An Indoor Localization Strategy for a mini-UAV in the Presence of Obstacles

In this paper, we propose a novel approach to mini‐UAV localization in a wireless sensor network. We firstly employ the environment adaptive RSS parameters’ estimation method to estimate the parameters of range estimation model. However, the direct path from the target to a beacon is blocked by obstacles in a complicated indoor environment. So the proposed method, which employs a sequential probability ratio test to identify whether the measurement contains non‐line of sight (NLOS) errors, is tolerant to parameter fluctuations. Finally, a particle swarm optimization‐based method is proposed to solve the established objective function. Simulation results show that the proposed method achieved relatively higher localization accuracy. In addition, the performance analyses, carried out for a realistic indoor environment, shows that the proposed method still preserves the same localization accuracy.