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Real-Time Millimeter-Wave Imaging for Moving Targets Realized in a sparse array Based on InP-HBT MMICs

IEEE TRANSACTIONS ON MICROWAVE THEORY AND TECHNIQUES 2022年第10期70卷 4478-4490页

作者： Tu, Hao Pan, Xiaofeng Chen, Lin Meng, Xiangxin Hu, Ruiji Liu, Yao Zhang, Jun Zhao, Ming Liu, Jie Huang, Wen Sang, Lei Hefei Univ Technol Sch Microelect Hefei 230009 Peoples R China Brainware Terahertz Informat Technol Co Ltd Hefei 230000 Peoples R China Nanjing Elect Devices Inst Sci & Technol Monolith Integrated Circuits & Modu Nanjing 210016 Peoples R China

Millimeter-wave (MMW) imaging has been widely studied for applications, such as personnel screening and industrial noninvasive testing;however, real-time MMW imaging with a subcentimeter resolution and a large field of view (FoV) for a fast-moving target has been rarely reported to date. In this article, we present the design of such an imaging system at the Ka-band utilizing the concept of multistatic sparse array. Microwave monolithic integrated circuits based on an InP-heterojunction bipolar transistor (HBT) technology are used for the transmitter and receiver chipsets. With the help of an improved backprojection algorithm and a computation platform based on field-programmable gate arrays, real-time imaging for a target moving as fast as about 10 m/s is demonstrated at a frame rate of over 20 frames/s. The imaging resolution is measured to be better than 6 mm and the FoV can reach over 1 x 1 m(2). Imaging of a moving person with concealed items is carried out to illustrate the system's capability for personnel screening. To the hest of the authors' knowledge, this is the first real-time MMW sparse array imaging system built upon lnP-HBT chipsets.

关键词： Backprojection (BP) field-programmable gate array (FPGA) InP-heterojunction bipolar transistor (HBT) millimeter-wave (MMW) imaging real-time imaging sparse array

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A novel high degree of freedom sparse array with displaced multistage cascade subarrays

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DIGITAL SIGNAL PROCESSING 2019年 90卷 36-45页

作者： Zhang, Yan-kui Xu, Hai-yun Zong, Rong Ba, Bin Wang, Da-ming Natl Digital Switching Syst Engn & Technol Res Ct Zhengzhou 450001 Henan Peoples R China

The coprime array is a recently developed sparse array that is widely used in direction-of-arrival (DOA) estimation. The degree of freedom (DOF) for existing coprime arrays relies on the virtual array model, which is limited to the array structure. Furthermore, the continuous virtual array aperture is restricted. This paper aims to propose a novel high DOF sparse array with displaced multistage cascade subarrays to further increase the length of the continuous virtual array and improve the DOF. Through cascading and separating the same sparse arrays, the continuous virtual array aperture is improved and the accuracy of the direction-of-arrival estimation is increased. It is proved that the range of the displaced distance for the maximized continuous virtual array can be obtained. The comparison between the array configuration presented in this paper and the existing common arrays are analyzed. The simulation experiments show that, compared with the uniform array, the coprime array, the nested array, and the coprime array with displaced subarrays (CADiS), the sparse array configuration proposed in this paper can significantly increase the aperture of the continuous virtual array, greatly improve the array DOF and the DOA estimation accuracy, and effectively estimate the DOA of multiple sources in underdetermined conditions. (C) 2019 Elsevier Inc. All rights reserved.

关键词： Direction-of-arrival (DOA) sparse array Degree of freedom (DOF) Virtual array

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Planar sparse array Synthesis for Sensor Selection by Convex Optimization with Constrained Beam Pattern

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WIRELESS PERSONAL COMMUNICATIONS 2016年第4期89卷 1147-1163页

作者： Du, Yu Hu, Fengye Liu, Xiaolan Cen, Ling Xiong, Wei Jilin Univ Coll Commun Engn Changchun 130025 Jilin Peoples R China

The design of sparse array which is able to achieve good performance of beampattern satisfying the minimum peak sidelobe level (PSL) with the number of sensors as few as possible is a research area of increasing interest. This paper presents a method for planar optimization with sensor selection via convex optimization in condition of constrained beam-pattern. In the optimization procedure, the solution algorithm is based on convex optimization including a reweighted l(1)-norm minimization. The objective is the minimum of the number of sensors and the PSL. sparse array is obtained by removing those sensors with weights equal to zero or approximately equal to zero. In this paper, we also give the optimization algorithm respectively by row, column and the intersection on the basis of the linear array optimization. Numerical results are included, which illustrate the optimum method for planar arrays overall performs better than the other methods presented above for sensor selection.

