Distributed autonomous situational awareness is one of the most important foundation for Unmanned Aerial Vehicle (UAV) swarm to implement various missions. Considering the appli-cation environment being usually characterized by strong confrontation, high dynamics, and deep uncertainty, the distributed situational awareness system based on UAV swarm needs to be driven by the mission requirements, while each node in the network can autonomously avoid collisions and perform detection mission through limited resource sharing as well as complementarity of respective advantages. By efficiently solving the problems of self-avoidance, autonomous flocking and split-ting, joint estimation and control, etc., perception data from multi-platform multi-source should be extracted and fused reasonably, to generate refined, tailored target information and provide reli-able support for decision-making.