Particle Swarm Optimization-Based Unmanned Aerial Vehicle Passive Localization Research

This paper addresses the problem two of pure azimuth passive localization of unmanned aerial vehicles (UAVs) based on the direction information received by the UAVs. The initial UAV is considered as the starting point or UAV number 1. By connecting with UAV number 3 and emitting signals, subsequent UAVs receive angle signals. The UAV that receives the signal closest to 60 degrees is selected, and due to slight deviations, this UAV is identified as UAV number 2. The particle swarm algorithm is then used to determine the position of UAV number 2. A plane is established based on this position. The UAV that receives the signal closest to 60 degrees is UAV number 5, and another application of the particle swarm algorithm determines its adjustment orientation. By continuing to calculate based on the signals close to 60 degrees, the positions of UAVs number 4, 6, 8, 9, 7, 11, and so on, are determined using the particle swarm algorithm multiple times. In the final part of this paper, we evaluate the established model, discuss its advantages and disadvantages, and propose future development prospects. This research has certain reference value for the development of related industries.