Robust Angle Estimation for MIMO Radar with the Coexistence of Mutual Coupling and Colored Noise
This paper deals with joint estimation of direction-of-departure (DOD) and direction-of- arrival (DOA) in bistatic multiple-input multiple-output (MIMO) radar with the coexistence of unknown mutual coupling and spatial colored noise by developing a novel robust covariance tensor-based angle estimati...
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doaj-9074532ffa9d424ea38a4288de01676a2020-11-24T21:49:58ZengMDPI AGSensors1424-82202018-03-0118383210.3390/s18030832s18030832Robust Angle Estimation for MIMO Radar with the Coexistence of Mutual Coupling and Colored NoiseJunxiang Wang0Xianpeng Wang1Dingjie Xu2Guoan Bi3College of Automation, Harbin Engineering University, Harbin 150001, ChinaState Key Laboratory of Marine Resource Utilization in South China Sea, Hainan University, Haikou 570228, ChinaCollege of Electical Engineering and Automation , Harbin Institute of Technology University, Harbin 150001, ChinaSchool of Electrical and Electronic Engineering, Nanyang Technological University, Singapore 639798, SingaporeThis paper deals with joint estimation of direction-of-departure (DOD) and direction-of- arrival (DOA) in bistatic multiple-input multiple-output (MIMO) radar with the coexistence of unknown mutual coupling and spatial colored noise by developing a novel robust covariance tensor-based angle estimation method. In the proposed method, a third-order tensor is firstly formulated for capturing the multidimensional nature of the received data. Then taking advantage of the temporal uncorrelated characteristic of colored noise and the banded complex symmetric Toeplitz structure of the mutual coupling matrices, a novel fourth-order covariance tensor is constructed for eliminating the influence of both spatial colored noise and mutual coupling. After a robust signal subspace estimation is obtained by using the higher-order singular value decomposition (HOSVD) technique, the rotational invariance technique is applied to achieve the DODs and DOAs. Compared with the existing HOSVD-based subspace methods, the proposed method can provide superior angle estimation performance and automatically jointly perform the DODs and DOAs. Results from numerical experiments are presented to verify the effectiveness of the proposed method.http://www.mdpi.com/1424-8220/18/3/832MIMO radarangle estimationmutual couplingspatial colored noiseHOSVD |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Junxiang Wang Xianpeng Wang Dingjie Xu Guoan Bi |
spellingShingle |
Junxiang Wang Xianpeng Wang Dingjie Xu Guoan Bi Robust Angle Estimation for MIMO Radar with the Coexistence of Mutual Coupling and Colored Noise Sensors MIMO radar angle estimation mutual coupling spatial colored noise HOSVD |
author_facet |
Junxiang Wang Xianpeng Wang Dingjie Xu Guoan Bi |
author_sort |
Junxiang Wang |
title |
Robust Angle Estimation for MIMO Radar with the Coexistence of Mutual Coupling and Colored Noise |
title_short |
Robust Angle Estimation for MIMO Radar with the Coexistence of Mutual Coupling and Colored Noise |
title_full |
Robust Angle Estimation for MIMO Radar with the Coexistence of Mutual Coupling and Colored Noise |
title_fullStr |
Robust Angle Estimation for MIMO Radar with the Coexistence of Mutual Coupling and Colored Noise |
title_full_unstemmed |
Robust Angle Estimation for MIMO Radar with the Coexistence of Mutual Coupling and Colored Noise |
title_sort |
robust angle estimation for mimo radar with the coexistence of mutual coupling and colored noise |
publisher |
MDPI AG |
series |
Sensors |
issn |
1424-8220 |
publishDate |
2018-03-01 |
description |
This paper deals with joint estimation of direction-of-departure (DOD) and direction-of- arrival (DOA) in bistatic multiple-input multiple-output (MIMO) radar with the coexistence of unknown mutual coupling and spatial colored noise by developing a novel robust covariance tensor-based angle estimation method. In the proposed method, a third-order tensor is firstly formulated for capturing the multidimensional nature of the received data. Then taking advantage of the temporal uncorrelated characteristic of colored noise and the banded complex symmetric Toeplitz structure of the mutual coupling matrices, a novel fourth-order covariance tensor is constructed for eliminating the influence of both spatial colored noise and mutual coupling. After a robust signal subspace estimation is obtained by using the higher-order singular value decomposition (HOSVD) technique, the rotational invariance technique is applied to achieve the DODs and DOAs. Compared with the existing HOSVD-based subspace methods, the proposed method can provide superior angle estimation performance and automatically jointly perform the DODs and DOAs. Results from numerical experiments are presented to verify the effectiveness of the proposed method. |
topic |
MIMO radar angle estimation mutual coupling spatial colored noise HOSVD |
url |
http://www.mdpi.com/1424-8220/18/3/832 |
work_keys_str_mv |
AT junxiangwang robustangleestimationformimoradarwiththecoexistenceofmutualcouplingandcolorednoise AT xianpengwang robustangleestimationformimoradarwiththecoexistenceofmutualcouplingandcolorednoise AT dingjiexu robustangleestimationformimoradarwiththecoexistenceofmutualcouplingandcolorednoise AT guoanbi robustangleestimationformimoradarwiththecoexistenceofmutualcouplingandcolorednoise |
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1725886083829334016 |