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Subspace Extension Algorithm for Joint DOA and DOD Estimation in Bistatic MIMO Radar

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Artificial Intelligence and Security (ICAIS 2019)

Part of the book series: Lecture Notes in Computer Science ((LNSC,volume 11634))

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Abstract

A subspace extension algorithm for joint direction of departure (DOD) and direction of arrival (DOA) estimation in bistatic multiple-input multiple-output (MIMO) radar is proposed. A two-level nested array is employed as receive array. The signal subspace can be got by eigenvalue decomposition (EVD) of covariance matrix. Then the signal subspace can be extended without additional EVD, and the DOD and DOA can be estimated by ESPRIT algorithm. Because of subspace extension, the proposed algorithm has higher precision than the traditional ESPRIT algorithm. Numerical simulations demonstrate the performance of the proposed design technology.

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Acknowledgments

This work was supported by the Cooperation Agreement Project by the Department of Science and Technology of Guizhou Province of China (LH [2017]7320, LH [2017]7321), the Foundation of Top-notch Talents by Education Department of Guizhou Province of China (KY [2018]075), the Innovation Group Major Research Program Funded by Guizhou Provincial Education Department (KY [2016]051) and PhD Research Startup Foundation of Tongren University (trxyDH1710).

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Authors and Affiliations

  1. Tongren University, Tongren, 554300, China

    Sheng Liu, Jing Zhao & Wei Li

Authors
  1. Sheng Liu
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  2. Jing Zhao
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  3. Wei Li
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Corresponding author

Correspondence to Sheng Liu .

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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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Liu, S., Zhao, J., Li, W. (2019). Subspace Extension Algorithm for Joint DOA and DOD Estimation in Bistatic MIMO Radar. In: Sun, X., Pan, Z., Bertino, E. (eds) Artificial Intelligence and Security. ICAIS 2019. Lecture Notes in Computer Science(), vol 11634. Springer, Cham. https://doi.org/10.1007/978-3-030-24271-8_22

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  • DOI: https://doi.org/10.1007/978-3-030-24271-8_22

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-24270-1

  • Online ISBN: 978-3-030-24271-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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