Joint 2D-DOD, 2D-DOA, and Polarization Angles Estimation for Bistatic EMVS-MIMO Radar via PARAFAC Analysis

被引:157
作者
Wen, Fangqing [1 ,2 ]
Shi, Junpeng [3 ]
Zhang, Zijing [4 ]
机构
[1] Yangtze Univ, Sch Elect & Informat, Jingzhou 434023, Peoples R China
[2] Hainan Univ, State Key Lab Marine Resource Utilizat South Chin, Haikou 570228, Hainan, Peoples R China
[3] Natl Univ Def Technol, Hefei 230037, Peoples R China
[4] Xidian Univ, Natl Lab Radar Signal Proc, Xian 710071, Peoples R China
基金
中国国家自然科学基金;
关键词
Tensile stress; Two dimensional displays; Matrix decomposition; MIMO radar; Estimation; MIMO communication; Physical layer; wireless communication; MIMO system; electromagnetic vector sensors; parallel factor analysis; OF-ARRIVAL ESTIMATION; DOA ESTIMATION; VECTOR-SENSOR; ESTIMATION ACCURACY; SUBSPACE ESTIMATION; MASSIVE MIMO; DIRECTION; DECOMPOSITION; LOCALIZATION; DEPARTURE;
D O I
10.1109/TVT.2019.2957511
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Multiple-input multiple-output (MIMO) is a technical hotspot in physical layer with numerous applications in wireless communications, radars, sonars, and well beyond. In this paper, we focus on the multi-dimensional angle estimation problem in a bistatic electromagnetic vector sensors (EMVS) MIMO system. Namely, we need to simultaneously estimate two-dimensional (2D) direction-of-arrival (DOA), 2D direction-of-departure (DOD), 2D receive polarization angle (RPA) and 2D transmit polarization angle (TPA). To tackle this issue, a parallel factor (PARAFAC) analysis-based estimator is proposed. Firstly, a third-order PARAFAC analysis data model is established, which can efficiently exploit the tensor structure of the array measurement. After performing PARAFAC decomposition on the tensor measurement, the factor matrices are achieved. By combining the estimation method of signal parameters via rotational invariance technique (ESPRIT) with the vector cross-product method, joint estimates of 2D-DOD, 2D-DOA, 2D-TPA and 2D-RPA are obtained without further pairing calculation. Compared with the state-of-the-art ESPRIT-Like approach, the proposed method can achieve better performance by enforcing the third-order structure information, and it is suitable for arbitrary array manifolds. Theoretical analyses are given and numerical results corroborate our analysis.
引用
收藏
页码:1626 / 1638
页数:13
相关论文
共 46 条
[1]   DOA estimation for coprime EMVS arrays via minimum distance criterion based on PARAFAC analysis [J].
Ahmed, Tanveer ;
Zhang Xiaofei ;
Zheng Wang .
IET RADAR SONAR AND NAVIGATION, 2019, 13 (01) :65-73
[2]   What Will 5G Be? [J].
Andrews, Jeffrey G. ;
Buzzi, Stefano ;
Choi, Wan ;
Hanly, Stephen V. ;
Lozano, Angel ;
Soong, Anthony C. K. ;
Zhang, Jianzhong Charlie .
IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS, 2014, 32 (06) :1065-1082
[3]  
[Anonymous], 1999, P INT WORKSH ICA BSS
[4]   Target detection and localization using. MIMO radars and sonars [J].
Bekkerman, Ilya ;
Tabrikian, Joseph .
IEEE TRANSACTIONS ON SIGNAL PROCESSING, 2006, 54 (10) :3873-3883
[5]   Polynomial root finding technique for joint DOA DOD estimation in bistatic MIMO radar [J].
Bencheikh, Mohamed Laid ;
Wang, Yide ;
He, Hongyang .
SIGNAL PROCESSING, 2010, 90 (09) :2723-2730
[6]   Multi-dimensional model order selection [J].
Carvalho Lustosa da Costa, Joao Paulo ;
Roemer, Florian ;
Haardt, Martin ;
de Sousa, Rafael Timoteo, Jr. .
EURASIP JOURNAL ON ADVANCES IN SIGNAL PROCESSING, 2011,
[7]   A low-complexity joint 2D-DOD and 2D-DOA estimation algorithm for MIMO radar with arbitrary arrays [J].
Chen, Chen ;
Zhang, Xiaofei .
INTERNATIONAL JOURNAL OF ELECTRONICS, 2013, 100 (10) :1455-1469
[8]   Average-entropy variation in iterative decoding of turbo codes and its application [J].
Chen, J. Y. ;
Zhang, L. ;
Qin, J. .
ELECTRONICS LETTERS, 2008, 44 (22) :1314-U32
[9]   Multi-SVD based subspace estimation to improve angle estimation accuracy in bistatic MIMO radar [J].
Cheng, Yuanbing ;
Yu, Rusheng ;
Gu, Hong ;
Su, Weimin .
SIGNAL PROCESSING, 2013, 93 (07) :2003-2009
[10]   2D-DOD and 2D-DOA estimation using the electromagnetic vector sensors [J].
Chintagunta, Srinivasarao ;
Ponnusamy, Palanisamy .
SIGNAL PROCESSING, 2018, 147 :163-172