2D-DOD and 2D-DOA Estimation for a Mixture of Circular and Strictly Noncircular Sources Based on L-Shaped MIMO Radar
In this paper, a joint diagonalization based two dimensional (2D) direction of departure (DOD) and 2D direction of arrival (DOA) estimation method for a mixture of circular and strictly noncircular (NC) sources is proposed based on an L-shaped bistatic multiple input multiple output (MIMO) radar. By...
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MDPI AG
2020-04-01
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| Series: | Sensors |
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| Online Access: | https://www.mdpi.com/1424-8220/20/8/2177 |
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| author | Jiaxiong Fang Yonghong Liu Yifang Jiang Yang Lu Zehao Zhang Hua Chen Laihua Wang |
| author_facet | Jiaxiong Fang Yonghong Liu Yifang Jiang Yang Lu Zehao Zhang Hua Chen Laihua Wang |
| author_sort | Jiaxiong Fang |
| collection | DOAJ |
| description | In this paper, a joint diagonalization based two dimensional (2D) direction of departure (DOD) and 2D direction of arrival (DOA) estimation method for a mixture of circular and strictly noncircular (NC) sources is proposed based on an L-shaped bistatic multiple input multiple output (MIMO) radar. By making full use of the L-shaped MIMO array structure to obtain an extended virtual array at the receive array, we first combine the received data vector and its conjugated counterpart to construct a new data vector, and then an estimating signal parameter via rotational invariance techniques (ESPRIT)-like method is adopted to estimate the DODs and DOAs by joint diagonalization of the NC-based direction matrices, which can automatically pair the four dimensional (4D) angle parameters and solve the angle ambiguity problem with common one-dimensional (1D) DODs and DOAs. In addition, the asymptotic performance of the proposed algorithm is analyzed and the closed-form stochastic Cramer–Rao bound (CRB) expression is derived. As demonstrated by simulation results, the proposed algorithm has outperformed the existing one, with a result close to the theoretical benchmark. |
| first_indexed | 2024-03-10T20:30:45Z |
| format | Article |
| id | doaj.art-2dcb5b6906424ce6903e5d9b78e1c02d |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-03-10T20:30:45Z |
| publishDate | 2020-04-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-2dcb5b6906424ce6903e5d9b78e1c02d2023-11-19T21:24:36ZengMDPI AGSensors1424-82202020-04-01208217710.3390/s200821772D-DOD and 2D-DOA Estimation for a Mixture of Circular and Strictly Noncircular Sources Based on L-Shaped MIMO RadarJiaxiong Fang0Yonghong Liu1Yifang Jiang2Yang Lu3Zehao Zhang4Hua Chen5Laihua Wang6School of Faculty of Information Science and Engineering, Ningbo University, Ningbo 315211, ChinaSchool of Faculty of Information Science and Engineering, Ningbo University, Ningbo 315211, ChinaSchool of Faculty of Information Science and Engineering, Ningbo University, Ningbo 315211, ChinaSchool of Faculty of Information Science and Engineering, Ningbo University, Ningbo 315211, ChinaSchool of Faculty of Information Science and Engineering, Ningbo University, Ningbo 315211, ChinaSchool of Faculty of Information Science and Engineering, Ningbo University, Ningbo 315211, ChinaSchool of Software, Qufu Normal University, Qufu 273165, ChinaIn this paper, a joint diagonalization based two dimensional (2D) direction of departure (DOD) and 2D direction of arrival (DOA) estimation method for a mixture of circular and strictly noncircular (NC) sources is proposed based on an L-shaped bistatic multiple input multiple output (MIMO) radar. By making full use of the L-shaped MIMO array structure to obtain an extended virtual array at the receive array, we first combine the received data vector and its conjugated counterpart to construct a new data vector, and then an estimating signal parameter via rotational invariance techniques (ESPRIT)-like method is adopted to estimate the DODs and DOAs by joint diagonalization of the NC-based direction matrices, which can automatically pair the four dimensional (4D) angle parameters and solve the angle ambiguity problem with common one-dimensional (1D) DODs and DOAs. In addition, the asymptotic performance of the proposed algorithm is analyzed and the closed-form stochastic Cramer–Rao bound (CRB) expression is derived. As demonstrated by simulation results, the proposed algorithm has outperformed the existing one, with a result close to the theoretical benchmark.https://www.mdpi.com/1424-8220/20/8/2177MIMO radarfour dimensional (4D) angle estimationnoncircular signaljoint diagonalizationstochastic Cramer–Rao bound (CRB) |
| spellingShingle | Jiaxiong Fang Yonghong Liu Yifang Jiang Yang Lu Zehao Zhang Hua Chen Laihua Wang 2D-DOD and 2D-DOA Estimation for a Mixture of Circular and Strictly Noncircular Sources Based on L-Shaped MIMO Radar Sensors MIMO radar four dimensional (4D) angle estimation noncircular signal joint diagonalization stochastic Cramer–Rao bound (CRB) |
| title | 2D-DOD and 2D-DOA Estimation for a Mixture of Circular and Strictly Noncircular Sources Based on L-Shaped MIMO Radar |
| title_full | 2D-DOD and 2D-DOA Estimation for a Mixture of Circular and Strictly Noncircular Sources Based on L-Shaped MIMO Radar |
| title_fullStr | 2D-DOD and 2D-DOA Estimation for a Mixture of Circular and Strictly Noncircular Sources Based on L-Shaped MIMO Radar |
| title_full_unstemmed | 2D-DOD and 2D-DOA Estimation for a Mixture of Circular and Strictly Noncircular Sources Based on L-Shaped MIMO Radar |
| title_short | 2D-DOD and 2D-DOA Estimation for a Mixture of Circular and Strictly Noncircular Sources Based on L-Shaped MIMO Radar |
| title_sort | 2d dod and 2d doa estimation for a mixture of circular and strictly noncircular sources based on l shaped mimo radar |
| topic | MIMO radar four dimensional (4D) angle estimation noncircular signal joint diagonalization stochastic Cramer–Rao bound (CRB) |
| url | https://www.mdpi.com/1424-8220/20/8/2177 |
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