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@article{ART002727777},
author={Seung-Hoon Oh and MAENG JUHYUN},
title={Improvement of location positioning using KNN, Local Map Classification and Bayes Filter for indoor location recognition system},
journal={Journal of The Korea Society of Computer and Information},
issn={1598-849X},
year={2021},
volume={26},
number={6},
pages={29-35},
doi={10.9708/jksci.2021.26.06.029}

TY - JOUR
AU - Seung-Hoon Oh
AU - MAENG JUHYUN
TI - Improvement of location positioning using KNN, Local Map Classification and Bayes Filter for indoor location recognition system
JO - Journal of The Korea Society of Computer and Information
PY - 2021
VL - 26
IS - 6
PB - The Korean Society Of Computer And Information
SP - 29
EP - 35
SN - 1598-849X
AB - In this paper, we propose a method that combines KNN(K-Nearest Neighbor), Local Map Classification and Bayes Filter as a way to increase the accuracy of location positioning. First, in this technique, Local Map Classification divides the actual map into several clusters, and then classifies the clusters by KNN. And posterior probability is calculated through the probability of each cluster acquired by Bayes Filter. With this posterior probability, the cluster where the robot is located is searched. For performance evaluation, the results of location positioning obtained by applying KNN, Local Map Classification, and Bayes Filter were analyzed. As a result of the analysis, it was confirmed that even if the RSSI signal changes, the location information is fixed to one cluster, and the accuracy of location positioning increases.
KW - Positioning;KNN;K-Mean;Bayes Filter;Mobile Robot
DO - 10.9708/jksci.2021.26.06.029
ER -

Seung-Hoon Oh and MAENG JUHYUN. (2021). Improvement of location positioning using KNN, Local Map Classification and Bayes Filter for indoor location recognition system. Journal of The Korea Society of Computer and Information, 26(6), 29-35.

Seung-Hoon Oh and MAENG JUHYUN. 2021, "Improvement of location positioning using KNN, Local Map Classification and Bayes Filter for indoor location recognition system", Journal of The Korea Society of Computer and Information, vol.26, no.6 pp.29-35. Available from: doi:10.9708/jksci.2021.26.06.029

Seung-Hoon Oh, MAENG JUHYUN "Improvement of location positioning using KNN, Local Map Classification and Bayes Filter for indoor location recognition system" Journal of The Korea Society of Computer and Information 26.6 pp.29-35 (2021) : 29.

Seung-Hoon Oh, MAENG JUHYUN. Improvement of location positioning using KNN, Local Map Classification and Bayes Filter for indoor location recognition system. 2021; 26(6), 29-35. Available from: doi:10.9708/jksci.2021.26.06.029

Seung-Hoon Oh and MAENG JUHYUN. "Improvement of location positioning using KNN, Local Map Classification and Bayes Filter for indoor location recognition system" Journal of The Korea Society of Computer and Information 26, no.6 (2021) : 29-35.doi: 10.9708/jksci.2021.26.06.029

Seung-Hoon Oh; MAENG JUHYUN. Improvement of location positioning using KNN, Local Map Classification and Bayes Filter for indoor location recognition system. Journal of The Korea Society of Computer and Information, 26(6), 29-35. doi: 10.9708/jksci.2021.26.06.029

Seung-Hoon Oh; MAENG JUHYUN. Improvement of location positioning using KNN, Local Map Classification and Bayes Filter for indoor location recognition system. Journal of The Korea Society of Computer and Information. 2021; 26(6) 29-35. doi: 10.9708/jksci.2021.26.06.029

Seung-Hoon Oh, MAENG JUHYUN. Improvement of location positioning using KNN, Local Map Classification and Bayes Filter for indoor location recognition system. 2021; 26(6), 29-35. Available from: doi:10.9708/jksci.2021.26.06.029

Seung-Hoon Oh and MAENG JUHYUN. "Improvement of location positioning using KNN, Local Map Classification and Bayes Filter for indoor location recognition system" Journal of The Korea Society of Computer and Information 26, no.6 (2021) : 29-35.doi: 10.9708/jksci.2021.26.06.029