TY - JOUR
T1 - A precise RFID indoor localization system with sensor network assistance
AU - ZHANG, Dian
AU - LU, Kezhong
AU - MAO, Rui
PY - 2015/4
Y1 - 2015/4
N2 - Indoor localization is very critical for medical care applications, e.g., the patient localization or tracking inside the building of the hospital. Traditional Radio Frequency Identification (RFID) technologies are very popular in this area since their cost is very low. In such technologies, each tag acts as the transmitter and the Radio Signal Strength Indicator (RSSI) information is measured from the readers. However, RSSI information suffers severely from the mult i-path phenomenon. As a result, if in a very large area, the localization accuracy will be affected seriously. In order to solve this problem, we introduce Wireless Sensor Networks (WSNs) with only a few nodes, each of which acts as both transmitter and receiver. In such networks, the change of signal strength (referred as dynamic of RSSI) is leveraged to select a cluster of reference tags as candidates. Then the final target location is estimated by using the RSSI relationships between the target tag and candidate reference tags. Thus, the localization accuracy and scalability are able to be improved. We proposed two algorithms, SA-LANDMARC, and COCKTAIL. Experiments show that the localization accuracy of the two algorithms can reach 0.7m and 0.45m, respectively. Compared to most traditional Radio Frequency (RF)-based approaches, the localization accuracy is improved at least 50%.
AB - Indoor localization is very critical for medical care applications, e.g., the patient localization or tracking inside the building of the hospital. Traditional Radio Frequency Identification (RFID) technologies are very popular in this area since their cost is very low. In such technologies, each tag acts as the transmitter and the Radio Signal Strength Indicator (RSSI) information is measured from the readers. However, RSSI information suffers severely from the mult i-path phenomenon. As a result, if in a very large area, the localization accuracy will be affected seriously. In order to solve this problem, we introduce Wireless Sensor Networks (WSNs) with only a few nodes, each of which acts as both transmitter and receiver. In such networks, the change of signal strength (referred as dynamic of RSSI) is leveraged to select a cluster of reference tags as candidates. Then the final target location is estimated by using the RSSI relationships between the target tag and candidate reference tags. Thus, the localization accuracy and scalability are able to be improved. We proposed two algorithms, SA-LANDMARC, and COCKTAIL. Experiments show that the localization accuracy of the two algorithms can reach 0.7m and 0.45m, respectively. Compared to most traditional Radio Frequency (RF)-based approaches, the localization accuracy is improved at least 50%.
KW - radio frequency
KW - RFID
KW - support vector regression
KW - hybrid
UR - https://www.scopus.com/inward/record.uri?eid=2-s2.0-84930730941&doi=10.1109%2fCC.2015.7114062&partnerID=40&md5=0dfbd9b77739d495475284a60b6695c0
U2 - 10.1109/CC.2015.7114062
DO - 10.1109/CC.2015.7114062
M3 - Journal Article (refereed)
VL - 12
SP - 13
EP - 22
JO - China Communications
JF - China Communications
SN - 1673-5447
IS - 4
ER -