Multitarget detection and tracking with continuous capture microwave imaging

Continuous capture microwave image detection and ranging (m-Widar) is an emerging sensing concept which combines sparse image reconstruction with an inverse light transport model. This enables a ‘single pixel microwave camera’ to densely image a surrounding environment in milliseconds via reflected microwaves, while requiring minimal hardware and set up. As such, m-Widar has many potential novel applications, including sensing through walls, vehicle detection, and standoff vital-sign monitoring. This work describes m-Widar sensing fundamentals and the challenges involved for practical multi-object detection and tracking. We present a Bayesian Hidden Markov Model (HMM) tracking approach to address these issues, along with proof-of-concept simulation assessments and directions for ongoing work.