Affiliations: Arkansas State University, State University, Arkansas, USA | University of Arkansas at Little Rock, Arkansas, USA
Note: [] Corresponding author: Farhad Moeeni, Arkansas State University, PO Box 130, State University, Arkansas 72467, USA. Tel.: +1 870 680 8442; E-mails: moeeni@astate.edu (F. Moeeni); cxchiang@ualr.edu (C.-C. Chiang).
Abstract: RFID-based localization has become a major area of interest in ubiquitous computing in the last decade. RFID has been used for identifying and tracking static objects such as inventory items or mobile objects such as robots, vehicles, etc. Various range-based and triangulation methods have commonly been used with RFID systems (active or passive) for localization purposes. These methods include RSS, TOA, TDOA, etc. On the other hand, less attention has been devoted to range-free or proximity methods. Specifically, the proximity methods work well with passive RFID systems. We propose proximity—based passive RFID model that can identify the location of mobile nodes relative to existing anchor nodes, i.e. nodes with known location. The study explores various algorithms for estimating location coordinates. These algorithms are much simpler to implement than other techniques such as the tag segregation. We also discuss the resulting accuracy and precision of the proposed model, implemented in a laboratory environment.
