TY - GEN
T1 - Hybrid technique for indoor positioning system based on Wi-Fi received signal strength indication
AU - Torteeka, Peerapong
AU - Chundi, Xiu
AU - Dongkai, Yang
N1 - Publisher Copyright:
© 2014 IEEE.
PY - 2014
Y1 - 2014
N2 - An indoor positioning system based on Receive Signal Strength Indication(RSSI) from wireless access equipment has become very popular in recent years. This system is very useful in many applications such as tracking service for older people or customer inside living communities, mobile robot localization, logistics systems etc. While outdoor environment using Global Navigation Satellite System(GNSS) and cellular network work well and are widespread used for navigation. However, there is a problem with signal propagation from satellites or cell site. They cannot be used effectively inside complex building areas or even in an urban environment. In general, the widely used method for indoor environment positioning based on Wi-Fi consists with two main categories, which are trilateration technique and location fingerprint technique(LF). It is already known that the explicit positioning performance of trilateration technique is more sensitive to noise effect than LF technique. Nevertheless, the accuracy of LF technique depends on training data set and it does not work well when environment changes. In this article, we propose the hybrid algorithm, the combination of the advantages of both systems, which is able to improve the accuracy stability and robustness. The performance of this algorithm is evaluated by the experimental results, which shows that our proposed scheme can achieve a certain level of positioning system accuracy.
AB - An indoor positioning system based on Receive Signal Strength Indication(RSSI) from wireless access equipment has become very popular in recent years. This system is very useful in many applications such as tracking service for older people or customer inside living communities, mobile robot localization, logistics systems etc. While outdoor environment using Global Navigation Satellite System(GNSS) and cellular network work well and are widespread used for navigation. However, there is a problem with signal propagation from satellites or cell site. They cannot be used effectively inside complex building areas or even in an urban environment. In general, the widely used method for indoor environment positioning based on Wi-Fi consists with two main categories, which are trilateration technique and location fingerprint technique(LF). It is already known that the explicit positioning performance of trilateration technique is more sensitive to noise effect than LF technique. Nevertheless, the accuracy of LF technique depends on training data set and it does not work well when environment changes. In this article, we propose the hybrid algorithm, the combination of the advantages of both systems, which is able to improve the accuracy stability and robustness. The performance of this algorithm is evaluated by the experimental results, which shows that our proposed scheme can achieve a certain level of positioning system accuracy.
KW - Extended Kalman Filter(EKF)
KW - Indoor Positioning System
KW - K-Nearest Neighbor(K-NN)
KW - Location Fingerprint technique
KW - RSSI
KW - Wi-Fi trilateration technique
UR - https://www.scopus.com/pages/publications/84988273244
U2 - 10.1109/IPIN.2014.7275467
DO - 10.1109/IPIN.2014.7275467
M3 - 会议稿件
AN - SCOPUS:84988273244
T3 - IPIN 2014 - 2014 International Conference on Indoor Positioning and Indoor Navigation
SP - 48
EP - 57
BT - IPIN 2014 - 2014 International Conference on Indoor Positioning and Indoor Navigation
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 5th International Conference on Indoor Positioning and Indoor Navigation, IPIN 2014
Y2 - 27 October 2014 through 30 October 2014
ER -