Title :
Fuzzy-Adaptive Kaiman Filter for RFID localization
Author :
Nick, T. ; Gotze, Joachim ; John, Wolfgang
Author_Institution :
Inf. Process. Lab., Tech. Univ. Dortmund, Dortmund, Germany
Abstract :
Radio Frequency Identification (RFID) can not only be used to identify objects, but also to localize them. If Received Signal Strength Indicator (RSSI) values are converted into distances, a Constrained Unscented Kaiman Filter (CUKF) can estimate an object´s position via these measurements. In case of unknown or varying measurement noise a Fuzzy-Adaptive version of the filter (FACUKF) leads to an increase in location accuracy and filter consistency.
Keywords :
adaptive filters; nonlinear filters; radiofrequency identification; CUKF; FACUKF; RFID localization; RSSI values; constrained unscented Kaiman filter; filter consistency; fuzzy-adaptive Kalman filter; fuzzy-adaptive version of the filter; location accuracy; radio frequency identification; received signal strength indicator; Antenna measurements; Antennas; Covariance matrix; Kalman filters; Noise; Noise measurement; Radiofrequency identification; Fuzzy system; RFID localization; RSSI; Unscented Kaiman Filter;
Conference_Titel :
Ubiquitous Positioning, Indoor Navigation, and Location Based Service (UPINLBS), 2012
Conference_Location :
Helsinki
Print_ISBN :
978-1-4673-1908-9
DOI :
10.1109/UPINLBS.2012.6409751
