Paper Title :Wi-Fi Multi-Fingerprint Technique For High Accuracy Indoor Positioning
Author :Kittipong Kasantikul, Xiu Chundi, Yang Dongkai
Article Citation :Kittipong Kasantikul ,Xiu Chundi ,Yang Dongkai ,
(2015 ) " Wi-Fi Multi-Fingerprint Technique For High Accuracy Indoor Positioning " ,
International Journal of Electrical, Electronics and Data Communication (IJEEDC) ,
pp. 39-43,
Volume-3, Issue-6
Abstract : Determining position is very important because it is easier and faster to search for the best route to the destination
with known position. Nowadays, more and more people move to urban areas and live in complex buildings. Indoor
positioning, therefore, plays an important role for determining position for indoor areas and also in urban areas. Indoor
positioning focuses on using smartphone to receive Wi-Fi signal due to its convenience and ease of operation. The Wi-Fi
Fingerprint has been commonly used for indoor positioning. Nevertheless, Fingerprint technique has limitation in multipath
rich indoor environment. Thus, this research focuses on improving the efficiency of Fingerprint technique by using multilayer
of Fingerprint, named “Multi-Fingerprint Technique” in order to overcome the limitation of Fingerprint technique. Two types
of Multi-Fingerprint technique were created in this research, which are (1) Patterned Fingerprint, radio map and converted
radio map (or named distance map) with certain reference nodes were used for position determining; each reference node on
distance map was calculated by the reversion of radio propagation model equation, and (2) Random Fingerprint, radio map and
distance map with random reference nodes were used for position determining; each reference node was randomly defined by
computer program. The four layers of radio maps and distance maps mentioned above were integrated (named
Multi-Fingerprint map) and k-Nearest Neighbor (k-NN) algorithm was used for classifying position. Experimental results
showed the difference in positioning efficiency among patterned distance map, random distance map, and Multi-Fingerprint
map. Besides, root mean square error equation was used for measuring errors between real position and estimated position.
Keywords- Indoor positioning, Multi-Fingerprint technique, Received Signal Strength Indicator, Path loss model, k-Nearest
Neighbor (k-NN)
Type : Research paper
Published : Volume-3, Issue-6
DOIONLINE NO - IJEEDC-IRAJ-DOIONLINE-2262
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Published on 2015-06-16 |
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