Generic placeholder image

Recent Advances in Electrical & Electronic Engineering

Author(s): Lu Bai*, Chenglie Du and Jinchao Chen

DOI: 10.2174/2352096512666191024170807

DownloadDownload PDF Flyer Cite As
Weighted K-nearest Neighbor Fast Localization Algorithm Based on RSSI for Wireless Sensor Systems

Page: [295 - 301] Pages: 7

  • * (Excluding Mailing and Handling)

Explore Articles
About Journal
For Authors
For Editors
For Reviewers

Abstract

Background: Wireless positioning is one of the most important technologies for realtime applications in wireless sensor systems. This paper mainly studies the indoor wireless positioning algorithm of robots.

Methods: The application of the K-nearest neighbor algorithm in Wi-Fi positioning is studied by analyzing the Wi-Fi fingerprint location algorithm based on Received Signal Strength Indication (RSSI) and K-Nearest Neighbor (KNN) algorithm in Wi-Fi positioning. The KNN algorithm is computationally intensive and time-consuming.

Results: In order to improve the positioning efficiency, improve the positioning accuracy and reduce the computation time, a fast weighted K-neighbor correlation algorithm based on RSSI is proposed based on the K-Means algorithm. Thereby achieving the purpose of reducing the calculation time, quickly estimating the position distance, and improving the positioning accuracy.

Conclusion: Simulation analysis shows that the algorithm can effectively shorten the positioning time and improve the positioning efficiency in robot Wi-Fi positioning.

Keywords: K-nearest neighbor, Wi-Fi positioning, RSSI, wireless sensor system, location fingerprint positioning, K-Means.

Graphical Abstract

[1]
L. Zhang, and Q. Cheng, "Landscape (T), “A robust and low-cost sensor positioning system using the dual of target tracking", Proceedings of Int. Conf. Distributed Computing in Sensor Systems (DCOSS2006), vol. 6, . 2006
[2]
L. Zhang, X. Zhou, and Q. Cheng, "Landscape (3D): A robust sensor localization scheme for sensor networks over 3D terrains", Proceedings of IEEE Conf. Local Computer Networks (LCN).Tampa, FL, USA 2006, pp. 11.
[3]
L. Zhang, Q. Cheng, and Y. Wang, "A novel distributed sensor positioning system using the dual of target tracking", IEEE Trans. Comput., vol. 57, no. 57, pp. 246-260, 2006.
[4]
Y. Liang, X. Yu, and Z. Zhou, "Analysis of the indoor positioning systems in pervasive environment", Comput. Sci., vol. 37, no. 3, pp. 112-126, 2010.
[5]
"C. Chen, C. Lin, S. Lin, Indoor position location based on cascade correlation networks", IEEE International Conference on System, Man, and Cybernetics (SMC)Anchorage: AK, USA, . 2011, pp.2295-2300.
[6]
J. Chen, C. Du, and F. Xie, "Schedulability analysis of non-preemptive strictly periodic tasks in multi-core real-time systems", Real-Time Syst., vol. 52, no. 3, pp. 239-271, 2016.
[http://dx.doi.org/10.1007/s11241-015-9226-z]
[7]
J. Chon, and H. Cha, "Lifemap: A smart phone-based context provider for location-based services", IEEE Pervasive Comput., vol. 10, no. 2, pp. 58-67, 2011.
[http://dx.doi.org/10.1109/MPRV.2011.13]
[8]
""Peterson. L. E. K-nearest neighbor", Scholarpedia", Vol. 4, no. 2,2009
[9]
Ma. Kuanhong, Research on Wi-Fi Indoor Positioning Technology Based on Position Fingerprint., Harbin Institute of Technology: Harbin, 2016, pp. 10-13.
[10]
X. Lu, W. Yuan, and Y. Qiu, "Improved dynamic prediction fingerprint localization algorithm based on KNN", Jisuanji Yingyong Yanjiu, vol. 34, no. 7, pp. 2016-2018, 2017.
[11]
Y. Wang, Text Classification Based on Decision Tree and K-Nearest Neighbor Algorithm., Tianjin University: Tianjin, 2006, pp. 22-25.
[12]
X. Li, Research and Implementation of Weighted Clustering Algorithm for K-MeansType Variables., Harbin Institute of Technology: Harbin, 2006, pp. 18-31.
[13]
Y. Lu, Research and Application of Cluster Analysis Using the Data Mining Method., Anhui University: Anhui, 2007.
[14]
A. Chen, N. Chen, and L. Zhou, Data mining techniques and applications. Science Press: Beijing, 2006, pp. 111-188-236-238.
[15]
B. Li, J. Salter, and A.G. Dempster, "Indoor positioning techniques based on wireless LAN", IEEE Inter. Conf. Lan. 2007, pp. 13-16.
[16]
C. Zhang, "Research on application of decision tree algorithm in performance analysis in colleges", Comput. Programm. Skills Mainten., vol. 12, pp. 112-113, 2009.
[17]
Z. Wu, R. Cai, and S. Xu, "Research and improvement of Wi-Fi positioning based on K-nearest neighbor method", Comput. Eng., vol. 43, no. 3, pp. 289-293, 2017.
[18]
F. Yang, "Zhao.D.WiFi positioning based on the Android platform", Dianzi Celiang Jishu, vol. 35, no. 9, pp. 116-119, 2012.
[19]
S. Chandra, and A.K. Bharti, "Speed distribution curves for pedestrians during walking and crossing", Procedia Soc. Behav. Sci., vol. 104, pp. 660-667, 2013.
[http://dx.doi.org/10.1016/j.sbspro.2013.11.160]