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

• Published in: International journal of advanced robotic systems Vol. 9; no. 4
• Main Authors: Cheng, Long, Wu, Cheng-Dong, Zhang, Yun-Zhou, Wang, Yan
• Format: Journal Article
• Language: English
• Published: London, England SAGE Publications 01.10.2012; Sage Publications Ltd; SAGE Publishing
• Subjects: Accuracy; Acoustics; Algorithms; Barriers; Computer simulation; Experiments; Indoor environments; Localization; Methods; Noise; Parameter estimation; Particle swarm optimization; Remote sensors; Success; Unmanned aerial vehicles; Variation; Wireless networks; Wireless sensor networks; indoor localization; non-line of sight (NLOS); wireless sensor networks; particle swarm optimization; mini-UAV
• ISSN: 1729-8806; 1729-8814
• DOI: 10.5772/52754

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.