AI RESEARCH
SEArch: Optimistic Policy Selection Between Scene Noise and Drift for UAV Radar Search
arXiv CS.LG
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ArXi:2606.01325v1 Announce Type: cross Unmanned Aerial Vehicles (UAVs) equipped with radar sensors are deployed for target search missions in diverse environments, where targets exhibit characteristic signatures (e.g., respiration micro-motion in human search) detectable through occlusions. A fundamental challenge arises from shifts in radar statistics as the UAV moves through a dynamic and potentially non-stationary environment, rendering any fixed signal-processing strategy suboptimal; yet perception and adaptation must run onboard a resource-constrained aerial node in real time.