Current acquisition, tracking, and pointing technologies employ optical image processing and/or inertial measurement unit data to mitigate image jitter in critical air  borne targeting applications. Image processing is typically performed using filters with known shortcomings. In general, they are ill-suited for nonlinearly moving targets which is what is observed in a jittering image stream.

Recent development of an enhanced image processor based on the Particle Filter Algorithm (PFA) is attractive because, among other advantages, they inherently handle target nonlinearities. The enhanced PFA has been designed to improve speed, compensate jitter, and reduce detectable target SNR through the incorporation of a number of preprocessing components.

The High Energy Laser (HEL) Mobile Demonstrator is an effective system to counter RAM and has the potential to address the threat of UASs. Adverse weather conditions limit acquisition and tracking performance. Polaris is investigating a variety of sensing modalities across the infrared to improve acquisition and tracking performance in adverse weather. Atmospheric propagation models are being studied and additional models are being developed to assess atmospheric and weather effects of representative RAM signatures. The effort will focus on the potential for polarimetric sensing to improve signal to background ratios.

Countering UASs is an ever-increasing challenge due to the variety of threats. The control systems in particular are continually evolving which complicates detection, identification, and tracking. A robust and reliable means of completing these steps in the kill chain is required. Polaris proposes to enhance the optical signatures over that of standard sensors with polarization sensitive cameras operating from visible to LWIR. This offers a multi-modal, multi-spectral sensor suite which allows us to implement algorithms that take advantage of the multi-modal sensing for optimal contrast and detection, identification, and tracking performance.