10 juillet 2024 | International, Terrestre, Sécurité
9 décembre 2020 | International, Naval
The US Navy wants to find ships to kill using aerial drones launched from submarines
By: David B. Larter
WASHINGTON – The name of the game in the Pacific is stand-off range. But with longer range torpedoes and anti-ship missiles in the arsenal, submariners are looking to a new domain to help them extend their deadly reach: The air.
In an October request for information, Naval Sea Systems Command's Submarine Combat and Weapons Control Program Office asked industry for input into a “Submarine-Launched Unmanned Aerial System,” or SLUAS, currently in development.
The Navy has been interested in sub-launched drones for some time and has been testing prototypes, but the RFI shows the service is getting serious about the idea as it adds longer-range torpedoes and anti-ship cruise missiles to the arsenal of its attack submarines.
The idea for the SLUAS is an ambitious one.
The drone would launch from a submerged submarine out of a 3-inch ejector tube used for sonobuoys, flares and countermeasures among other things. The battery-operated UAS would then deploy its wings and operate for an hour, well beyond the range visible from just the low-in-the-water periscope.
Additionally, the UAS should have an “electro-optic capability with reliable target solution analysis,” the RFI said, adding that it should be able to “operate at ranges out to the line-of-sight radio horizon, and use a variable bandwidth encrypted datalink with at least 256-bit encryption strength.
The drone should also have a degree of autonomy and “include the ability to operate in an emission-controlled environment and operate without constant radio communication links.”
“Every submarine has a 3-inch launcher, so in theory, every submarine could operate with UASs,” said Bryan Clark, a retired submarine officer and senior fellow with The Hudson Institute. “The idea is that you would be about the size of a sonobuoy — it could be pretty long — and you'd put it inside a canister. Then you launch this in a canister, it floats to the surface and the USA deploys from there.
“And from there it can either connect up with the submarine or it could connect with another unit, and it gives you the ability to have over-the-horizon surveillance.”
“The demonstrations have been pretty successful,” Clark added.
The responses to the RFI were due in November.
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7 juin 2019 | International, Aérospatial, C4ISR
Deep Learning Model Speeds Up, Automates Satellite Image Analysis
Lockheed Martin (NYSE: LMT) develops satellite imagery recognition system using open-source deep learning libraries to quickly identify and classify objects or targets in large areas across the world, potentially saving image analysts countless hours manually categorizing and labeling items within an image. Global Automated Target Recognition runs in the cloud, using Maxar's Geospatial Big Data platform (GBDX) to access Maxar's 100 petabyte satellite imagery library and millions of curated data labels across dozens of categories that expedite the training of deep learning algorithms. Fast GPU's let GATR scan a large area very quickly, while deep learning methods automate object recognition and reduce the need for extensive algorithm training. GATR teaches itself what the identifying characteristics of an object area or target, for example, learning how to distinguish between a cargo plane and a military transport jet. The system scales quickly to scan large areas, including entire countries. GATR uses deep learning techniques common in the commercial sector and can identify ships, airplanes, buildings, seaports, and many other categories. “There's more commercial satellite data than ever available today, and up until now, identifying objects has been a largely manual process,” said Maria Demaree, vice president and general manager of Lockheed Martin Space Mission Solutions. “Artificial Intelligence models like GATR keep analysts in control while letting them focus on higher-level tasks.” GATR has a high accuracy rate, well over 90% on the models we've tested so far. It only took two hours to search the entire state of Pennsylvania for fracking sites – that's 120,000 square kilometers “I'm not an expert on what oil production sites are, and I don't have to be,” said Mark Pritt, senior fellow at Lockheed Martin and principle investigator for GATR. “This system teaches itself the defining characteristics of an object, saving valuable time training an algorithm and ultimately letting an image analyst focus more on their mission.” GATR builds on research Pritt's team pioneered during a Intelligence Advanced Research Projects Activity (IARPA) challenge, called the “Functional Map of the World.” The Lockheed Martin team was the only team from a company who placed in the top five. https://news.lockheedmartin.com/news-releases?item=128745
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7 mai 2024 | International, Terrestre
How DC became obsessed with a potential 2027 Chinese invasion of Taiwan
Some in defense circles say the U.S. needs to prepare for Beijing's invasion of Taiwan in 2027. China experts say it isn’t a deadline.