| With the rise of the Internet of Things and the widespread deployments of wireless networks,the demand for location-based services has gradually increased.Indoor localization technologies have attracted the widespread attention from researchers.Received signal strength(RSS)is often used in fingerprint-based and ranging-based indoor localization methods.However,the indoor multipath interference can affect the performance of indoor localization.Attacking to this problem,the channel state information(CSI)of the physical layer is exploited to reflect the current channel state with a finer granularity and achieve more accurate location estimation.The paper designs and implements a device-free indoor localization method based on channel state information fingerprint difference.The main research content is as follows.First of all,a preprocessing method based on effective subcarrier selection is proposed to reduce the system overhead.Taking the channel frequency response and the channel impulse response to distinguish the position into account,the channel frequency response is selected as the fingerprint feature.Secondly,the method of fingerprint difference of channel state information is proposed as a feature to establish a fingerprint database,and passive device-free indoor positioning is realized.Based on the impact on the signal when the user moves in different directions,an incremental accuracy method using coarse-grained localization and fine-grained localization is adopted.This method uses the influence of users in different areas on the link to determine the area where the user is located,then reduces the amount of system for the fine-grained localization.Finally,fingerprint data were collected in two typical indoor environments,and the effects of different experimental parameters on the proposed method performance were analyzed and evaluated.The results show that the proposed method can achieve the localization accuracy superior to the states of arts. |
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