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A linear regression based cost function for WSN localization

Frank Vanheel (UGent) , Jo Verhaevert (UGent) , Eric Laermans (UGent) , Ingrid Moerman (UGent) and Piet Demeester (UGent)
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Organization
Abstract
Localization with Wireless Sensor Networks (WSN) creates new opportunities for location-based consumer communication applications. There is a great need for cost functions of maximum likelihood localization algorithms that are not only accurate but also lack local minima. In this paper we present Linear Regression based Cost Function for Localization (LiReCoFuL), a new cost function based on regression tools that fulfills these requirements. With empirical test results on a real-life test bed, we show that our cost function outperforms the accuracy of a minimum mean square error cost function. Furthermore we show that LiReCoFuL is as accurate as relative location estimation error cost functions and has very few local extremes.
Keywords
regression analysis, maximum likelihood estimation, sensor placement, wireless sensor networks

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Please use this url to cite or link to this publication:

MLA
Vanheel, Frank, et al. “A Linear Regression Based Cost Function for WSN Localization.” 2011 19th International Conference on Software, Telecommunications and Computer Networks (SoftCOM 2011), IEEE, 2011.
APA
Vanheel, F., Verhaevert, J., Laermans, E., Moerman, I., & Demeester, P. (2011). A linear regression based cost function for WSN localization. In 2011 19th International conference on software, telecommunications and computer networks (SoftCOM 2011). Piscataway, NJ, USA: IEEE.
Chicago author-date
Vanheel, Frank, Jo Verhaevert, Eric Laermans, Ingrid Moerman, and Piet Demeester. 2011. “A Linear Regression Based Cost Function for WSN Localization.” In 2011 19th International Conference on Software, Telecommunications and Computer Networks (SoftCOM 2011). Piscataway, NJ, USA: IEEE.
Chicago author-date (all authors)
Vanheel, Frank, Jo Verhaevert, Eric Laermans, Ingrid Moerman, and Piet Demeester. 2011. “A Linear Regression Based Cost Function for WSN Localization.” In 2011 19th International Conference on Software, Telecommunications and Computer Networks (SoftCOM 2011). Piscataway, NJ, USA: IEEE.
Vancouver
1.
Vanheel F, Verhaevert J, Laermans E, Moerman I, Demeester P. A linear regression based cost function for WSN localization. In: 2011 19th International conference on software, telecommunications and computer networks (SoftCOM 2011). Piscataway, NJ, USA: IEEE; 2011.
IEEE
[1]
F. Vanheel, J. Verhaevert, E. Laermans, I. Moerman, and P. Demeester, “A linear regression based cost function for WSN localization,” in 2011 19th International conference on software, telecommunications and computer networks (SoftCOM 2011), Split, Croatia, 2011.
@inproceedings{2065068,
  abstract     = {{Localization with Wireless Sensor Networks (WSN) creates new opportunities for location-based consumer communication applications. There is a great need for cost functions of maximum likelihood localization algorithms that are not only accurate but also lack local minima. In this paper we present Linear Regression based Cost Function for Localization (LiReCoFuL), a new cost function based on regression tools that fulfills these requirements. With empirical test results on a real-life test bed, we show that our cost function outperforms the accuracy of a minimum mean square error cost function. Furthermore we show that LiReCoFuL is as accurate as relative location estimation error cost functions and has very few local extremes.}},
  author       = {{Vanheel, Frank and Verhaevert, Jo and Laermans, Eric and Moerman, Ingrid and Demeester, Piet}},
  booktitle    = {{2011 19th International conference on software, telecommunications and computer networks (SoftCOM 2011)}},
  isbn         = {{9781457714399}},
  keywords     = {{regression analysis,maximum likelihood estimation,sensor placement,wireless sensor networks}},
  language     = {{eng}},
  location     = {{Split, Croatia}},
  pages        = {{5}},
  publisher    = {{IEEE}},
  title        = {{A linear regression based cost function for WSN localization}},
  year         = {{2011}},
}

Web of Science
Times cited: