Abstract: Optimizing the monitoring points of complicated airport scenes can effectively improve the operating efficiency of airport scenes. However, the real-time positioning of monitoring points with high precision is still unresolved. Aiming at this problem, an adaptive niche ejection particle swarm algorithm combined with Taylor series expansion method is proposed. The positioning results of the proposed algorithm are taken as initial reference points for Taylor series iteration, solving the dependence of traditional Taylor series expansion method on the initial reference point selection. Simulation results show that the positioning estimation accuracy of the improved particle swarm algorithm combined with the Taylor series expansion method is greatly improved compared with the simple Taylor series expansion method.

Key words:  , airport scene surveillance, multipoint positioning, self-adaptive particle swarm algorithm, niche ejection strategy