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Adaptive RLS-Received Signal Strength Algorithm in Wireless Network Area for Multi-Mobile Nodes Location Estimation System

by Abhishek Singh, Rajesh Mehra
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 64 - Number 15
Year of Publication: 2013
Authors: Abhishek Singh, Rajesh Mehra
10.5120/10709-5671

Abhishek Singh, Rajesh Mehra . Adaptive RLS-Received Signal Strength Algorithm in Wireless Network Area for Multi-Mobile Nodes Location Estimation System. International Journal of Computer Applications. 64, 15 ( February 2013), 12-15. DOI=10.5120/10709-5671

@article{ 10.5120/10709-5671,
author = { Abhishek Singh, Rajesh Mehra },
title = { Adaptive RLS-Received Signal Strength Algorithm in Wireless Network Area for Multi-Mobile Nodes Location Estimation System },
journal = { International Journal of Computer Applications },
issue_date = { February 2013 },
volume = { 64 },
number = { 15 },
month = { February },
year = { 2013 },
issn = { 0975-8887 },
pages = { 12-15 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume64/number15/10709-5671/ },
doi = { 10.5120/10709-5671 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:16:31.448846+05:30
%A Abhishek Singh
%A Rajesh Mehra
%T Adaptive RLS-Received Signal Strength Algorithm in Wireless Network Area for Multi-Mobile Nodes Location Estimation System
%J International Journal of Computer Applications
%@ 0975-8887
%V 64
%N 15
%P 12-15
%D 2013
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Recently, the current Received Signal Strength based positioning systems have been designed to monitor the location information of mobile nodes and Patients. The positioning systems are designed with different wireless communication technologies and adapted algorithms in wireless network area. The adaptive algorithms improve the accuracy of location of mobile nodes in RSS (Received Signal Strength) based positioning systems. The proposed work introduced adaptive Recursive Least Square - Received Signal Strength (RLS-RSS algorithm) algorithm to reduce the effect of multipath propagation in Trilateration Localization system. In the proposed work the entire three reference node receives the RSS-values from the multi-mobile nodes and then RLS-RSS algorithm is used to estimate the RSS-values at each reference node. The estimated RSS-value provides the coordinates of multi-mobile nodes. From the simulation results it is shown that the accuracy of the coordinate's point of the multi-mobile nodes is improved for different environments.

References
  1. Nicolas L. D. , Florian Gain, Per Zetterberg, "Wi-Fi Fingerprint Indoor Positioning System Using Probability Distribution Comparison", IEEE International Conference on Acoustics, Speech and Signal Processing, IEEE, March 2012, pp. 2301-2304.
  2. Ryan J. R. Thompson, Ediz Cetin, and Andrew G. Dempster, "Unknown Source Localization Using RSS in Open Areas in The Presence of Ground Reflections", IEEE conference on Position Location and Navigation Symposium (PLANS), IEEE, April 2012, pp. 1018-1027.
  3. HongyuShi, "A New Weighted Centroid Locali- zation Algorithm based on RSSI", IEEE International Conference on Information and Automation, IEEE, June 2012, pp. 137-141.
  4. Shrestha S. , Laitinen E. , Talvitie J. , Lohan E. S. , "RSSI Channel Effects in Cellular and WLAN Positioning", Workshop on Positioning Navigation and Communication (WPNC), IEEE, March 2012, pp. 187-192.
  5. Gansemer S. , Grossmann U. , Hakobyan S. , "RSSI-Based Euclidean Distance Algorithm for Indoor Positioning Adapted For The Use in Dynamically Changing WLAN Environments and Multi-Level Buildings", International Conference on Indoor Positioning and Indoor Navigation (IPIN), IEEE, Sept. 2010, pp. 1-6.
  6. Jiannan Tian, Zhan Xu, "RSSI Localization Algorithm Based on RBF Neural Network", IEEE international conference on software engineering and service science (ICSESS), IEEE, June 2012, pp. 321-324.
  7. Zhiqiang Kan, Li Tan, Chongchong Yu, Zijun Wu, "Research and Implementation of Intelligent Mobile Phone Location Based on RSSI in Smart Space", International Conference on Systems and Informatics (ICSAI), IEEE, May 2012, pp. 1635-1639.
  8. Yuhong L. , Yaokuan Wang, "A Position System of Multi-APs Based on RSSI", International conference on Consumer Electronics, Communications and Networks (CECNet), IEEE, April 2012, pp. 1565-1568.
  9. Peisen Zhao, Chunxiao Jiang, Chen H. , Yong Ren, "Probabilistic Neural Network for RSS-Based Collaborative Localization", IEEE Vehicular Technology Conference (VTC Spring), IEEE, May 2012, pp. 1-5.
  10. E. E. L. Lau, B. G. Lee, S. C. Lee, W Y Chung, "Enhanced RSSI-Based High Accuracy Real-Time User Location Tracking System For Indoor and Outdoor Environments", International Journal On Smart Sensing And Intelligent Systems, vol. 1, no. 2, pp. 534-548.
  11. Hyo-Sung Ahn, Wonpil Yu, "Environmental-Adaptive RSSI-Based Indoor Localization", IEEE Transactions on Automation Science and Engineering, IEEE, Oct. 2009, vol. 6, no. 4, pp. 626-633.
  12. Xin Xiao, Xiaojun Jing, Siqing You, Jian Zeng, "An environmental-adaptive RSSI based indoor positioning approach using RFID", International Conference on Advanced Intelligence and Awareness Internet, IEEE, 23-25 Oct. 2010, pp. 127-130
Index Terms

Computer Science
Information Sciences

Keywords

Trilateration Localization System Recursive Least Square Adaptive Filtering Received Signal Strength (RSS)

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