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Direction finding in MIMO radar with large antenna arrays and nonorthogonal waveforms

DIGITAL SIGNAL PROCESSING 2019年 94卷 75-83页

作者： Wen, Fangqing Mao, Chenxing Zhang, Gong Yangtze Univ Elect & Informat Sch Jingzhou 434023 Peoples R China Hainan Univ State Key Lab Marine Resource Utilizat South Chin Haikou 570228 Hainan Peoples R China Nanjing Univ Aeronaut & Astronaut Key Lab Radar Imaging & Microwave Photon Nanjing 210016 Jiangsu Peoples R China

As an important research branch in multiple-input multiple-output (MIMO) radar, orthogonal waveforms are always desirable. In practice, however, the orthogonality may not be always guaranteed. In this paper, a computationally efficient parallel factor (PARAFAC) estimator is proposed, which is suitable for direction-of-arrival (DOA) estimation in colocated MIMO radar with large antenna arrays as well as nonorthogonal waveforms. Firstly, the spatially colored noise caused by the nonorthogonal waveforms is eliminated via temporal cross-correlation of the measurement. Thereafter, a third-order PARAFAC (or called trilinear decomposition) model is established by exploiting the multidimensional structure as well as the low rank property of the cross covariance matrix. The DOA estimation problem is then linked to PARAFAC decomposition and finally obtained via least squares technique. Compared with the existing matrix completion-based algorithm, the proposed estimator is attractive from the perspective of computational complexity and estimation accuracy, especially with large antenna arrays scenario. In addition, the stochastic Cramer-Rao bound on DOA estimation with waveform imperfectly is derived. Numerical simulations are provided to verify the effectiveness of the proposed estimator. (C) 2019 Elsevier Inc. All rights reserved.

关键词： Direction-of-arrival estimation multiple-input multiple-output radar Nonorthogonal waveform Parallel factor analysis

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MIMO radar with widely separated antennas

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IEEE SIGNAL PROCESSING MAGAZINE 2008年第1期25卷 116-129页

作者： Haimovich, Alexander M. Blum, Rick S. Cimini, Leonard J., Jr. Lehigh Univ ECE Dept Bethlehem PA USA

MIMO (multiple-input multiple-output) radar refers to an architecture that employs multiple, spatially distributed transmitters and receivers. While, in a general sense, MIMO radar can be viewed as a type of multistatic radar, the separate nomenclature suggests unique features that set MIMO radar apart from the multistatic radar literature and that have a close relation to MIMO communications. This article reviews some recent work on MIMO radar with widely separated antennas. Widely separated transmit/receive antennas capture the spatial diversity of the target's radar cross section (RCS). Unique features of MIMO radar are explained and illustrated by examples. It is shown that with noncoherent processing, a target's RCS spatial variations can be exploited to obtain a diversity gain for target detection and for estimation of various parameters, such as angle of arrival and Doppler. For target location, it is shown that coherent processing can provide a resolution far exceeding that supported by the radar's waveform.

关键词： MIMO communication diversity reception radar antennas radar cross-sections radar receivers radar transmitters MIMO communications MIMO radar RCS multiple-input multiple-output radar multistatic radar radar cross section radar target detect radar antennas MIMO communication radar receivers multiple input multiple output systems reactor cooling system radar cross section multistatic radar MIMO radar radar transmitters diversity reception

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Efficient Solutions for MIMO radar Localization Under Unknown Transmitter Positions and Offsets

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IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS 2022年第1期21卷 505-518页

作者： Wu, Xiaoping Liu, Yupeng Zhu, Xuefeng Mo, Lufeng Huzhou Univ Sch Informat Engn Huzhou 313000 Peoples R China Zhejiang A&F Univ Informat & Educ Technol Ctr Hangzhou 311300 Peoples R China

Two efficient solutions are proposed for the localization problem of an object in multiple-input multiple-output (MIMO) radar systems, when the transmitter positions and offsets are unknown. The localization problem is first recast into a convex form by applying the semidefinite relaxation (SDR) technique, the solution of which converges to global optimum. We also propose a closed-form solution warranting global convergence, in which the object position is estimated by two stages. In the stage-one solution, the auxiliary variables are introduced to transform the nonlinear problem into a linear form. The stage-two solution is further designed to refine the estimates obtained from the stage-one solution. The minimum number of receivers and the complexity are also analyzed for the proposed solutions. The simulated results show that the SDR and closed-form solutions provide good estimates for the object position and transmitter positions. Their performance can sufficiently approach the Cramer-Rao Lower Bound (CRLB) accuracy at the high signal-to-noise ratio (SNR).

