Pathfinder is developing visual and IR-based remote sensing technology for aircraft. Using both single and multiple-camera approaches, Pathfinder's technology offers increased safety and situational awareness, as well as a  means to detect stealthy aircraft. Developed with actual flight test data, PSI's physics-based approach integrates aerodynamic modeling with deep learning.

Digital Engineering for Edge Systems (DEES)

Operational Prototype for Sense-and-Avoid Technology (OPSAT)

Federal Aviation Regulation paragraph 91.113(b) require aircraft operators “See and Avoid” other aircraft:

“When weather conditions permit, regardless of whether an operation is conducted under instrument flight rules or visual flight rules, vigilance shall be maintained by each person operating an aircraft so as to see and avoid other aircraft.”

Pathfinder’s OPSAT effort will provide Remotely Piloted Aircraft pilots with a “See and Avoid” capability using Commercial Off The Shelf components. The solutions developed under this effort will also be directly applied to drone detection and 360° situational awareness for the commercial and general aviation market.

OPSAT detecting an intruding aircraft

A Unique Approach

  • Passive sensing of Intruder aircraft

  • Developed from actual, verified flight data

  • Interfaces with existing avionics and COTS sensors

  • Integrates aerodynamic modeling with deep learning

  • Physics based, real-time, 3D model of ownship space

Multi-Use and Low Cost

  • UAS Detect and Avoid

  • Increased Safety & Situational Awareness for manned aircraft

  • Drone detection during vulnerable flight stages

DEES (FA8649-21-P1663) September 2021-December 2022 is a current program developing precision targeting instrumentation for future manned or unmanned fighters to achieve "kill at first shot" attacks on stealthy opponents.

The DEES project uses AI-based target detection routines to increase detection range. New single-camera range estimation algorithms provide an improved target state vector estimation capability. The program is also investigating multi-ship capabilities, using target detections from multiple aircraft for a range estimate.

We are conducting instrumented flight tests using improved embedded processors and high-resolution visible light and FLIR cameras. This new video data will be used to update the training of AI image detection routines. The flight tests also demonstrate new solution features that maximize single-camera range detection effectiveness.

DEES tracking a target aircraft