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《Chinese Journal of Sensors and Actuators》 2018-06
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Localization Algorithm Based on Wireless Channel State Phase Information Optimization

ZHOU Mingkuai;HUANG Wei;CHEN Bin;MAO Keji;Applied Engineering College,Zhejiang Business College;Zhejiang Branch of China Communications Services Company;Collage of Computer,Zhejiang University of Technology;  
With the increasing demand for location services,indoor localization technology based on Wi-Fi has been one of the research hotspots. By detecting the impact of environmental changes on the channel state information( CSI),Wi-Fi generally has the advantages such as strong versatility and low deployment cost. For the problem that most systems only use the amplitude feature of CSI,this paper designs and implements a localization algorithm based on the CSI phase feature optimization. This method combines the amplitude and phase parameters as a position fingerprint. Fingerprint databases were constructed after pre-smoothing and denoising the feature data,and then the classification of personnel positions was identified by machine learning methods. Because the phase and amplitude information can complement each other,it can make up for the misclassification of certain confusing positions,thus solving the problem of positioning accuracy and stability using a single feature. Experiments were performed in two different multipath scenarios. The effects of different fingerprint feature selections,data preprocessing methods,and three machine learning algorithms on positioning accuracy were compared. The results show that the proposed algorithm can generally increase by 13% on the basis of using only CSI amplitude characteristics.
【Fund】: 浙江省基础公益研究计划项目(LGG18F020018)
【CateGory Index】: TN92;TP181
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