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Cellular Iterative Position Method with Gaussian Noise

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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

On the assumption that the errors obey same gaussian noise for every sensor in the base station network, maximum likelihood estimation iterative algorithm is presented for localizing a target using angle of arrival measurements. It is shown that the RMSs and means of error between maximum likelihood estimation iterative algorithm is much less than that of least squares estimation algorithm by simulation experiments.

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References

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Author information

Authors and Affiliations

  1. College of Marine, Northwestern Polytechnical University, Xi’an, 710072, China

    Qinli An & Jianfeng Chen

  2. College of Science, Air Force Engineering University, Xi’an, 710051, China

    Qinli An & Zhonghai Yin

Authors
  1. Qinli An
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  2. Jianfeng Chen
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  3. Zhonghai Yin
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Corresponding author

Correspondence to Qinli An .

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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Cite this paper

An, Q., Chen, J., Yin, Z. (2015). Cellular Iterative Position Method with Gaussian Noise. 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_13

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  • DOI: https://doi.org/10.1007/978-3-662-46981-1_13

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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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