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• W2895989450 abstract "Recently, WiFi has been the focus of much research on activity recognition, indoor positioning, trajectory tracking. Traditional methods dealing with the research depend on received signal strength (RSS) or signal phase of the channel state information (CSI) of the commercial WiFi chips. But a lot of the research has not been turned into business application because of the instability of RSS and the lack of time synchronized phase between the transmitter and the receiver. Therefore, finding out how the signal propagates affected by the surroundings is the key question. In this paper, we design and implement WFSense, which tracks the direction of signal propagation of commercial WiFi system. WFSense represents the indoor multipath by taking full advantage of the subcarriers in OFDM and the space diversity across multi-antennas in MIMO system to improve MUSIC algorithm to estimate the angle of arrival (AoA) and departure (AoD) of the multipath signals. The minimum description length (MDL) principle is exploited to estimate the number of the multipath signals. WFSense identifies the directpath from the multiple paths with the time of flight (ToF) deduced by sanitizing the phase. The experiment results in different scenarios demonstrate that WFSense achieves a great performance." @default.
• W2895989450 created "2018-10-26" @default.
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• W2895989450 date "2018-08-01" @default.
• W2895989450 modified "2023-09-25" @default.
• W2895989450 title "Signal Tracking Using Commodity WiFi" @default.
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• W2895989450 doi "https://doi.org/10.1109/bigcom.2018.00007" @default.
• W2895989450 hasPublicationYear "2018" @default.
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