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multiple-input-multiple-output radar superresolution three-dimensional imaging based on multidimensional smoothed L0

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JOURNAL OF APPLIED REMOTE SENSING 2016年第3期10卷

作者： Hu, Xiaowei Tong, Ningning Wang, Heming Wang, Yuchen Air Force Engn Univ Air & Missile Def Coll Changledong St Xian 710051 Peoples R China

By exploiting the sparsity of radar target image, it is hopeful to obtain a high-resolution target image in multiple-input-multiple-output (MIMO) radar via a sparse representation (SR) method. However, for the three-dimensional (3-D) imaging, the conventional SR method has to convert the 3-D problem into the one-dimensional (1-D) problem. Thus, it will inevitably impose a heavy burden on the storage and computation. A multidimensional smoothed L0 (MD-SL0) algorithm is proposed based on the conventional smoothed L0 algorithm. The proposed MD-SL0 can directly apply to the multidimensional SR problem without transforming to the 1-D case. As a result, a MIMO radar 3-D imaging method via MD-SL0 is achieved with high computation efficiency and low storage burden. Finally, the effectiveness of the method is validated by the results of comparative experiments. (C) 2016 Society of Photo-Optical Instrumentation Engineers (SPIE)

关键词： multiple-input-multiple-output radar three-dimensional imaging multidimensional smoothed L0

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Robust adaptive beamforming against large DOA mismatch with linear phase and magnitude constraints for multiple-input-multiple-output radar

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IET SIGNAL PROCESSING 2016年第9期10卷 1062-1072页

作者： Yu, Hongbo Feng, Dazheng Yao, Xiaokun Xidian Univ Natl Lab Radar Signal Proc Xian 710071 Peoples R China Beijing Inst Radio Metrol & Measurement Atom Frequency Stand Lab Beijing 100039 Peoples R China

In this study, a robust adaptive beamformer against large direction-of-arrival (DOA) mismatch for multiple-input-multiple-output radar is proposed with linear phase and magnitude constraints on main lobe. First, the full-dimensional weight vector (WV) is expressed as the Kronecker product of the transmit and receive array WVs based on the WV separable principle. For the transmit array WV, the authors find an interesting property that the Fourier spectrum of its conjugate inverse arrangement is equal to its array response function within a phase factor. This property also exists in the receive array WV. Using this property, the phase response of the transmit and receive array, respectively, is set to be linear based on designing a finite impulse response filter. Then, a bi-quadratic cost function with respect to the transmit and receive WVs is established by only constraining the real magnitude response and it is effectively solved by the bi-iterative algorithm. The proposed beamformer has lower computational complexity and faster sample convergence rate, compared with the traditional magnitude response constraints beamformers with full degrees of freedom. Moreover, it can provide good robustness against large DOA mismatch. Numerical experiments are provided to demonstrate the effectiveness of the proposal.

关键词： MIMO radar radar signal processing array signal processing vectors Fourier transforms FIR filters iterative methods convergence of numerical methods degrees of freedom magnitude response constraints beamformers convergence rate bi-iterative algorithm biquadratic cost function FIR filter finite impulse response filter phase response array response function conjugate inverse arrangement Fourier spectrum transmit array receive array Kronecker product WV full-dimensional weight vector main lobe linear phase direction-of-arrival mismatch DOA mismatch MIMO radar multiple-input-multiple-output radar robust adaptive beamforming

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Knowledge-based design of space-time transmit code and receive filter for a multiple-input-multiple-output radar in signal-dependent interference

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IET radar SONAR AND NAVIGATION 2015年第8期9卷 1124-1135页

作者： Karbasi, Seyyed Mohammad Aubry, Augusto Carotenuto, Vincenzo Naghsh, Mohammad Mahdi Bastani, Mohammad Hassan Sharif Univ Technol Fac Elect Engn Tehran *** Iran Univ Naples Federico II Dipartimento Ingn Elettr & Tecnol Informaz I-80125 Naples Italy Isfahan Univ Technol Dept Elect & Comp Engn Esfahan *** Iran