关键词： Location awareness Receivers MIMO radar Clocks Wireless communication Transmitters Closed-form solutions Localization multiple-input multiple-output radar semidefinite relaxation closed-form solution time delay

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Orthogonal Waveform With multiple Diversities for MIMO radar

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IEEE SENSORS JOURNAL 2018年第11期18卷 4462-4476页

作者： Chang, Guanghong Liu, Aijun Yu, Changjun Ji, Yonggang Wang, Yiming Zhang, Jie Harbin Inst Technol Sch Elect & Informat Engn Harbin 150001 Heilongjiang Peoples R China Harbin Inst Technol Weihai Sch Informat & Elect Engn Weihai 264209 Peoples R China State Ocean Adm Lab Marine Phys & Remote Sensing Inst Oceanog 1 Qingdao 266061 Peoples R China

For multiple-inputmultiple-output radar employing the advantage of virtual array, the general assumption of the perfect orthogonality between multiple waveforms is proved to be unachievable. Therefore, to achieve good orthogonality, transmission schemes employing frequency diversity or chirp modulation diversity have been extensively investigated. Inspired by the idea of "diversity means superiority," approach which integrates multiple diversities in a single waveform might be used to improve the orthogonality. In this paper, a novel waveform named discrete frequency and chirp-rate coding waveform (DFCCW) consisting of both frequency and chirp modulation diversities is proposed. Based on the auto-and cross-ambiguity functions of the DFCCW, we prove that the proposed approach is able to decrease the cross ambiguity peak values. To generate and optimize a set of Pareto-optimal DFCCWs, a many-objective optimization algorithm named nondominated sorting genetic algorithm with differential evolution is presented. Besides, the optimal criteria considering Doppler effects ensure that the DFCCW possess good performance in presence of moving targets. Numerical results show that the DFCCW achieves better orthogonality than the waveforms that utilize only single diversity type.

关键词： multiple-input multiple-output radar orthogonal waveform frequency diversity chirp modulation diversity many-objective optimization algorithm

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Transmit beamspace-based DOD and DOA estimation method for bistatic MIMO radar

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SIGNAL PROCESSING 2019年 157卷 88-96页

作者： Xu, Baoqing Zhao, Yongbo Xidian Univ Natl Lab Radar Signal Proc Xian 710071 Shaanxi Peoples R China Xidian Univ Collaborat Innovat Ctr Informat Sensing & Underst Xian 710071 Shaanxi Peoples R China

In this paper, we propose a novel angle estimation method in bistatic multiple-input multiple-output (MIMO) radar, which combines the transmit beamspace (TB) technique with the unitary ESPRIT (U-ESPRIT) model. The TB matrix is designed to focus the transmitted energy within the desired spatial sector, thus achieving the transmit coherent gain. Due to the special data structure of the TB-based bistatic MIMO radar, a corresponding method is proposed to construct the real-valued model. Unfortunately, the existed interpolation error inevitably degrades the direction-of-departure (DOD) estimation performance. To compensate the DOD estimation error, a look-up table is created, which establishes a one-to-one mapping relationship for DOD. The Cramer-Rao bound (CRB) on angle estimation in TB-based bistatic MIMO radar is also derived for performance analysis. Compared with existing methods, the proposed algorithm has better estimation performance due to the improved signal-to-noise ratio (SNR) gain and requires less computational complexity. Numerical simulations are presented to demonstrate the estimation performance of the proposed algorithm. (C) 2018 Elsevier B.V. All rights reserved.

