Abstract: For the problem of missing localization characteristics caused by the activation failure of passive UHF RFID tags,given the significant challenges in precisely modeling the channel,this paper proposes a missing localization characteristic estimation algorithm based on the linear model of signal strength Euclidean distance-space Euclidean distance to improve the localization accuracy of the scene analysis algorithms by increasing the number of characteristic dimensions.To increase the completeness of the scene matching data for nonactivated reference tags,the missing localization characteristics could be calculated directly by using the linear model.For the nonactivated target tags,the linear model is used to estimate the distance between the target tag and multiple benchmark reference tags,the least squares algorithm is used to estimate the preliminary location information of the target tag,and again the missing localization features are estimated using the linear model in reverse to complete the localization characteristics of the target tags.Experiments show that the proposed algorithm can not only effectively improve the localization accuracy of all missing target tags,but also the target tags around the missing reference tags.In addition,there is no additional hardware equipment included for this algorithm,which meets the application requirements of low-cost and high-precision.

Key words: Localization, Passive UHF RFID, Scene analysis, Signal strength, Characteristic estimation