CSI Based High Accuracy Localization System

With the popular utilization of mobile devices,the center of interest is transformed to the new aspect of wireless indoor environment while the point is still on the side of utilizing active methods aimed at tracking target and indoor localization.But since 2013,Device-Free-Passive based indoor localization has appealed more attention because of its convenience and low power of transmitting,Within Wi-Fi,we are able to receive lots of rich channel information,and then using the maximum-likelihood to train our data so that we can reach our goal of localization.A new radio frequency(RF)fingerprint that incorporates the channel impulse response(CIR)and Angle of Arrival(AoA)was introduced to enhance the accuracy of the indoor positioning.To use the new fingerprint,we use the generalized distance metric,i.e.,Jensen-Shannon Divergence(JSD)and cluster center to compare the distance between data collected at the test point and given reference point.Based on the new RF fingerprint,we proposed a device free passive localization(DFPL)system that does not require the user to have any measurement devices.The user location is estimated by searching the reference points with the the smallest distance between the test data and the database.The experimental results show that the proposed system has better location accuracy method comparing with the conventional fingerprint algorithms.In addition,based on the accuracy of our stationary localization system and the obtained CSI data according to the localization phase,we put up with a tracking system based on a modified particle filter in order to track the moving target in the monitored area which is inspired by the online SLAM problem.