In an RSSI-based RFID indoor localization system, the signal propagation model in each subregion is different from others due to heterogeneity of environmental interference distribution in the area. A region division-based localization method is proposed to divide the localization region into many triangle subregions.A multi-round voting method is used to search the sub-region where the target object is located.We then build a signal propagation model by estimating the environmental factor and path loss value of that sub-region. By introducing virtual reference tags, we construct a virtual signal strength space and find the nearest neighbor tags, and then calculate coordinates of the target with a self-correcting K nearest neighbor algorithm presented in this paper. Simulation experiments show that estimation accuracy and adaptability of the proposed method are significantly higher than that of LANDMARC and VIRE, especially in complex and low tag density environments.
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