Tensor-based angle estimation approach for strictly noncircular sources with unknown mutual coupling in bistatic MIMO radar

In the paper, the estimation of joint direction-of-departure (DOD) and direction-of-arrival (DOA) for strictly noncircular targets in multiple-input multiple-output (MIMO) radar with unknown mutual coupling is considered, and a tensor-based angle estimation method is proposed. In the proposed method...

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Main Authors: Guo, Yuehao, Wang, Xianpeng, Wang, Wensi, Huang, Mengxing, Shen, Chong, Cao, Chunjie, Bi, Guoan
Other Authors: School of Electrical and Electronic Engineering
Format: Article
Language:English
Published: 2018
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Online Access:https://hdl.handle.net/10356/88967
http://hdl.handle.net/10220/46016
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-889672020-03-07T13:57:27Z Tensor-based angle estimation approach for strictly noncircular sources with unknown mutual coupling in bistatic MIMO radar Guo, Yuehao Wang, Xianpeng Wang, Wensi Huang, Mengxing Shen, Chong Cao, Chunjie Bi, Guoan School of Electrical and Electronic Engineering DRNTU::Engineering::Electrical and electronic engineering Bistatic MIMO Radar Angle Estimation In the paper, the estimation of joint direction-of-departure (DOD) and direction-of-arrival (DOA) for strictly noncircular targets in multiple-input multiple-output (MIMO) radar with unknown mutual coupling is considered, and a tensor-based angle estimation method is proposed. In the proposed method, making use of the banded symmetric Toeplitz structure of the mutual coupling matrix, the influence of the unknown mutual coupling is removed in the tensor domain. Then, a special enhancement tensor is formulated to capture both the noncircularity and inherent multidimensional structure of strictly noncircular signals. After that, the higher-order singular value decomposition (HOSVD) technology is applied for estimating the tensor-based signal subspace. Finally, the direction-of-departure (DOD) and direction-of-arrival (DOA) estimation is obtained by utilizing the rotational invariance technique. Due to the use of both noncircularity and multidimensional structure of the detected signal, the algorithm in this paper has better angle estimation performance than other subspace-based algorithms. The experiment results verify that the method proposed has better angle estimation performance. Published version 2018-09-18T02:01:32Z 2019-12-06T17:14:49Z 2018-09-18T02:01:32Z 2019-12-06T17:14:49Z 2018 Journal Article Guo, Y., Wang, X., Wang, W., Huang, M., Shen, C., Cao, C., & Bi, G. (2018). Tensor-based angle estimation approach for strictly noncircular sources with unknown mutual coupling in bistatic MIMO radar. Sensors, 18(9), 2788-. doi:10.3390/s18092788 1424-8220 https://hdl.handle.net/10356/88967 http://hdl.handle.net/10220/46016 10.3390/s18092788 en Sensors © 2018 by The Author(s). Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). 14 p. application/pdf
institution Nanyang Technological University
building NTU Library
country Singapore
collection DR-NTU
language English
topic DRNTU::Engineering::Electrical and electronic engineering
Bistatic MIMO Radar
Angle Estimation
spellingShingle DRNTU::Engineering::Electrical and electronic engineering
Bistatic MIMO Radar
Angle Estimation
Guo, Yuehao
Wang, Xianpeng
Wang, Wensi
Huang, Mengxing
Shen, Chong
Cao, Chunjie
Bi, Guoan
Tensor-based angle estimation approach for strictly noncircular sources with unknown mutual coupling in bistatic MIMO radar
description In the paper, the estimation of joint direction-of-departure (DOD) and direction-of-arrival (DOA) for strictly noncircular targets in multiple-input multiple-output (MIMO) radar with unknown mutual coupling is considered, and a tensor-based angle estimation method is proposed. In the proposed method, making use of the banded symmetric Toeplitz structure of the mutual coupling matrix, the influence of the unknown mutual coupling is removed in the tensor domain. Then, a special enhancement tensor is formulated to capture both the noncircularity and inherent multidimensional structure of strictly noncircular signals. After that, the higher-order singular value decomposition (HOSVD) technology is applied for estimating the tensor-based signal subspace. Finally, the direction-of-departure (DOD) and direction-of-arrival (DOA) estimation is obtained by utilizing the rotational invariance technique. Due to the use of both noncircularity and multidimensional structure of the detected signal, the algorithm in this paper has better angle estimation performance than other subspace-based algorithms. The experiment results verify that the method proposed has better angle estimation performance.
author2 School of Electrical and Electronic Engineering
author_facet School of Electrical and Electronic Engineering
Guo, Yuehao
Wang, Xianpeng
Wang, Wensi
Huang, Mengxing
Shen, Chong
Cao, Chunjie
Bi, Guoan
format Article
author Guo, Yuehao
Wang, Xianpeng
Wang, Wensi
Huang, Mengxing
Shen, Chong
Cao, Chunjie
Bi, Guoan
author_sort Guo, Yuehao
title Tensor-based angle estimation approach for strictly noncircular sources with unknown mutual coupling in bistatic MIMO radar
title_short Tensor-based angle estimation approach for strictly noncircular sources with unknown mutual coupling in bistatic MIMO radar
title_full Tensor-based angle estimation approach for strictly noncircular sources with unknown mutual coupling in bistatic MIMO radar
title_fullStr Tensor-based angle estimation approach for strictly noncircular sources with unknown mutual coupling in bistatic MIMO radar
title_full_unstemmed Tensor-based angle estimation approach for strictly noncircular sources with unknown mutual coupling in bistatic MIMO radar
title_sort tensor-based angle estimation approach for strictly noncircular sources with unknown mutual coupling in bistatic mimo radar
publishDate 2018
url https://hdl.handle.net/10356/88967
http://hdl.handle.net/10220/46016
_version_ 1681047946828709888