The authors deal with the robust design of multiple-input-multiple-output (MIMO) space-time transmit code (STTC) and space-time receive filter (STRF) for a point-like target embedded in signal-dependent interference. Specifically, they assume that the radar exploits knowledge provided by dynamic environmental database, to roughly predict the actual scattering scenario. Then, they devise an iterative method to optimise the (constrained) STTC and the (constrained) STRF which sequentially improves the worst-case (over interfering scatterers statistics) signal-to-interference-plus-noise ratio (SINR). Each iteration of the algorithm is handled via solving two (hidden) convex optimisation problems. The resulting computational complexity is linear with the number of iterations and polynomial with the sizes of the STTC and the STRF. At the analysis stage, they assess the performance of the proposed algorithm in terms of the achieved SINR. They show that properly exploiting the spatial degrees of freedom offered by the MIMO system, it is possible to obtain considerable SINR gains with respect to the conventional single-input-single-output system. Moreover, their results highlight the capability of the proposed method to robustify the performance of the designed system against possible knowledge inaccuracies.

关键词： MIMO radar radar receivers radar transmitters radar interference filtering theory space-time codes iterative methods radar signal processing radar clutter convex programming computational complexity polynomials knowledge-based design space-time transmit code multiple-input-multiple-output radar signal-dependent interference STTC STRF space-time receive filter point-like target dynamic environmental database iterative method clutter statistics signal-to-interference-plus-noise ratio SINR convex optimisation problem computational complexity MIMO system single-input-single-output system

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Joint estimation of direction of departure and direction of arrival for multiple-input multiple-output radar based on improved joint ESPRIT method

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IET radar SONAR AND NAVIGATION 2015年第3期9卷 308-317页

作者： Oh, Daegun Li, Ying-chun Khodjaev, Jasurbek Chong, Jong-Wha Lee, Jong-Hun DGIST Robot Syst Dalseong Gun Daegu Peoples R China Hanyang Univ Dept EE Seoul 133791 South Korea

This study presents an improved joint estimation method of signal parameters via rotational invariance technique (ESPRIT) algorithm for low-complexity simultaneous estimation of direction of departure (DOD) and direction of arrival (DOA) in a multiple-input-multiple-output radar system. The proposed algorithm is based on a data matrix and estimates DOD and DOA without a pairing operation. The computational complexity of the proposed joint ESPRIT algorithm is derived to be less than that of conventional two dimension multiple signal classification (2D-MUSIC) and reduced dimension multiple signal classification. The authors' simulation results demonstrate that the proposed algorithm achieves performance very close to that of 2D-MUSIC and better performance than that of the ESPRIT algorithm.

关键词： MIMO radar radar signal processing signal classification direction-of-arrival estimation radar antennas antenna arrays matrix algebra improved joint signal parameter estimation method low-complexity simultaneous direction-of-departure estimation low-complexity simultaneous direction-of-arrival estimation multiple-input-multiple-output radar MIMO radar rotational invariance technique method data matrix reduced dimension multiple signal classification 2D multiple signal classification 2D-MUSIC joint ESPRIT algorithm

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Robust adaptive beamforming for MIMO radar in the presence of covariance matrix estimation error and desired signal steering vector mismatch

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IET radar SONAR AND NAVIGATION 2020年第1期14卷 118-126页

作者： Huang, Junsheng Su, Hongtao Yang, Yang Xidian Univ Natl Lab Radar Signal Proc Xian 710071 Peoples R China

Owing to covariance matrix estimation error, desired signal steering vector mismatch, and the existence of target signal in training samples, most of adaptive beamforming algorithms suffer from a great performance degradation. Aim at this, this study proposes a robust adaptive beamforming algorithm for multiple-input-multiple-output radar. To be specific, the sample covariance matrix is replaced by the reconstructed covariance matrix, to narrow the difference between the maximum and minimum noise eigenvalues. In addition, the diagonal loading technique is applied to correct the mismatched desired signal steering vector by maximising the output signal-to-interference-plus-noise ratio of adaptive beamformer, and a simple closed-form solution to loading factor can be further obtained. Computer simulation results demonstrate that the proposed algorithm can efficiently improve the robustness of adaptive beamformer against both covariance matrix estimation error and desired signal steering vector mismatch.

