Constrained tensor decomposition for 2D DOA estimation in transmit beamspace MIMO radar with subarrays

Feng Xu; Sergiy A. Vorobyov

doi:10.1109/ICASSP39728.2021.9413987

Constrained tensor decomposition for 2D DOA estimation in transmit beamspace MIMO radar with subarrays

Feng Xu, Sergiy A. Vorobyov

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Scientific › peer-review

1 Citation (Scopus)

Abstract

In this paper, a constrained tensor decomposition method that enables two dimensional (2D) direction of arrival (DOA) estimation for transmit beamspace (TB) Multiple-Input Multiple-Output (MIMO) radar with subarrays is proposed. Specifically, a higher-order tensor model is designed to collect the received signal for TB MIMO radar with multiple subarrays. By exploiting the inner structure of the factor matrix, the constrained tensor decomposition is conducted, and subsequently the target DOA is estimated. In addition, the angular information can also be computed by solving the minimization problem that originates from the second factor matrix to improve the robustness of the 2D DOA estimation. Simulation results validate the proposed approach.

Original language	English
Title of host publication	ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
Publisher	IEEE
Pages	4380-4384
Number of pages	5
Volume	2021-June
ISBN (Electronic)	978-1-7281-7605-5
DOIs	https://doi.org/10.1109/ICASSP39728.2021.9413987
Publication status	Published - 2021
MoE publication type	A4 Article in a conference publication
Event	IEEE International Conference on Acoustics, Speech, and Signal Processing - Virtua, Online, Toronto, Canada Duration: 6 Jun 2021 → 11 Jun 2021

Publication series

Name	IEEE International Conference on Acoustics, Speech and Signal Processing
ISSN (Print)	1520-6149
ISSN (Electronic)	2379-190X

Conference

Conference	IEEE International Conference on Acoustics, Speech, and Signal Processing
Abbreviated title	ICASSP
Country/Territory	Canada
City	Toronto
Period	06/06/2021 → 11/06/2021

Keywords

Constrained tensor decomposition
Direction of arrival estimation
MIMO radar with subarrays

Access to Document

10.1109/ICASSP39728.2021.9413987

Cite this

Xu, F., & Vorobyov, S. A. (2021). Constrained tensor decomposition for 2D DOA estimation in transmit beamspace MIMO radar with subarrays. In ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) (Vol. 2021-June, pp. 4380-4384). (IEEE International Conference on Acoustics, Speech and Signal Processing ). IEEE. https://doi.org/10.1109/ICASSP39728.2021.9413987

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title = "Constrained tensor decomposition for 2D DOA estimation in transmit beamspace MIMO radar with subarrays",

abstract = "In this paper, a constrained tensor decomposition method that enables two dimensional (2D) direction of arrival (DOA) estimation for transmit beamspace (TB) Multiple-Input Multiple-Output (MIMO) radar with subarrays is proposed. Specifically, a higher-order tensor model is designed to collect the received signal for TB MIMO radar with multiple subarrays. By exploiting the inner structure of the factor matrix, the constrained tensor decomposition is conducted, and subsequently the target DOA is estimated. In addition, the angular information can also be computed by solving the minimization problem that originates from the second factor matrix to improve the robustness of the 2D DOA estimation. Simulation results validate the proposed approach.",

keywords = "Constrained tensor decomposition, Direction of arrival estimation, MIMO radar with subarrays",

author = "Feng Xu and Vorobyov, {Sergiy A.}",

note = "Funding Information: This work was supported by Academy of Finland (Grant: No. 299243), and by the China Scholarship Council. Publisher Copyright: {\textcopyright} 2021 IEEE; IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP ; Conference date: 06-06-2021 Through 11-06-2021",

year = "2021",

doi = "10.1109/ICASSP39728.2021.9413987",

language = "English",

volume = "2021-June",

series = "IEEE International Conference on Acoustics, Speech and Signal Processing ",

publisher = "IEEE",

pages = "4380--4384",

booktitle = "ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)",

address = "United States",

}

Xu, F & Vorobyov, SA 2021, Constrained tensor decomposition for 2D DOA estimation in transmit beamspace MIMO radar with subarrays. in ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). vol. 2021-June, IEEE International Conference on Acoustics, Speech and Signal Processing , IEEE, pp. 4380-4384, IEEE International Conference on Acoustics, Speech, and Signal Processing, Toronto, Ontario, Canada, 06/06/2021. https://doi.org/10.1109/ICASSP39728.2021.9413987

Constrained tensor decomposition for 2D DOA estimation in transmit beamspace MIMO radar with subarrays. / Xu, Feng; Vorobyov, Sergiy A.

ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). Vol. 2021-June IEEE, 2021. p. 4380-4384 (IEEE International Conference on Acoustics, Speech and Signal Processing ).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Scientific › peer-review

TY - GEN

T1 - Constrained tensor decomposition for 2D DOA estimation in transmit beamspace MIMO radar with subarrays

AU - Xu, Feng

AU - Vorobyov, Sergiy A.

PY - 2021

Y1 - 2021

N2 - In this paper, a constrained tensor decomposition method that enables two dimensional (2D) direction of arrival (DOA) estimation for transmit beamspace (TB) Multiple-Input Multiple-Output (MIMO) radar with subarrays is proposed. Specifically, a higher-order tensor model is designed to collect the received signal for TB MIMO radar with multiple subarrays. By exploiting the inner structure of the factor matrix, the constrained tensor decomposition is conducted, and subsequently the target DOA is estimated. In addition, the angular information can also be computed by solving the minimization problem that originates from the second factor matrix to improve the robustness of the 2D DOA estimation. Simulation results validate the proposed approach.

AB - In this paper, a constrained tensor decomposition method that enables two dimensional (2D) direction of arrival (DOA) estimation for transmit beamspace (TB) Multiple-Input Multiple-Output (MIMO) radar with subarrays is proposed. Specifically, a higher-order tensor model is designed to collect the received signal for TB MIMO radar with multiple subarrays. By exploiting the inner structure of the factor matrix, the constrained tensor decomposition is conducted, and subsequently the target DOA is estimated. In addition, the angular information can also be computed by solving the minimization problem that originates from the second factor matrix to improve the robustness of the 2D DOA estimation. Simulation results validate the proposed approach.

KW - Constrained tensor decomposition

KW - Direction of arrival estimation

KW - MIMO radar with subarrays

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DO - 10.1109/ICASSP39728.2021.9413987

M3 - Conference contribution

AN - SCOPUS:85101859342

VL - 2021-June

T3 - IEEE International Conference on Acoustics, Speech and Signal Processing

SP - 4380

EP - 4384

BT - ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

PB - IEEE

T2 - IEEE International Conference on Acoustics, Speech, and Signal Processing

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Xu F, Vorobyov SA. Constrained tensor decomposition for 2D DOA estimation in transmit beamspace MIMO radar with subarrays. In ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). Vol. 2021-June. IEEE. 2021. p. 4380-4384. (IEEE International Conference on Acoustics, Speech and Signal Processing ). https://doi.org/10.1109/ICASSP39728.2021.9413987

Constrained tensor decomposition for 2D DOA estimation in transmit beamspace MIMO radar with subarrays

Abstract

Publication series

Conference

Keywords

Access to Document

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Transmit beamspace for active compressive sensing and communication with multiple waveforms

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Constrained tensor decomposition for 2D DOA estimation in transmit beamspace MIMO radar with subarrays

Abstract

Publication series

Conference

Keywords

Access to Document

Other files and links

Fingerprint

Projects

Transmit beamspace for active compressive sensing and communication with multiple waveforms

Cite this