  We demonstrate how efficient autonomous drone swarms can be in detecting and
tracking occluded targets in densely forested areas, such as lost people during
search and rescue missions. Exploration and optimization of local viewing
conditions, such as occlusion density and target view obliqueness, provide much
faster and much more reliable results than previous, blind sampling strategies
that are based on pre-defined waypoints. An adapted real-time particle swarm
optimization and a new objective function are presented that are able to deal
with dynamic and highly random through-foliage conditions. Synthetic aperture
sensing is our fundamental sampling principle, and drone swarms are employed to
approximate the optical signals of extremely wide and adaptable airborne
lenses.
