Real-Time Dismount Detection and Tracking Using Synthetic Aperture Radar (SAR) System

AFRL-WPAFB has initiated various programs to better understand the coherent information in SAR data. The current effort is intended to further this objective by developing algorithms to detect dismounts in SAR imagery that are acquired via: i) subaperture monostatic and along-track bistatic monopulse SAR data from a single pass; ii) subaperture monostatic SAR data of a single pass; and iii) subaperture monostatic SAR data of multiple passes. We will use 2D spatially-varying adaptive filtering in range and Doppler domains to blindly calibrate these dual imagery for clutter cancellation. The approach does not require complicated hardware development and time-consuming signal processing of a multiple-channel SAR platform that are essential for other algorithms such as STAP. To improve the system sensitivity to detect dismounts, we propose the use of a nonlinear flight path such as AFRL"s GOTCHA platform. We also utilize an innovative feature-aided tracking technique which has shown good performance for tracking weak and slowly-moving target signatures in strong clutter. In addition to GOTCHA data, Goleta Star would also collect SAR data with its dual-channel Ka-band UAV radar. Thus, the proposed algorithms and associated signal processing form a basis for a practical and real-time approach to detect and track dismounts. BENEFIT: The anticipated result from successful completion of this project will be a set of innovative subaperture-based nonlinear SAR signal processing algorithms and their associated hardware implementation for real-time processing to detect, track and image moving dismounts that are applicable in surveillance and reconnaissance radar platforms of the Departments of Defense, Homeland, and Justice.