Algorithms for Acquisition and Tracking

The ability to defeat small Unmanned Aerial Systems (UAS) and Rockets, Artillery and Mortars (RAM) is becoming a reality through directed energy weapons.Challenges remain in the first part of the kill chain, however.The first two steps in defeating them are 1) acquiring them when they are at a range sufficient so there is still the opportunity to defeat them, and 2) maintaining a track on them even when they pass in front of confounding backgrounds which includes clouds and terrain.Advanced algorithms can improve acquisition and tracking performance and are required to achieve the required capability for robust operation in difficult environments in all scenarios.Polaris Sensor Technologies proposes to adapt algorithms developed previously for low signal to noise ratio scenarios and for multi-modal sensor imagery, and to develop new algorithms using contemporary techniques such as super-resolution and machine learning to improve the acquisition and tracking for small, long range UAS and RAM targets for the HEL program.Image data from Counter-UAS and Counter-RAM tests will be used to develop, train, and assess the algorithms.Hardware implementations will be developed and tested for real time performance.