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Near-Field Source Localization by Exploiting the Signal Sparsity

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Communications and Networking (ChinaCom 2019)

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Abstract

This work aims to study the source localization problem using a symmetric array in a near-field environment. To reduce the computational complexity, in this work, two spatial correlation signals are created in which each signal only depends on one parameter of direction of arrival (DOA) or range. In the development process, the each resulting signal still possesses the array spatial structure, and therefore, the atomic norm minimization is utilized to obtain the corresponding solutions. The utilization of atomic norm also allows one to avoid the off-grid problem when the sparse reconstruction concept is employed. The numerical studies demonstrate the proposed method provides a superior performance compared with other approaches.

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Acknowledgment

This work was jointly supported by the National Natural Science Foundation of China under Grants 61501072 and 61801066.

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Authors and Affiliations

  1. School of Communication and Information Engineering, Chongqing University of Posts and Telecommunications, Chongqing, China

    Huan Meng & Yi Zhou

  2. Chongqing Key Lab of Mobile Communications Technology, Chongqing University of Posts and Telecommunications, Chongqing, China

    Hongqing Liu & Zhen Luo

Authors
  1. Huan Meng
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  2. Hongqing Liu
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  3. Yi Zhou
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  4. Zhen Luo
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Corresponding author

Correspondence to Huan Meng .

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Editors and Affiliations

  1. Shanghai University, Shanghai, China

    Honghao Gao

  2. School of Computer Software, Tianjin University, Tianjin, China

    Zhiyong Feng

  3. Hangzhou Dianzi University, Hangzhou, China

    Jun Yu

  4. Tongji University, Shanghai Shi, China

    Jun Wu

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© 2020 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

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Meng, H., Liu, H., Zhou, Y., Luo, Z. (2020). Near-Field Source Localization by Exploiting the Signal Sparsity. In: Gao, H., Feng, Z., Yu, J., Wu, J. (eds) Communications and Networking. ChinaCom 2019. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 313. Springer, Cham. https://doi.org/10.1007/978-3-030-41117-6_2

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  • DOI: https://doi.org/10.1007/978-3-030-41117-6_2

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-41116-9

  • Online ISBN: 978-3-030-41117-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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