US Air Force / Airman 1st Class Codie Trimble
AI and machine learning could help F-15 EW avionics handle emitter ambiguities and emerging threats in sparse and dense signal environments.
John Keller
Mar 15th, 2021
WRIGHT-PATTERSON AFB, Ohio – U.S. Air Force airborne electronic warfare (EW) experts would like to apply artificial intelligence (AI) and machine learning technologies to existing and developmental EW avionics for the Air Force F-15 combat jet.
Officials of the Air Force Lifecycle Management Center at Wright-Patterson Air Force Base, Ohio, issued a request for information (AFLCMC-WAQ-F15) on Thursday for the AFLCMC Cognitive EW project.
This project is surveying industry to find companies able to apply cognitive AI and machine learning algorithms to advance the capabilities of F-15 airborne electronic warfare (EW) systems in development or in production.
The Air Force wants to find companies with strong EW experience in algorithms and technologies that could enable EW systems aboard the F-15 to respond to emitter ambiguities and emerging threats quickly and intelligently in sparse and dense signal environments.
The goal is to develop and build cognitive EW technologies at least as mature as a laboratory breadboard version (TRL-4), and investigate challenges of adaptive, agile, ambiguous, and out-of-library complex emitters that operate inside RF background noise. The Air Force also is interested in cognitive technologies that provide rapid EW reprogramming and learning capability for improved system performance.
The Air Force F-15 Program Office is looking for cognitive EW technologies that could be installed in the next two years into EW systems in development for the F-15 combat jet.
EW systems aboard the F-15 aircraft today include the BAE Systems Eagle Passive Active Warning Survivability System (EPAWSS), which this year entered low-rate initial production; the Northrop Grumman AN/ALQ-135 automatic EW system that manages and defeats several different threats simultaneously; and the Northrop Grumman externally mounted ALQ-131 self-protection jammer pod.
Companies interested in participating on this airborne cognitive EW project should email responses no later than 12 April 2021 to the Air Force's Michael Crane at michael.crane.11@us.af.mil. Those responding should use the RFI response form that is available online at https://beta.sam.gov/api/prod/opps/v3/opportunities/resources/files/2d27b6e793cf4b3096e0892b920e4fc1/download?api_key=null&token=.
Email questions or concerns to the Air Force's Capt. Max Harkavy at maxim.harkavy@us.af.mil, Maj. Joel Sanders at joel.sanders.3@us.af.mil, or David Black at david.black@us.af.mil.
More information is online at https://beta.sam.gov/opp/db33f3c0d6b749cb9bd5e577d4195886/view.
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