| Citation: | Kun LIU, Jianxin WU, Jie ZHEN, Tong WANG. Indoor Localization Algorithm Based on Array Antenna and Sparse Bayesian Learning[J]. Journal of Electronics & Information Technology, 2020, 42(5): 1158-1164. doi: 10.11999/JEIT190314
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Due to the influence of many factors such as multipath and multi-source, the traditional indoor localization algorithms based on Bluetooth signal strength have low performance in accuracy and stability. In order to solve the location problem in complex indoor environment based on Bluetooth signal, an indoor localization algorithm based on low-cost array antenna is developed. The algorithm utilizes single-channel using switch-antenna polarization sensitive array to sample Bluetooth signal, then combines the accurate array manifold measured in dark room and the algorithm of Polarized Fast Converging Sparse Bayesian Learning (P-FCSBL) to estimate the source’s angle, and finally gets the target location by angle. This algorithm makes full use of polarization information and angle information to separate target and multipath signal, and simultaneous sampling of one source ensures estimation stability. Finally, the effectiveness of the method is verified by the real data.
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