15 janvier 2021 | International, Aérospatial
by Pat Host
The US Air Force (USAF) has downselected Northrop Grumman as the sole contractor to complete final project efforts to provide the electronic warfare (EW) suite for the service's Lockheed Martin F-16 Fighting Falcon fleet.
Northrop Grumman spokesman Stephen Lamb said on 11 January that the company was selected in 2019 to develop a prototype internally mounted EW suite and digital radar warning receiver for F-16s. Northrop Grumman, he said, is performing on this contract. L3Harris was also competing under this contract. However, L3Harris spokesperson Kristin Jones said on 12 January that the company was not selected to move forward.
This EW suite will protect pilots from radio frequency (RF)-guided weapons by detecting, identifying, and defeating advanced threat systems, according to a company statement. Northrop Grumman's solution uses common building blocks and architecture. Lamb said the company has combined its ultra wideband radar warning receiver technology with a lightweight processor and digital transmitter modules to provide effective protection.
Northrop Grumman will deliver and demonstrate a safety of flight-qualified prototype to meet customer requirements under this other transaction agreement (OTA) contract, and is working toward its fielding. Lamb said the OTA period of performance ends in mid-2021.
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Nathan Strout After landing a contract with the U.S. Air Force in April, California-based company Labelbox announced May 20 it is making its artificial intelligence training data platform available more widely to the federal government and intelligence community. Labelbox offers a software platform by the same name that allows development teams to manage the data used to train machine learning algorithms. For instance, in order for a machine learning tool to successfully begin identifying missile launchers in satellite imagery, it needs to be fed hundreds — or even millions — of pre-labeled pictures identifying the objects it needs to identify. The more accurate training data is fed to the algorithm, the better it works. Some government machine learning projects need to process petabytes of data per day, the company says, a flow of data that can be overwhelming. “Labelbox is an integrated solution for data science teams to not only create the training data but also to manage it in one place,” said CEO Manu Sharma in a statement. “It's the foundational infrastructure for customers to build their machine learning pipeline.” The platform can be used in the cloud or on-premises, allowing data science teams to work together across agencies or locations, the company claims. In April, the company announced it had won an Air Force Innovation Hub Network (AFWERX) Phase 1 Small Business Innovation Research contract to conduct feasibility studies on how their platform could integrate with ongoing Air Force efforts. Now, the company is partnering with Carahsoft Technology Corp. to make their platform more widely available to the federal government and the intelligence community. Carahsoft will be able to provide the platform to interested agencies through its NASA Solutions for enterprise-wide procurement contracts and reseller partners, the company announced May 20. https://www.c4isrnet.com/artificial-intelligence/2020/05/20/this-platform-will-help-train-ai-algorithms-for-the-military/