In order to improve the mobile node tracking accuracy of indoor environment, a mobile node tracking algorithm based on channel propagating characteristic is proposed. Channel propagation model is established by actual measurement and fitting analysis in three different scenarios, which included closed corridor, open corridor and laboratory. The anchor node periodically measures the RSSI of the beacons from mobile node, to estimate the coordinates of the mobile node location, speed and direction by using the Maximum Likelihood method and channel model. The simulation results prove that the proposed scheme is effective and can meet the real-time requirements of indoor localization.
Published in | International Journal of Intelligent Information Systems (Volume 5, Issue 5) |
DOI | 10.11648/j.ijiis.20160505.12 |
Page(s) | 65-70 |
Creative Commons |
This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited. |
Copyright |
Copyright © The Author(s), 2016. Published by Science Publishing Group |
Wireless Sensor Network, Propagating Characteristic of Channel, Tracking, Maximum Likelihood
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APA Style
Ying Li, Yiliang Wu, Nina Hu, Guangsong Yang. (2016). Tracking Algorithm Based on Channel Propagating Characteristic in Wireless Sensor Network. International Journal of Intelligent Information Systems, 5(5), 65-70. https://doi.org/10.11648/j.ijiis.20160505.12
ACS Style
Ying Li; Yiliang Wu; Nina Hu; Guangsong Yang. Tracking Algorithm Based on Channel Propagating Characteristic in Wireless Sensor Network. Int. J. Intell. Inf. Syst. 2016, 5(5), 65-70. doi: 10.11648/j.ijiis.20160505.12
AMA Style
Ying Li, Yiliang Wu, Nina Hu, Guangsong Yang. Tracking Algorithm Based on Channel Propagating Characteristic in Wireless Sensor Network. Int J Intell Inf Syst. 2016;5(5):65-70. doi: 10.11648/j.ijiis.20160505.12
@article{10.11648/j.ijiis.20160505.12, author = {Ying Li and Yiliang Wu and Nina Hu and Guangsong Yang}, title = {Tracking Algorithm Based on Channel Propagating Characteristic in Wireless Sensor Network}, journal = {International Journal of Intelligent Information Systems}, volume = {5}, number = {5}, pages = {65-70}, doi = {10.11648/j.ijiis.20160505.12}, url = {https://doi.org/10.11648/j.ijiis.20160505.12}, eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijiis.20160505.12}, abstract = {In order to improve the mobile node tracking accuracy of indoor environment, a mobile node tracking algorithm based on channel propagating characteristic is proposed. Channel propagation model is established by actual measurement and fitting analysis in three different scenarios, which included closed corridor, open corridor and laboratory. The anchor node periodically measures the RSSI of the beacons from mobile node, to estimate the coordinates of the mobile node location, speed and direction by using the Maximum Likelihood method and channel model. The simulation results prove that the proposed scheme is effective and can meet the real-time requirements of indoor localization.}, year = {2016} }
TY - JOUR T1 - Tracking Algorithm Based on Channel Propagating Characteristic in Wireless Sensor Network AU - Ying Li AU - Yiliang Wu AU - Nina Hu AU - Guangsong Yang Y1 - 2016/10/17 PY - 2016 N1 - https://doi.org/10.11648/j.ijiis.20160505.12 DO - 10.11648/j.ijiis.20160505.12 T2 - International Journal of Intelligent Information Systems JF - International Journal of Intelligent Information Systems JO - International Journal of Intelligent Information Systems SP - 65 EP - 70 PB - Science Publishing Group SN - 2328-7683 UR - https://doi.org/10.11648/j.ijiis.20160505.12 AB - In order to improve the mobile node tracking accuracy of indoor environment, a mobile node tracking algorithm based on channel propagating characteristic is proposed. Channel propagation model is established by actual measurement and fitting analysis in three different scenarios, which included closed corridor, open corridor and laboratory. The anchor node periodically measures the RSSI of the beacons from mobile node, to estimate the coordinates of the mobile node location, speed and direction by using the Maximum Likelihood method and channel model. The simulation results prove that the proposed scheme is effective and can meet the real-time requirements of indoor localization. VL - 5 IS - 5 ER -