The RFID data clustering algorithm for improving indoor network positioning based on LANDMARC technology

Abstract

Radio frequency identification (RFID) is a technique that uses radio frequency signals to automatically position the target. RFID-based location identification based on dynamic active RFID calibration (LANDMARC) system has prominent superiority in indoor positioning of complex environment. However, the original LANDMARC algorithm has disadvantages such as few reference tags, impractical weight definition, wrong selection for neighbor tags, unreasonable layout of readers and reference tags. In the work, an improved LANDMARC system was established by using 4 readers, 4 nearest neighbors and 28 reference tags. After that, the wrong neighbor tags were judged by distance constraint. The RSSI value was divided into 128 energy levels to set weight formula of index neighbor tag, thus obtaining more ideal indoor positioning effect.