The US Air Force is turning to AI to sharpen battlefield decision-making, contracting Matrix Research to develop algorithms that fuse radar, infrared, and lidar data to automatically detect, classify, and prioritize targets.
The program, known as Combat Identification Automated Target Recognition Technology (CATCH), is a $15-million effort led by the Sensors Directorate of the Air Force Research Laboratory (AFRL).
CATCH focuses on new air-to-air and air-to-ground combat identification software algorithms for F-16 and F-15 aircraft.
The program is designed to help operators quickly size up detected objects: What is it? Is it friendly, hostile, neutral, or unknown? Is it a threat?
By fusing multi-mode sensor inputs, CATCH can reportedly overcome the limitations of individual sensors in extreme weather, darkness, complex terrain, and electromagnetic interference.
The program’s AI algorithms also aim to reduce misidentification, counter deception, and support rapid, accurate decisions, all while maintaining human oversight over mission-critical actions.
Based in Ohio, Matrix Research specializes in developing multi-mode sensor fusion algorithms using machine learning, signal processing for electromagnetic reconnaissance, and software that supports automatic target recognition and combat identification across multiple sensor types.
The CATCH program was first outlined in an AFRL solicitation issued in May 2025.
