Vision Guided MIMO Radar Beamforming for Enhanced Vital Signs Detection
  in Crowds
Shuaifeng Jiang Ahmed Alkhateeb Daniel W. Bliss Yu Rong
Radar as a remote sensing technology has been used to analyze human activity
for decades. Despite all the great features such as motion sensitivity, privacy
preservation, penetrability, and more, radar has limited spatial degrees of
freedom compared to optical sensors and thus makes it challenging to sense
crowded environments without prior information. In this paper, we develop a
novel dual-sensing system, in which a vision sensor is leveraged to guide
digital beamforming in a multiple-input multiple-output (MIMO) radar. Also, we
develop a calibration algorithm to align the two types of sensors and show that
the calibrated dual system achieves about two centimeters precision in
three-dimensional space within a field of view of $75^\circ$ by $65^\circ$ and
for a range of two meters. Finally, we show that the proposed approach is
capable of detecting the vital signs simultaneously for a group of closely
spaced subjects, sitting and standing, in a cluttered environment, which
highlights a promising direction for vital signs detection in realistic
environments.