关键词： multiple-input multiple-output radar Angle estimation Transmit beamspace design DOD estimation error compensation

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Tensor-based real-valued subspace approach for angle estimation in bistatic MIMO radar with unknown mutual coupling

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SIGNAL PROCESSING 2015年 116卷 152-158页

作者： Wang, Xianpeng Wang, Wei Liu, Jing Liu, Qi Wang, Ben Harbin Engn Univ Coll Automat Harbin 150001 Peoples R China

In this paper, a tensor-based real-valued subspace approach for joint direction of departure (DOD) and direction of arrival (DOA) estimation in bistatic MIMO radar with unknown mutual coupling is proposed. Exploiting the inherent multidimensional structure of received data after matched filtering, a third-order measurement tensor signal model is formulated. For eliminating the effect of the unknown mutual coupling, a sub-tensor can be extracted from the third-order measurement tensor by taking advantage of the banded symmetric Toeplitz structure of the mutual coupling matrix (MCM). Then the sub-tensor can be turned into a real-valued one by forward-backward averaging and unitary transformation, and a real-valued signal subspace is constructed to estimate the DOD and DOA by the higher-order singular value decomposition (HOSVD). Owing to utilize the multidimensional structure of received data and forward-backward averaging technique, the proposed method has better angle estimation performance than MUSIC-Like and ESPRIT-Like algorithms. Furthermore, the proposed method is suitable for coherent targets. Simulation results verify the effectiveness and advantage of the proposed method. (C) 2015 Elsevier B.V. All rights reserved.

关键词： multiple-input multiple-output radar Angle estimation Real-valued signal subspace Higher-order singular value decomposition Mutual coupling

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Transmit beampattern synthesis for MIMO radar using extended circulating code

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IET radar SONAR AND NAVIGATION 2018年第6期12卷 610-616页

作者： Li, Shengyuan Liu, Nan Zhang, Linrang Zhang, Juan Tang, Shiyang Huang, Xiang Xidian Univ Natl Lab Radar Signal Proc Xian 710071 Shaanxi Peoples R China

In multiple-input multiple-output (MIMO) radar settings, it is often desired to transmit power only to a given location or sets of locations defined by the beampattern. Some previous works achieve transmit beampattern synthesis by developing new MIMO radar architectures. In these radar architectures, orthogonal waveforms must be utilised. In fact, the perfect orthogonal waveforms are hardly achievable so that the radar performance loss is inevitable. On the other hand, some waveform design methods, which show superior performance, are proposed. However, the modulus variation and high computational complexity impede their applications in reality. In this study, a simple method for transmit beampattern synthesis is proposed. Based on the circulating code principle, the beampattern synthesis problem has been simplified as a single waveform spectral shaping issue. To solve the spectral shaping issue, an extended circulating code (ECC) with constant modulus is provided. The proposed ECC can achieve an arbitrary beampattern with a single constant modulus waveform while the computational complexity is relatively low. Due to these properties, ECC is simple to apply in practice. The method is evaluated by simulated data and the results can verify its effectiveness.

关键词： MIMO radar radar signal processing signal synthesis codes computational complexity radar antennas transmitting antennas waveform analysis antenna arrays transmit beampattern synthesis extended circulating code multiple-input multiple-output radar MIMO radar architectures orthogonal waveforms radar performance loss waveform design methods computational complexity single waveform spectral shaping ECC single constant modulus waveform modulus variation transmit antenna array

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Combined root-MUSIC algorithms for multi-carrier MIMO radar with sparse uniform linear arrays

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IET radar SONAR AND NAVIGATION 2019年第1期13卷 89-97页

作者： Liu, Aihua Zhang, Xin Yang, Qiang Wu, XiaoChuan Deng, Weibo Harbin Inst Technol Sch Elect & Informat Engn Harbin 150000 Heilongjiang Peoples R China Harbin Inst Technol Collaborat Innovat Ctr Informat Sensing & Underst Harbin 150000 Heilongjiang Peoples R China

