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TACO: A Traceback Algorithm Based on Ant Colony Optimization for Geomagnetic Positioning

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Advances in Wireless Sensor Networks (CWSN 2014)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 501))

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Abstract

Magnetic field fluctuations in modern buildings can derive from both natural and man-made sources, which typically include steel, reinforced concrete structures, and electric power systems, etc. Since the anomalies of the magnetic field inside the building are nearly static and have sufficient local variability, this provides a unique magnetic clue which could be utilized for global self-localization. In this research, we propose TACO, an algorithm that uses Ant Colony Optimization (ACO) and Multi-Position TraceBack Algorithm (MTA) to solve one dimensional magnetic data localization problem. TACO employs a set of novel techniques to resolve ambiguity in locations: ACO is used to generate candidate locations and MTA to make full use of both historical positions and users moving direction information. The evaluation results show that TACO could achieve high localization accuracy, when appropriate previous position information is provided.

This work was supported in part by the National Natural Science Foundation of China (61374214), the Major Projects of Ministry of Industry and Information Technology (2014ZX03006003-002), the National High Technology Research and Development Program of China (2013AA12A201) and Taiyuan-Zhongguancun Cooperation special Project (130104).

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Author information

Authors and Affiliations

  1. Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China

    Hui Li & Haiyong Luo

  2. Beijing University of Posts and Telecommunications, Beijing, China

    Fang Zhao

  3. University of North Texas, Denton, USA

    Xinrong Li

Authors
  1. Hui Li
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  2. Haiyong Luo
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  3. Fang Zhao
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  4. Xinrong Li
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Corresponding author

Correspondence to Hui Li .

Editor information

Editors and Affiliations

  1. Chinese Academy of Sciences, Beijing, China

    Limin Sun

  2. Beijing, China

    Huadong Ma

  3. Northwest University, Xi’an, China

    Dingyi Fang

  4. Northwest University, Xi’an, China

    Jinping Niu

  5. Northwest University, Xi’an, China

    Wei Wang

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© 2015 Springer-Verlag Berlin Heidelberg

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Li, H., Luo, H., Zhao, F., Li, X. (2015). TACO: A Traceback Algorithm Based on Ant Colony Optimization for Geomagnetic Positioning. In: Sun, L., Ma, H., Fang, D., Niu, J., Wang, W. (eds) Advances in Wireless Sensor Networks. CWSN 2014. Communications in Computer and Information Science, vol 501. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-46981-1_20

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  • DOI: https://doi.org/10.1007/978-3-662-46981-1_20

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-662-46980-4

  • Online ISBN: 978-3-662-46981-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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