Adaptive Ranging And Positioning Based On Wi-Fi Channel State Information

With the rapid development of mobile and smart devices,smart phones have be-come the basis of the "Internet of Everything".Advanced technology products,such as virtual reality and smart homes,have promoted people's clothing,food,accommoda-tion and living experiences,and have built up personalized,intelligent application and service scenarios.Location-Based services(LBS)bring great convenience to people's daily life and work.In addition,most of the activities take place indoors,so researchers are paying more and more attention to the indoor positioning technology.With the continuous development of Wi-Fi technology and widespread adoption of devices with Wi-Fi capability,Wi-Fi based indoor positioning has become a mainstream branch of the research field of indoor positioning.This dissertation mainly focuses on the problem of geometric mapping based in-door positioning over Wi-Fi networks.Due to the movement of the target,the Wi-Fi signal is often disturbed in the indoor environments of different layouts,and the posi-tioning results are obviously influenced by the environmental changes.In order to cope with this problem,this dissertation adopts Channel State Information(CSI)combined with wireless signal propagation attenuation model to design and realize a self-adaptive positioning method.Compared with the self-adaptive positioning method proposed in this dissertation,the existing fingerprint positioning methods based on Wi-Fi networks often require a large amount of manpower and material costs.The existing positioning methods based on the model of Fresnel zone theory usually require inexistence of obsta-cles between transmitting and receiving antennas,and have more constraints and fewer applicabilities.In addition,the indoor positioning methods based on arrival Angle have high computational complexity.The main research contents and contributions of this dissertation can be summarized into two aspects:By analyzing the characteristics of fine-grained channel state of Wi-Fi signals,we propose a CSI-based adaptive ranging method.First,we employ the CSI test to detect the path blocking Of LOS(line-of-sight,LOS),and propose the adaptive compensation method for the path loss model based on the LOS detection results.Meanwhile,in order to utilize the feature of CSI frequency diversity better,we propose a CSI segmentation fusion method,in which the CSI is segmentally fused along its subcarriers to form multiple sets of effective CSIs for distance calcula-tion.Finally,the simulation experiment shows the ranging method proposed in this dissertation can realize the adaptive ranging according to the dynamic changes of environments.By using the above adaptive ranging scheme,the dissertation implements a CSI-based self-adaptive positioning method.When there are more than three AP nodes in the Wi-Fi networks,we determine an optimal AP collection according to the LOS signal strength and ranging results between target and APs.Then the adaptive positioning coordinate of the target position is derived from the range re-sults of the optimal APs and the geometric positioning algorithm.Meanwhile,in order to improve the positioning accuracy,we also propose to use the LOS signal strength between the target and APs to correct the positioning results.Finally,the simulation results show that the adaptive positioning method has the advantages of good accuracy and robustness.Compared with traditional ranging and positioning methods based on wireless sig-nal propagation attenuation model,the CSI-based self-adaptive ranging and positioning methods proposed in this dissertation can achieve a better accuracy.Moreover,they are applicable to more environments with fewer constraints.