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...
| Main Authors: | , , , , , , |
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| Other Authors: | |
| Format: | Journal Article |
| Language: | English |
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2018
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| Online Access: | https://hdl.handle.net/10356/88967 http://hdl.handle.net/10220/46016 |
| _version_ | 1824453912009113600 |
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| author | Guo, Yuehao Wang, Xianpeng Wang, Wensi Huang, Mengxing Shen, Chong Cao, Chunjie Bi, Guoan |
| 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 |
| author_sort | Guo, Yuehao |
| collection | NTU |
| 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. |
| first_indexed | 2025-02-19T03:13:57Z |
| format | Journal Article |
| id | ntu-10356/88967 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2025-02-19T03:13:57Z |
| publishDate | 2018 |
| record_format | dspace |
| spelling | ntu-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 |
| 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 |
| title | 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_short | 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 |
| topic | DRNTU::Engineering::Electrical and electronic engineering Bistatic MIMO Radar Angle Estimation |
| url | https://hdl.handle.net/10356/88967 http://hdl.handle.net/10220/46016 |
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