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k- Nearest Neighbor Algorithm For Improving Accuracy In Clutter Based Location Estimation Of Wireless Nodes

This research is focusing on the precise location estimation of mobile node by using k - nearest neighbor algorithm (k-NN). It is based on our previous research findings in which we divided the geographical area into thirteen clutters/terrains based on the behavior of radio waves. We calculated the...

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Main Authors:	Muhammad Mansoor Alam, Mazliham Mohd Su'ud, Patrice Boursier, Shahrulniza Musa
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Published:	University Malaya 2013
Subjects:	k-NN Available Signal Strength, Receive Signal Strength, Location Estimation Triangulation Clutters/terrains CERT
Online Access:	http://mjcs.fsktm.um.edu.my/document.aspx?FileName=1086.pdf http://ir.unikl.edu.my/jspui/handle/123456789/2130
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spelling	my.unikl.ir-21302013-05-14T10:34:55Z k- Nearest Neighbor Algorithm For Improving Accuracy In Clutter Based Location Estimation Of Wireless Nodes Muhammad Mansoor Alam Mazliham Mohd Su'ud Patrice Boursier Shahrulniza Musa k-NN Available Signal Strength, Receive Signal Strength, Location Estimation Triangulation Clutters/terrains CERT This research is focusing on the precise location estimation of mobile node by using k - nearest neighbor algorithm (k-NN). It is based on our previous research findings in which we divided the geographical area into thirteen clutters/terrains based on the behavior of radio waves. We calculated the point-to-point distance from the antennas to mobile node by using receive signal strength and available signal strength information. A C# prototype was developed by using WiFi (IEEE 802.11 b/g standard) to record data points in different clutters at every 2 meter distance. We derived Clutter based Enhanced Error Rate Table (CERT) for precision. Although CERT minimizes errors due to the atmospheric considerations but in highly attenuated clutters the error rate was still high. The k-NN algorithm is used to minimize the error ranging from 1-3 meters to 0.4- 1.2 meter only, depending on the clutter we are dealing with. Current research is divided into three steps. First we calculate the P2P distance in all different clutters by using available signal strength and receive signal strength at five different time intervals (t0 – t4). In step 2 we construct three triangles at random by using the data gathered in step 1 and calculate mean value of predicted locations. Finally based on locations calculated in step 2 we apply the k-NN algorithm to minimize error in the estimated location. Results show that the k-NN can produce from 217% - 289% better results compare to the famous triangulation method. The purpose of this research is to reduce errors in order to achieve estimated position near to accurate. 2013-05-14T10:34:55Z 2013-05-14T10:34:55Z 2011 Vol.24,No.3,p146-159 http://mjcs.fsktm.um.edu.my/document.aspx?FileName=1086.pdf http://ir.unikl.edu.my/jspui/handle/123456789/2130 Malaysian Journal of Computer Science; University Malaya
institution	Universiti Kuala Lumpur
building	UniKL Library
collection	Institutional Repository
continent	Asia
country	Malaysia
content_provider	Universiti Kuala Lumpur
content_source	UniKL Institutional Repository
url_provider	http://ir.unikl.edu.my/
topic	k-NN Available Signal Strength, Receive Signal Strength, Location Estimation Triangulation Clutters/terrains CERT
spellingShingle	k-NN Available Signal Strength, Receive Signal Strength, Location Estimation Triangulation Clutters/terrains CERT Muhammad Mansoor Alam Mazliham Mohd Su'ud Patrice Boursier Shahrulniza Musa k- Nearest Neighbor Algorithm For Improving Accuracy In Clutter Based Location Estimation Of Wireless Nodes
description	This research is focusing on the precise location estimation of mobile node by using k - nearest neighbor algorithm (k-NN). It is based on our previous research findings in which we divided the geographical area into thirteen clutters/terrains based on the behavior of radio waves. We calculated the point-to-point distance from the antennas to mobile node by using receive signal strength and available signal strength information. A C# prototype was developed by using WiFi (IEEE 802.11 b/g standard) to record data points in different clutters at every 2 meter distance. We derived Clutter based Enhanced Error Rate Table (CERT) for precision. Although CERT minimizes errors due to the atmospheric considerations but in highly attenuated clutters the error rate was still high. The k-NN algorithm is used to minimize the error ranging from 1-3 meters to 0.4- 1.2 meter only, depending on the clutter we are dealing with. Current research is divided into three steps. First we calculate the P2P distance in all different clutters by using available signal strength and receive signal strength at five different time intervals (t0 – t4). In step 2 we construct three triangles at random by using the data gathered in step 1 and calculate mean value of predicted locations. Finally based on locations calculated in step 2 we apply the k-NN algorithm to minimize error in the estimated location. Results show that the k-NN can produce from 217% - 289% better results compare to the famous triangulation method. The purpose of this research is to reduce errors in order to achieve estimated position near to accurate.
format
author	Muhammad Mansoor Alam Mazliham Mohd Su'ud Patrice Boursier Shahrulniza Musa
author_facet	Muhammad Mansoor Alam Mazliham Mohd Su'ud Patrice Boursier Shahrulniza Musa
author_sort	Muhammad Mansoor Alam
title	k- Nearest Neighbor Algorithm For Improving Accuracy In Clutter Based Location Estimation Of Wireless Nodes
title_short	k- Nearest Neighbor Algorithm For Improving Accuracy In Clutter Based Location Estimation Of Wireless Nodes
title_full	k- Nearest Neighbor Algorithm For Improving Accuracy In Clutter Based Location Estimation Of Wireless Nodes
title_fullStr	k- Nearest Neighbor Algorithm For Improving Accuracy In Clutter Based Location Estimation Of Wireless Nodes
title_full_unstemmed	k- Nearest Neighbor Algorithm For Improving Accuracy In Clutter Based Location Estimation Of Wireless Nodes
title_sort	k- nearest neighbor algorithm for improving accuracy in clutter based location estimation of wireless nodes
publisher	University Malaya
publishDate	2013
url	http://mjcs.fsktm.um.edu.my/document.aspx?FileName=1086.pdf http://ir.unikl.edu.my/jspui/handle/123456789/2130
_version_	1644484628699938816
score	13.222552

k- Nearest Neighbor Algorithm For Improving Accuracy In Clutter Based Location Estimation Of Wireless Nodes

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