Indoor localization based on subcarrier parameter estimation of LoS with wi-fi

With the wide application of MIMO-OFDM technology, Channel State Information (CSI) as a fine-grained feature can be extracted from PHY layer with Wi-Fi. Although CSI has a better performance on expressing the spatial and temporal features of wireless signal, it is more sensitive to the multipath reflection. As a result, Line-of-Sight (LoS) identification and corresponding subcarrier parameter estimation play an important role in improving positioning accuracy. In this paper, we propose a complete parameter processing framework, which involves phase calibration, phase ambiguity elimination, subcarrier parameter (amplitude and phase) estimation of LoS, fingerprint feature extraction and relationship mapping from fingerprint feature to position estimate. The experimental results show that, compared with existing algorithm, our proposed algorithm improves the positioning accuracy by 2.3% in LoS and 10.7% in NLoS cases.

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