Indoor Passive Localization Based On Channel State Information

Passive indoor localization plays an important role in applications such as security and smart housing.Received Signal Strength Indicator is the most popular physical parameter utilized in indoor localization.However,Received Signal Strength Indicator is coarse-grained and not stable enough.Instead,Channel State Information outperforms Received Signal Strength Indicator with fine granularity and high stability.In this paper,we first explore and discuss the principle and characters of Channel State Information,and then design methods to realize passive indoor localization.To enhance the performance of the system,we propose level of confidence.As the results of experiments reveal,our schemes can achieve a relatively excellent performance in different indoor environments.What’s more,to obtain more detailed feature of human’s activity,we study orientation detection,which lays a foundation for our future work.The contribution for this paper mainly consists of the following parts:(1)We introduce some traditional schemes of indoor localization based on Received Signal Strength Indicator.Then Channel State Information is proposed.We discuss the superiority of Channel State Information from its fine granularity and stability as well as the reasons why it can be used for passive localization;(2)To make the data more reliable and efficient,we study some methods to pre-process and extract features from the original data;(3)According to the characters of the data and the demand of localization system,we compare and balance several classification algorithms,and finally select Naive Bayes as our basic algorithm during the phase of passive localization;(4)We propose level of confidence by combining the results from different antenna pairs.It can help enhance the total accuracy of localization system with an improvement of about 30% at best case.The experiments from several scenarios also demonstrate that our schemes can adapt well in diverse indoor environments;(5)We realize passive detection of human’s orientation.Experiments are carried out to prove feasibility and some factors which may affect the accuracy of detection are analyzed.The accuracy for 4 orientations detection at best case is more than 90%.