Research On Indoor Carrier Phase Localization Algorithm Based On Wi-Fi

With the popularization of mobile devices and the rapid development of Location Based Services(LBS),people have higher and higher requirements for the accuracy and reliability of localization.Channel State Information(CSI)can provide more detailed Channel Frequency Response(CFR),so the Wi-Fi based CSI indoor high-precision localization technology has become the mainstream research in the field of localization.However,CSI-based localization methods always have some errors in the extraction of characteristic parameters,and some localization technologies need to modify the network card drivers and transform the hardware equipment,which are not universal and costly.Therefore,the parameter extraction process is simplified without changing the existing hardware devices and protocols in this thesis.Then,based on the exsiting errors of the characteristic parameters,a more universal indoor carrier phase localization algorithm based on Wi-Fi is proposed and the accuracy and reliability of the algorithm proposed is analyzed in this thesis.The research contents of this thesis are as follows:Firstly,an indoor carrier phase localization algorithm based on Wi-Fi is proposed.The indoor multipath environment is modeled based on the S-V channel model,and errors in the CSI carrier phase are analyzed combined with the Wi-Fi signal processing process under IEEE 802.11 n protocol in order to constructe the theoretical model of the CSI carrier phase.Then the phase information of the CSI center frequency subcarrier and the signal Time of Flight(To F)of the Line of Sight(Lo S)path are extracted.In order to eliminate the initial phase error and clock error,a carrier phase differential localization model is constructed through the virtual reference point to achieve the initial target location.The virtual baseline constraint method is used to solve the integer ambiguity solution.Meanwhile,in order to solve the fluctuation of localization,the carrier phase localization optimization algorithm based on extended Kalman filter is used to get the precise location of the target.Secondly,the performance of the algorithm proposed in this thesis is verified through experiments in different scenarios.In a typical indoor static environment,the median localization error is 0.12 m,and the maximum localization error is 0.31 m.In a typical indoor dynamic environment,including straight lines and random path,the median localization errors are both 0.12 m,and the maximum localization errors are 0.31 m and0.32 m,respectively.The results show that the proposed algorithm has high accuracy and reliability,which can effectively eliminate the integer ambiguity,solve the instability in the localization process,and improve the localization accuracy gradually.Finally,the accuracy and stability of the integer ambiguity solution,the influence of observation errors and reference point selection on localization accuracy are analyzed in this thesis.The experimental results show that the localization performance of the proposed algorithm is basically not affected by the phase measurement error and the To F measurement error.The average localization error is between 0.12 m and 0.13 m,which is robust and adaptable.