Teledyne FLIR OEM is expanding its Prism software lineup with a new variant designed to give military ground systems sharper battlefield awareness through AI-powered target recognition.
Called Prism Ground ISR, the software stack supports ground-based intelligence, surveillance, and reconnaissance (ISR) missions by combining AI-driven sensing with advanced computational imaging to detect, classify, and track potential threats.
The platform uses turbulence mitigation, dehazing, super-resolution, and advanced image processing to improve infrared imagery, extending detection range, reducing false alarms, and helping operators identify targets more quickly.
Trained on real and synthetic electro-optical and infrared data, Prism Ground ISR can distinguish between military vehicle classes and improve target recognition in cluttered environments.
It can classify up to 15 object classes, with Prism AIMMGen expanding the library through synthetic training data.
Built for Fast Deployment
Designed for rapid integration into tactical ground systems, Prism Ground ISR is compatible with Teledyne FLIR’s Boson+ and Neutrino camera families, including continuous-zoom models.
The software also supports third-party infrared and electro-optical sensors, allowing data from multiple sensor types to be fused into a single operating picture.
An accompanying software development kit is intended to simplify integration, reduce deployment risk, and accelerate the fielding of new capabilities.
Prism Ground ISR expands Teledyne FLIR OEM’s tactical software portfolio beyond its previously introduced Prism C-UAS platform and Prism SKR software.
“Just as Prism C-UAS transformed how we detect small, fast-moving drones, Prism Ground ISR marks a significant advancement in ground-based AI target recognition,” said Jared Faraudo, vice president of product management at Teledyne FLIR OEM.
“By integrating visible and infrared thermal data, including fine-grained military vehicle classification, we are turning raw data into a decisive tactical advantage.”
