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WiFi-based indoor localization using the fine time measurement (FTM) protocol has become a popular technique. However, in harsh Non-Line-of-Sight (NLoS) environments, WiFi FTM positioning (WFP) suffers from poor performance. In this letter, a novel WiFi FTM localization method with the assistance of geomagnetic positioning (GP) is proposed. To ensure the accuracy of GP, an enhanced mind evolutionary algorithm (EMEA) is designed. A fine-grained WiFi position estimation method using the overlapping searching area (OSA) and the coincident points selection strategy is proposed. Experimental results show that the EMEA-based GP improves the localization performance of WFP in NLOS environments, the mean localization error (ME) and root-mean-square error (RMSE) of the GP-aided WFP are 1.82 m and 2.08 m, respectively. Compared with the classic WFP using the weighted least square (WLS) method, the ME and RMSE are reduced by 51.7% and 52.4%, respectively.
Sun et al. (2022) studied this question.