Design and implementation of a novel real-time unmanned aerial vehicle localization scheme based on received signal strength

To accurately localize unmanned aerial vehicles (UAVs) is one of the key issues to deal with the security threats caused by UAVs. Thus, this article proposes a UAV localization scheme that utilizes the area grid quantization and transmit power statistical calibration techniques, in which the location and transmit power of the UAV are unknown. Firstly, the adaptive discrete particle swarm optimization (ADPSO) algorithm is used to find the global optimal solution to the localization problem. A grid quantization method is proposed to discretize the value space of the traditional PSO algorithm to reduce the estimated localization time. An adaptive factor is also introduced to adjust the value of power for each iteration in the discrete particle swarm optimization (DPSO) algorithm in order to find the global optimal solution efficiently. Secondly, the fixed transmit power range is adopted to calibrate the estimated value of transmit power and the corresponding location. The prototype system comprises four anchor nodes based on a universal software radio peripheral radio frequency (USRP RF). Finally, field experiments are carried out to demonstrate the effectiveness of the proposed localization scheme.