TY - GEN
T1 - RLLL: Accurate Relative Localization of RFID Tags with Low Latency
AU - Liu, Xuan
AU - Yang, Quan
AU - Zhang, Shigeng
AU - Xiao, Bin
N1 - Funding Information:
This work is partially supported by the National Natural Science Foundation of China (Grant Nos. 61602167, 61772559, 61772446 and 61972140) and in part by the National Defense Basic Research Plan under Grant JCKY2018110C145. Dr. X-uan Liu’s work is partially supported by the National Defense Science and Technology Innovation Special Zone Project of China.
Publisher Copyright:
© 2020 IEEE.
PY - 2020/6
Y1 - 2020/6
N2 - Radio frequency identification (RFID) has been widely used in many smart applications. In many scenarios, it is essential to know the ordering of a set of RFID tags. For example, to quickly detect misplaced books in smart libraries, we need to know the relative ordering of the tags attached to the books. Although several relative RFID localization algorithms have been proposed, they usually suffer from large localization latency and cannot support applications that require real-time detection of tag (product) positions like automatic manufacturing on an assembly line. Moreover, existing approaches face significant degradation in ordering accuracy when the tags are close to each other. In this paper, we propose RLLL, an accurate Relative Localization algorithm for RFID tags with Low Latency. RLLL reduces localization latency by proposing a novel geometry-based approach to identifying the V-zone in the phase reading sequence of each tag. Moreover, RLLL uses only the data in the V-zone to calculate relative positions of tags and thus avoids the negative effects of low-quality data collected when the tag is far from the antenna. Experimental results with commercial RFID devices show that RLLL achieves an ordering accuracy of higher than 0.986 with latency less than 0.8 seconds even when the tags are spaced only 7 mm from adjacent tags, in which case the state-of-the-art solutions only achieve ordering accuracy of lower than 0.8 with localization latency larger than 3 seconds.
AB - Radio frequency identification (RFID) has been widely used in many smart applications. In many scenarios, it is essential to know the ordering of a set of RFID tags. For example, to quickly detect misplaced books in smart libraries, we need to know the relative ordering of the tags attached to the books. Although several relative RFID localization algorithms have been proposed, they usually suffer from large localization latency and cannot support applications that require real-time detection of tag (product) positions like automatic manufacturing on an assembly line. Moreover, existing approaches face significant degradation in ordering accuracy when the tags are close to each other. In this paper, we propose RLLL, an accurate Relative Localization algorithm for RFID tags with Low Latency. RLLL reduces localization latency by proposing a novel geometry-based approach to identifying the V-zone in the phase reading sequence of each tag. Moreover, RLLL uses only the data in the V-zone to calculate relative positions of tags and thus avoids the negative effects of low-quality data collected when the tag is far from the antenna. Experimental results with commercial RFID devices show that RLLL achieves an ordering accuracy of higher than 0.986 with latency less than 0.8 seconds even when the tags are spaced only 7 mm from adjacent tags, in which case the state-of-the-art solutions only achieve ordering accuracy of lower than 0.8 with localization latency larger than 3 seconds.
UR - http://www.scopus.com/inward/record.url?scp=85094840420&partnerID=8YFLogxK
U2 - 10.1109/IWQoS49365.2020.9212981
DO - 10.1109/IWQoS49365.2020.9212981
M3 - Conference article published in proceeding or book
AN - SCOPUS:85094840420
T3 - 2020 IEEE/ACM 28th International Symposium on Quality of Service, IWQoS 2020
SP - 1
EP - 10
BT - 2020 IEEE/ACM 28th International Symposium on Quality of Service, IWQoS 2020
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 28th IEEE/ACM International Symposium on Quality of Service, IWQoS 2020
Y2 - 15 June 2020 through 17 June 2020
ER -