  This work contributes to efforts on autonomously detecting a
vegetation-occluded target by airborne observers. It investigates and enhances
previous work on a Particle Swarm Optimization (PSO) strategy for Airborne
Optical Sectioning (AOS) drone swarms. First, it identifies two issues with
that method and proposes to resolve them by a leader stabilization for its
scattering and projection-based line positions for its default scanning
pattern. Second, it connects this method to other PSO variants and presents a
new adaptive PSO strategy for AOS drone swarms that draws on the ideas of
Adaptive PSO (APSO).
