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International Conference on Artificial Intelligence and Security

ICAIS 2019: Artificial Intelligence and Security pp 488–497Cite as

Taylor Series Localization Algorithm Based on Semi-definite Programming

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Part of the book series: Lecture Notes in Computer Science ((LNSC,volume 11635))

Abstract

In order to improve the positioning accuracy of time difference of arrival, a Taylor series algorithm based on semi-definite programming is proposed in this paper. Firstly, base on the squared distance difference model, a semi-positive programming method is used to obtain the coarse location of the target node. Then, based on the distance difference model, the location of the target node is formulated as a linear least square problem by Taylor series expansion. Finally, the refined location is obtained by iteration. simulation results show that when the target node locates in the inner area surrounded by anchor nodes, the estimated values obtained by Taylor series algorithm are more concentrated and the center is more closer to the actual location of the target node than that obtained by semi-definite programming algorithm, and the superiority of Taylor series algorithm will be more obvious when the target node is far away from the center of the inner area.

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Authors and Affiliations

  1. Institute of Information Technology, Taizhou Polytechnic College, Taizhou, Jiangsu, China

    Jianfeng Lu & Xuanyuan Yang

Authors
  1. Jianfeng Lu
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  2. Xuanyuan Yang
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Corresponding author

Correspondence to Jianfeng Lu .

Editor information

Editors and Affiliations

  1. Nanjing University of Information Science and Technology, Nanjing, China

    Xingming Sun

  2. Nanjing University of Information Science and Technology, Nanjing, China

    Zhaoqing Pan

  3. Purdue University, West Lafayette, IN, USA

    Elisa Bertino

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Lu, J., Yang, X. (2019). Taylor Series Localization Algorithm Based on Semi-definite Programming. In: Sun, X., Pan, Z., Bertino, E. (eds) Artificial Intelligence and Security. ICAIS 2019. Lecture Notes in Computer Science(), vol 11635. Springer, Cham. https://doi.org/10.1007/978-3-030-24268-8_45

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  • DOI: https://doi.org/10.1007/978-3-030-24268-8_45

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-24267-1

  • Online ISBN: 978-3-030-24268-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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