In this study, sparse uniform linear arrays are used to improve the direction-of-arrival (DOA) estimation accuracy for the multiple-input multiple-output radar. With a suitable choice of multi-carrier frequencies, the DOA estimation ambiguity problem caused by spatial under-sampling can be resolved. Two kinds of search-free DOA estimation algorithms based on root-multiple signal classification (MUSIC) are proposed. The first algorithm directly applies the root-MUSIC to each carrier frequency separately for the true DOAs as well as their spurious DOAs, then, a novel DOA replicas matching algorithm is proposed to obtain the true DOAs from the ambiguous ones. The second algorithm utilises the manifold separation technique (MST) to align the noise subspaces of all multi-carrier frequencies. Using the MST, the separable representation of the array manifold vector of each carrier frequency is obtained, then the root-MUSIC polynomials of all multi-carrier frequencies are combined to construct a new polynomial, the true DOAs can be obtained directly by applying polynomial rooting without any matching processing. The two proposed algorithms are both practical, computationally efficient and robust. Numerical simulations verify the effectiveness of the proposed algorithms in terms of root-mean-squared error.

关键词： signal classification direction-of-arrival estimation polynomials array signal processing MIMO radar spurious DOAs novel DOA manifold separation technique multicarrier frequencies array manifold vector carrier frequency root-MUSIC polynomials polynomial rooting root-mean-squared error combined root-MUSIC algorithms multicarrier MIMO radar sparse uniform linear arrays direction-of-arrival estimation accuracy multiple-input multiple-output radar DOA estimation ambiguity problem search-free DOA estimation algorithms root-multiple signal classification

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Adaptive weight matrix design and parameter estimation via sparse modeling for MIMO radar

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SIGNAL PROCESSING 2017年 139卷 1-11页

作者： Gong, Pengcheng Wang, Wen-Qin Wan, Xianrong Hubei Univ Technol Sch Elect & Elect Engn Wuhan 430068 Hubei Peoples R China Univ Elect Sci & Technol China Sch Commun & Informat Engn Chengdu 611731 Sichuan Peoples R China Wuhan Univ Sch Elect Informat Wuhan 430072 Hubei Peoples R China

Although sparse representation and sparse recovery algorithms for colocated multiple-input multiple output (MIMO) radar have received much attention, incoherence of the sensing matrix received few discussions. In this paper, we propose adaptive weight matrix design and parameter estimation via sparse modeling to improve the recovery performance for MIMO radar. First, a sparse framework is formulated for the MIMO array with decoupled transmit weight matrix and steering matrix. Next, a two stage method is proposed to optimize the two matrices to improve the DOA estimation performance. Finally, a sparse recovery approach based on l(q) (0 < q <= 1) norm optimization is developed to estimate the unknown target parameters. Furthermore, the algorithm can be iteratively implemented with the obtained closed-form solution for the optimization problem. The angle-amplitude estimation performance is examined by analyzing the Cramer-Rao lower bound (CRLB). Numerical results demonstrate that significant performance improvement has been achieved by the proposed sensing matrix optimization and adaptive weight matrix design approach. (C) 2017 Elsevier B.V. All rights reserved.

关键词： Direction of arrival estimation multiple-input multiple-output radar Compressed sensing Sensing matrix Sparse representation

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Covariance vector sparsity-aware DOA estimation for monostatic MIMO radar with unknown mutual coupling

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SIGNAL PROCESSING 2016年 119卷 21-27页

作者： Liu, Jing Wang, Xianpeng Zhou, Weidong Harbin Engn Univ Coll Automat Harbin 150001 Peoples R China

In this paper, a covariance vector sparsity-aware DOA estimation method is proposed for monostatic multiple-input multiple-output (MIMO) radar with unknown mutual coupling. The new method firstly utilizes the banded symmetric Toeplitz structure of the mutual coupling matrix (MCM) in both of the transmit and receive arrays to eliminate the unknown mutual coupling. Then a sparse representation framework of the array covariance vector is formulated for obtaining the coarse DOA estimation. Finally, a refined maximum likelihood estimation procedure is introduced to estimate the DOA based on the recovered result. Compared with conventional algorithms, the proposed method provides higher angular resolution and better angle estimation performance. Furthermore, the computational complexity of the proposed method is reasonable, because it only involves single measurement vector (SMV) problem and does not require a dense discretized sampling grid for the recovered procedure. Simulation results are used to verify the effectiveness and advantages of the proposed method. (C) 2015 Elsevier B.V. All rights reserved.

关键词： multiple-input multiple-output radar Direction of arrival estimation Sparse representation Mutual coupling

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