关键词： MIMO communication vectors covariance matrices eigenvalues and eigenfunctions MIMO radar array signal processing reconstructed covariance matrix mismatched desired signal steering vector output signal-to-interference-plus-noise ratio adaptive beamformer covariance matrix estimation error desired signal steering vector mismatch target signal adaptive beamforming algorithms robust adaptive beamforming algorithm multiple-input-multiple-output radar sample covariance matrix

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SRAP for range-coupled radar imaging

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IET radar SONAR AND NAVIGATION 2020年第4期14卷 601-606页

作者： Chen, Baoxin Dong, Yunlong Huang, Yong Guan, Jian Chen, Xiaolong Naval Aviat Univ Yantai 265401 Peoples R China 92337 Troop PLA Dalian 116000 Peoples R China

Both waveforms of the frequency diverse array radar and the orthogonal frequency division multiplexing multiple-input-multiple-output radar are range coupled, so they provide an inherent advantage of angle-range joint imaging. The derivation of the signal models shows that the ranging principles are the same and the main differences lie in the spectrum structures and the demodulation schemes. Space-range adaptive processing (SRAP) is proposed for the two kinds of radar systems. Numerical simulations show that super-resolution angle-range images with extra-low sidelobes can be obtained via SRAP. The super-resolution performances of the range-coupled radars are evaluated and analysed.

关键词： array signal processing radar imaging demodulation OFDM modulation MIMO radar radar signal processing radar antennas MIMO communication SRAP range-coupled radars range-coupled radar imaging frequency diverse array radar multiple-input-multiple-output radar inherent advantage angle-range joint imaging signal models ranging principles space-range adaptive processing radar systems super-resolution angle-range images

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Two-dimensional pulse-to-pulse canceller applied in multiple-input-multiple-output radar

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IET radar SONAR AND NAVIGATION 2012年第9期6卷 945-955页

作者： Cao, Y. Feng, D. -Z. Shui, P. -L. Xiang, C. Xidian Univ Natl Lab Radar Signal Proc Xian 710071 Peoples R China

Since the spectrum of the ground clutter in the ground-based pulse radar is spatially-temporally decoupled, a simple pulse-to-pulse canceller is often used as a moving target indication filter for suppressing the ground clutter near the zero-Doppler frequency. In contrast, in the airborne phased-array radar, which is a typical single-input-multiple-output radar, the spectrum of the ground clutter is spatially-temporally coupled each other, and the two-dimensional pulse-to-pulse canceller (TDPC) for ground clutter cancellation has been developed by using the ground clutter model in the spatial-temporal domain. Based on the ground clutter model of multiple-input-multiple-output (MIMO) radar, the authors can extend the existing TDPC to more general form that can suppress the ground clutter in the MIMO radar. As the MIMO TDPC can be calculated offline by utilising the geometry knowledge of the ground clutter of MIMO radar, it can be used as an efficient and convenient ground clutter pre-filtering tool.

关键词： Electromagnetic compatibility and interference ground clutter prefiltering tool typical single-input-multiple-output radar ground-based pulse radar phased array radar zero-Doppler frequency radar equipment, systems and applications two-dimensional pulse-to-pulse canceller moving target indication filter spatial-temporal domain ground clutter cancellation Filtering methods in signal processing airborne phased-array radar radar clutter ground clutter suppression TDPC multiple-input-multiple-output radar filtering theory airborne radar MIMO radar interference suppression

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CRBs for direction-of-departure and direction-of-arrival estimation in collocated MIMO radar in the presence of unknown spatially coloured noise

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IET radar SONAR AND NAVIGATION 2019年第4期13卷 530-537页

作者： Wen, Fangqing Zhang, Xinyu Zhang, Zijing Yangtze Univ Elect & Informat Sch Jingzhou 434023 Peoples R China Lanzhou Univ Sch Informat Sci & Engn Lanzhou 730000 Peoples R China Natl Chung Hsing Univ Dept Comp Sci & Engn Taichung 402 Taiwan Xidian Univ Natl Lab Radar Signal Proc Xian 710071 Peoples R China

This study gives explicit closed-form expressions of the stochastic Cramer-Rao bounds (STO-CRBs) on direction-of-departure and direction-of-arrival estimation accuracies for collocated multiple-input-multiple-output (MIMO) radar with unknown spatially coloured noise. In some special cases, i.e. the CRB of direction estimation accuracy for monostatic MIMO radar, the white noise scenario is discussed. Theoretical comparisons between the STO-CRBs and the deterministic ones are presented. Finally, these bounds are numerically compared.

