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This paper presents a UAV-driven sensor system with a rotating radar designed to locate people in collapsed buildings. A framework including motion estimation, motion compensation, tracking and clustering is proposed. The developed algorithms enable the detection of people despite the motion of the UAV. Furthermore, we propose a Bayesian target selection approach to discriminate between human targets and other objects in the environment of the UAV with high confidence. The effectiveness of the proposed algorithms is demonstrated using measurements and a vital sign reference system, showing close agreement of the respiration signal over time with an overall respiration rate accuracy of 1.3 %.

Detection and Monitoring of People in Collapsed Buildings Using a Rotating Radar on a UAV