wave, rule-based AI technologies.
“We're very encouraged by the results we saw at PE2. The teams' radios faced new and unexpected scenarios but were still able to demonstrate smart, collaborative decision making. PE2 showed us that AI and machine learning's application to wireless spectrum management creates a very real opportunity to rethink our current century-old approach,” said Tilghman.
The competition now enters its third year and moves closer to the finale, which will be held at one of the country's largest annual technology and telecommunications shows – MWC19 Los Angeles. More than 22,000 attendees from the broad mobile ecosystem and adjacent industry sectors will convene at this three-day event to discuss the current opportunities and future trends shaping the industry. The SC2 championship event will be held on the keynote stage of MWC19 Los Angeles on October 23, 2019.
At the conclusion of SC2's finale, three teams will be awarded $2 million, $1 million and $750,000, respectively, for first, second and third place. The real prize, however, will be the promise of a more efficient wireless paradigm in which radio networks autonomously collaborate to determine how the spectrum should be used moment-to-moment, helping to usher in an era of spectrum abundance.
For more information about DARPA's Spectrum Collaboration Challenge, please visit: https://spectrumcollaborationchallenge.com/
On the same subject
-
-
August 4, 2020 | International, Aerospace
Japan confirms single prime contractor for F-X
by Jon Grevatt Japan's Defence Minister Taro Kono confirmed on 31 July plans to nominate a “single prime” Japanese contractor to oversee the development of the country's next-generation fighter aircraft. In comments in a media briefing in Tokyo, Kono said the prime contractor – almost certainly Mitsubishi Heavy Industries (MHI) – will be expected to act as the lead systems integrator on the project, which has been dubbed F-X. “The MoD will adopt a single-prime system. [The selected company] will be responsible for integrating systems and the engine,” said Kono in comments published by the Ministry of Defense (MoD). Kano indicated that the MoD had now commenced the process for selecting companies to be involved in the development project but did not elaborate. In the media briefing, Kono also confirmed that the MoD is currently considering developing the F-X alongside the United Kingdom and the United States. The latter is regarded as leading candidate, given its strong diplomatic, economic, strategic, and industrial ties with Japan. The F-X project is led within the MoD by a dedicated office set up in April. According to the MoD, its responsibilities include technical investigations, budget execution, information security issues, and the control of intellectual property. https://www.janes.com/defence-news/news-detail/japan-confirms-single-prime-contractor-for-f-x
-
August 6, 2019 | International, C4ISR
Can a dragonfly teach a missile how to hunt?
By: Jen Judson WASHINGTON — A computational neuroscientist is studying whether a dragonfly's excellent hunting skills can be replicated in a missile's ability to maneuver and destroy targets midair with better precision. Dragonflies are vicious little creatures with a hit-to-kill track record of 95 percent, meaning only 5 percent of its prey escapes. Sandia National Laboratories' Frances Chance is building algorithms that simulate how a dragonfly processes information when intercepting prey, and she's testing them in a virtual environment. So far, the results are promising. The laboratories are federally funded and focus on national security missions through scientific and engineering research. The project is a yearlong, high-risk, high-gain effort that will wrap up in September, and it is funded by Sandia's Autonomy for Hypersonics Mission Campaign, Chance said. “I think what is really interesting about insects, in general, is they do something really fast and really well, but they are not particularly smart in the way you or I would think of ourselves as being smart,” Chance told Defense News in a recent interview. While insects may not be the right fit for studying cognitive capabilities to develop complex artificial intelligence, they are ideal for developing efficient computations for intercept capability. A dragonfly can react to a particular prey's maneuvers in 50 milliseconds, Chance explained. That amount of time accounts for information to cross three neurons in a dragonfly's brain. This indicates the dragonfly doesn't learn how to hunt, but rather the skill is inherent and part of its brain's hard-wiring. “The challenge then is: Is there anything that we can learn from how dragonflies do this that we can then bring to the next generation of missiles, or maybe even the next-next generation of missiles?” Chance said. By developing an artificial neural network that mimics a dragonfly's ability to hunt and then applying it to missile capabilities that rely on computation-heavy systems, one could reduce the size, weight and power needed for a missile's onboard computers; improve intercept techniques for targets such as hypersonic weapons; and home in on targets using simpler sensors. If the model of a dragonfly's neural circuit developed through Chance's research shows enough promise, she would then pass the information to scientists, who would try to directly apply it to weapons systems. One of the greatest leaps involves adapting an algorithm to handle the speed at which a missile flies. While a dragonfly is fast, it's not nearly as fast as a missile. Animal brains process information significantly slower than a computer, so it's possible computations can be sped up to better align with the speed at which a missile approaches targets. “The hope is that even if the algorithm isn't wildly successful, you might be able to say something about what you can get away with in terms of what types of capabilities you give the next generation of weapons,” Chance said. The model she's building is several steps removed from implementation onto a weapon. “I would consider the project complete when we have a viable model — ‘viable' meaning it does interception — and a bonus if it's neurobiologically plausible. There is no reason to force that for this type of research, but only because it doesn't necessarily matter; so something biologically inspired that works I would consider a success.” https://www.c4isrnet.com/land/2019/08/05/can-a-dragonfly-teach-a-missile-how-to-hunt/