关键词： MIMO communication MIMO radar white noise direction-of-arrival estimation stochastic processes multiple-input-multiple-output radar unknown spatially coloured noise direction estimation accuracy monostatic MIMO radar white noise scenario STO-CRBs collocated MIMO radar closed-form expressions stochastic Cramer-Rao bounds direction-of-arrival estimation accuracies

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Array diagnosis and angle estimation in bistatic MIMO radar under array antenna failures

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IET radar SONAR AND NAVIGATION 2019年第7期13卷 1180-1188页

作者： Chen, Jinli Zhuo, Qigang Li, Jiaqiang Zhu, Yanping Nanjing Univ Informat Sci & Technol Collaborat Innovat Ctr Forecast & Evaluat Meteoro Nanjing Jiangsu Peoples R China Nanjing Univ Informat Sci & Technol Jiangsu Key Lab Meteorol Observat & Informat Proc Nanjing Jiangsu Peoples R China Nanjing Univ Informat Sci & Technol Sch Elect & Informat Engn Nanjing Jiangsu Peoples R China

The presence of fault antennas in bistatic multiple-input-multiple-output (MIMO) radar causes a significant degradation of angle estimation performance. In this study, the authors present a signal-processing scheme for bistatic MIMO radar with impaired receive array including array diagnosis as well as angle estimation. The damaged antenna in the receiver, which is incapable of receiving the target signals and leaves only the thermal noise generated within the receiver itself, leads to a decrease in the entropy of its received data. The dissimilarity of the entropy values between the damaged and normal receive antennas is used for array diagnosis. Thereafter, the useless noise data of the detected fault antennas is removed in the receive signal matrix, so that the successive data missing occurs along the row directions of the signal subspace matrix. A low-rank block-Hankel structured matrix is constructed from the incomplete signal subspace matrix, which can facilitate the exploitation of the matrix completion technique to recover that successive missing data. On the basis of the restored rotational invariance structure of the complete signal subspace, the estimation of signal parameters via rotational invariance technique can then be applied for angle estimation. Simulation results confirm the validity of the proposed methods.

关键词： MIMO radar receiving antennas Hankel matrices direction-of-arrival estimation matrix algebra array signal processing MIMO communication bistatic MIMO radar array antenna failures multiple-input-multiple-output radar significant degradation angle estimation performance target signal acquisition signal-processing scheme impaired receive array including array diagnosis damaged antenna target signals thermal noise received data entropy values damaged receive antennas normal receive antennas useless noise data detected fault antennas signal matrix successive data missing low-rank block-Hankel structured matrix incomplete signal subspace matrix matrix completion technique successive missing data complete signal subspace computationally efficient estimation signal parameters

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GRIDLESS ANGLE AND RANGE ESTIMATION FOR FDA-MIMO radar BASED ON DECOUPLED ATOMIC NORM MINIMIZATION 44

GRIDLESS ANGLE AND RANGE ESTIMATION FOR FDA-MIMO RADAR BASED...

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44th IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

作者： Tang, Wen-Gen Jiang, Hong Pang, Shuai-Xuan Jilin Univ Coll Commun Engn Changchun 130012 Jilin Peoples R China

ISBN: (纸本)9781479981311

The frequency diverse array (FDA), which exploits a small frequency increment across the transmitting antenna elements, has been recently introduced to multiple-input-multiple-output (MIMO) radar to offer the capability of range-angle-dependent beampattern and target localization. Traditionally, the two-dimensional (2D) subspace-based methods and grid-based sparse reconstruction algorithms are used to obtain angle and range in FDA-MIMO radar. In this paper, with a single measurement, we propose a gridless angle and range estimation approach for FDA-MIMO radar based on decoupled atomic norm minimization (DANM). First, we convert the 2D-ANM based angle and range estimation into a decoupled semi-definite programming problem with two one-dimensional (1D) Toeplitz Hermitian matrices. Then we apply the matrix enhancement and matrix pencil method and construct a permutation matrix to obtain joint angle and range estimation and parameter pairing. Numerical results verify that the proposed approach overcomes the grid-mismatch effect of the sparse reconstruction-based OMP algorithm and outperforms the subspace-based MUSIC method.

关键词： Frequency diverse array multiple-input-multiple-output radar angle and range estimation atomic norm minimization gridless parameter estimation

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