The conventional Received Signal Strength (RSS) based positioning algorithms such as Least Square (LS) and Weighted LS (WLS) produce significant estimation errors when the anchor nodes positions approach a collinear scenario. In this paper, we propose the CAP (Collinear Anchor aided Positioning) algorithm to provide robust positioning performance under ill-conditioned matrix conditions, whilst contributing toward overall low computational complexity. The CAP algorithm outperforms traditional approaches such as the maximum likelihood algorithm, LS and WLS among others.
| Published in | International Journal of Wireless Communications and Mobile Computing (Volume 2, Issue 1) |
| DOI | 10.11648/j.wcmc.20140201.13 |
| Page(s) | 18-22 |
| 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), 2014. Published by Science Publishing Group |
Ill-Conditioned, Collinear Anchors, Unbiased Estimate, CRLB
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APA Style
Senka Hadzic, Du Yang, Manuel Violas, Jonathan Rodriguez. (2014). RSS-based Near-Collinear Anchor aided Positioning Algorithm for Ill-conditioned Scenario. International Journal of Wireless Communications and Mobile Computing, 2(1), 18-22. https://doi.org/10.11648/j.wcmc.20140201.13
ACS Style
Senka Hadzic; Du Yang; Manuel Violas; Jonathan Rodriguez. RSS-based Near-Collinear Anchor aided Positioning Algorithm for Ill-conditioned Scenario. Int. J. Wirel. Commun. Mobile Comput. 2014, 2(1), 18-22. doi: 10.11648/j.wcmc.20140201.13
AMA Style
Senka Hadzic, Du Yang, Manuel Violas, Jonathan Rodriguez. RSS-based Near-Collinear Anchor aided Positioning Algorithm for Ill-conditioned Scenario. Int J Wirel Commun Mobile Comput. 2014;2(1):18-22. doi: 10.11648/j.wcmc.20140201.13
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Download@article{10.11648/j.wcmc.20140201.13,
author = {Senka Hadzic and Du Yang and Manuel Violas and Jonathan Rodriguez},
title = {RSS-based Near-Collinear Anchor aided Positioning Algorithm for Ill-conditioned Scenario},
journal = {International Journal of Wireless Communications and Mobile Computing},
volume = {2},
number = {1},
pages = {18-22},
doi = {10.11648/j.wcmc.20140201.13},
url = {https://doi.org/10.11648/j.wcmc.20140201.13},
eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.wcmc.20140201.13},
abstract = {The conventional Received Signal Strength (RSS) based positioning algorithms such as Least Square (LS) and Weighted LS (WLS) produce significant estimation errors when the anchor nodes positions approach a collinear scenario. In this paper, we propose the CAP (Collinear Anchor aided Positioning) algorithm to provide robust positioning performance under ill-conditioned matrix conditions, whilst contributing toward overall low computational complexity. The CAP algorithm outperforms traditional approaches such as the maximum likelihood algorithm, LS and WLS among others.},
year = {2014}
}
TY - JOUR T1 - RSS-based Near-Collinear Anchor aided Positioning Algorithm for Ill-conditioned Scenario AU - Senka Hadzic AU - Du Yang AU - Manuel Violas AU - Jonathan Rodriguez Y1 - 2014/02/20 PY - 2014 N1 - https://doi.org/10.11648/j.wcmc.20140201.13 DO - 10.11648/j.wcmc.20140201.13 T2 - International Journal of Wireless Communications and Mobile Computing JF - International Journal of Wireless Communications and Mobile Computing JO - International Journal of Wireless Communications and Mobile Computing SP - 18 EP - 22 PB - Science Publishing Group SN - 2330-1015 UR - https://doi.org/10.11648/j.wcmc.20140201.13 AB - The conventional Received Signal Strength (RSS) based positioning algorithms such as Least Square (LS) and Weighted LS (WLS) produce significant estimation errors when the anchor nodes positions approach a collinear scenario. In this paper, we propose the CAP (Collinear Anchor aided Positioning) algorithm to provide robust positioning performance under ill-conditioned matrix conditions, whilst contributing toward overall low computational complexity. The CAP algorithm outperforms traditional approaches such as the maximum likelihood algorithm, LS and WLS among others. VL - 2 IS - 1 ER -
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