Item-Level Indoor Localization With Passive UHF RFID Based on Tag Interaction Analysis

Abstract

Radio-frequency identification (RFID) with a received signal strength indicator (RSSI) is a low-cost and low-complexity approach for item-level indoor localization. Although RSSI-based algorithms suffer from multipath effect and other environmental factors, reference tags and RSSI changes can be utilized to further improve the localization accuracy. However, the current algorithms lack deep analysis of the influence of tag interaction on localization accuracy and faces the challenge of simultaneously locating multiple close targets. In this paper, we propose an analysis method about how tag interaction affects a tag antenna radiation pattern and an RSSI change. The tag interaction analysis guides us to improve the design of RSSI-based localization algorithms. We take the k-nearest neighbor (k-NN) algorithm and the Simplex algorithm as two examples. The experimental results show that the revised k-NN and the revised Simplex algorithms are robust to different numbers, spacing, and materials of target objects, and they are superior to other RFID localization schemes, considering cost, capability of simultaneous localization of multiple targets, and location estimation errors.