Multipath-based probabilistic fingerprinting method for indoor positioning
LI Jiahui1, ZHANG Yan2, LUAN Fengyu1, LI Xueru1, ZHOU Lai1, ZHOU Shidong1
1. Department of Electronic Engineering, Tsinghua University, Beijing 100084, China;
2. School of Information and Electronics, Beijing Institute of Technology, Beijing 100081, China
Abstract：The space-alternating generalized expectation-maximization (SAGE) algorithm provides efficient, accurate indoor channel multipath estimation. This paper describes a multipath-based probabilistic fingerprinting method for indoor positioning that utilizes the channel multipath parameters obtained by the SAGE algorithm as fingerprinting data to achieve better positioning accuracy and robustness. Tests of measurements in a typical indoor environment show that this method is more accurate than traditional indoor positioning methods.
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