TY - GEN
T1 - An accurate indoor positioning algorithm using particle filter based on the proximity of bluetooth beacons
AU - Momose, Ryoya
AU - Nitta, Tomoyuki
AU - Yanagisawa, Masao
AU - Togawa, Nozomu
N1 - Publisher Copyright:
© 2017 IEEE.
PY - 2017/12/19
Y1 - 2017/12/19
N2 - Indoor positioning without GPS is one of the most important problems in indoor pedestrian navigation. In this paper, we propose an accurate indoor positioning algorithm using a particle filter based on a floormap, where we use the proximity of the Bluetooth beacons as well as acceleration and geomagnetic sensors. In designing the likelihood function in the particle filter, we effectively use the proximity of the Bluetooth beacons, which just gives rough distance to the target beacon but more stable than conventional RSSI-based distance estimation. In addition to that, by effectively utilizing a floormap, the accumulated positioning errors due to the acceleration and geomagnetic sensors are much reduced. Moreover, when the radio waves from the Bluetooth beacons are blocked by obstacles, we can also take it into account in designing the likelihood function in the particle filter. Experimental results demonstrate that our algorithm can reduce the indoor positioning errors by up to 79% compared to several conventional algorithms.
AB - Indoor positioning without GPS is one of the most important problems in indoor pedestrian navigation. In this paper, we propose an accurate indoor positioning algorithm using a particle filter based on a floormap, where we use the proximity of the Bluetooth beacons as well as acceleration and geomagnetic sensors. In designing the likelihood function in the particle filter, we effectively use the proximity of the Bluetooth beacons, which just gives rough distance to the target beacon but more stable than conventional RSSI-based distance estimation. In addition to that, by effectively utilizing a floormap, the accumulated positioning errors due to the acceleration and geomagnetic sensors are much reduced. Moreover, when the radio waves from the Bluetooth beacons are blocked by obstacles, we can also take it into account in designing the likelihood function in the particle filter. Experimental results demonstrate that our algorithm can reduce the indoor positioning errors by up to 79% compared to several conventional algorithms.
UR - http://www.scopus.com/inward/record.url?scp=85045626831&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85045626831&partnerID=8YFLogxK
U2 - 10.1109/GCCE.2017.8229229
DO - 10.1109/GCCE.2017.8229229
M3 - Conference contribution
AN - SCOPUS:85045626831
T3 - 2017 IEEE 6th Global Conference on Consumer Electronics, GCCE 2017
SP - 1
EP - 5
BT - 2017 IEEE 6th Global Conference on Consumer Electronics, GCCE 2017
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 6th IEEE Global Conference on Consumer Electronics, GCCE 2017
Y2 - 24 October 2017 through 27 October 2017
ER -