Advanced UAV and Mortar Target Detection and Tracking Algorithms for Low Signal-to-Noise Ratio and Cluttered Environments

In this work, Areté Associates proposes to extend its long history of tracking and detection solutions to meet the challenge of tracking small and dim targets in high-clutter environments using a mid-wave infrared (MWIR) sensor coupled with innovative detection algorithms and processing. We present a track-before-detect, signal-integration approach that merges the functionality of Areté’s proven dim-target detection and tracking algorithms with SNR-increasing pre-processing, background-subtraction and whitening routines. In Phase I, we adapted and tested our algorithms using a suite of Areté-owned equipment and Graphics Processing Unit (GPU)-implementation. Pre-processing methods increased Signal-to-Noise Ratio (SNR) by 10-25 dB for all scenarios, while greatly reducing Signal-to-Clutter Ratio (SCR) for foliage/grass and cloud-edge clutter. Speed tests on a GPU-implemented version of the algorithms showed that a full processing chain is feasible at required frame rates. In Phase II, we will develop and test a breadboard demonstration system with new image stabilization and additional clutter rejection algorithms.