Efficient UAV Localization Based on Modified Particle Swarm Optimization

In UAV communication network, accurate and fast localization is a critical issue, especially when UAV has high mobility, strict energy constraints and collision avoidance requirements. Conventional image or GPS based UAV localization methods suffer from either high computation complexity or large localization error, thus decreasing the efficiency or increasing the risk of UAV collision. Particle swarm optimization (PSO), on the other hand, is a potential swarm intelligence method that can efficiently deal with these issues. To reduce the complexity and increase the localization accuracy, in this paper we propose a modified PSO based on particle reduction and improved particle update criteria. The proposed PSO has much lower computation complexity with less localization error than the conventional PSO. Simulation results verify the effectiveness of proposed method.