关键词： Sensor selection sparse array Convex optimization Peak sidelobe level array weight

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Adaptive sparse array Beamformer Design by Regularized Complementary Antenna Switching

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IEEE TRANSACTIONS ON SIGNAL PROCESSING 2021年 69卷 2302-2315页

作者： Wang, Xiangrong Greco, Maria Sabrina Gini, Fulvio Beihang Univ Sch Elect & Informat Engn Beijing Peoples R China Univ Pisa Dept Informat Engn I-56122 Pisa Italy

In this work, we propose a novel strategy of adaptive sparse array beamformer design, referred to as regularized complementary antenna switching (RCAS), to swiftly adapt both array configuration and excitation weights in accordance to the dynamic environment for enhancing interference suppression. In order to achieve an implementable design of array reconfiguration, the RCAS is conducted in the framework of regularized antenna switching, whereby the full array aperture is collectively divided into separate groups and only one antenna in each group is switched on to connect with the processing channel. A set of deterministic complementary sparse arrays with good quiescent beampatterns is first designed by RCAS and full array data is collected by switching among them while maintaining resilient interference suppression. Subsequently, adaptive sparse array tailored for the specific environment is calculated and reconfigured based on the information extracted from the full array data. The RCAS is devised as an exclusive cardinality-constrained optimization, which is reformulated by introducing an auxiliary variable combined with a piece-wise linear function to approximate the l(0)-norm function. A regularization formulation is proposed to solve the problem iteratively and eliminate the requirement of feasible initial search point. A rigorous theoretical analysis is conducted, which proves that the proposed algorithm is essentially an equivalent transformation of the original cardinality-constrained optimization. Simulation results validate the effectiveness of the proposed RCAS strategy.

关键词： Adaptive arrays Antenna arrays Switches array signal processing Sensors Antennas Sensor arrays sparse array situation awareness adaptive beamformer quiescent pattern regularized antenna switching

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A DOA Estimation Method for sparse array Based on DFT Spectrum of Received Signals

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IEEE ACCESS 2022年 10卷 95849-95858页

作者： Zhang, Liye Cui, Weijia Ba, Bin Jian, Chunxiao Li, Hao Natl Digital Switching Syst Engn & Technol Res Ct Zhengzhou 450001 Henan Peoples R China

In the direction of arrival (DOA) estimation of sparse array received signals, the estimation accuracy of the grid search method in compressed sensing is improved with the increase of over-complete redundant dictionary elements. However, the increase of over-complete redundant dictionary elements will lead to a significant increase in the computational complexity of this method. In order to reduce the computational complexity caused by over-complete redundant dictionary division, based on the equivalent received signal of large aperture continuous difference co-array generated by sparse array, a DOA estimation method using discrete Fourier transform (DFT) spectrum of signal for initial estimation is proposed in this paper. After obtaining the DFT spectrum of the equivalent signal, based on the correspondence between the DFT spectrum and the actual angle value, this paper proposes a new strategy for dividing the over-complete redundant dictionary. In the process of fine angle search, this paper applies Taylor expansion to orthogonal matching pursuit (OMP) algorithm to obtain higher estimation accuracy. Numerical simulation results demonstrate the advantages of the proposed estimation method over the other methods.

关键词： Sensor arrays Estimation Direction-of-arrival estimation Sensors Discrete Fourier transforms array signal processing Apertures array signal processing sparse array DOA estimation difference co-array

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sparse array Beampattern Synthesis via Majorization-Based ADMM 94

Sparse Array Beampattern Synthesis via Majorization-Based AD...

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94th IEEE Vehicular Technology Conference (VTC-Fall)

作者： Wei, Tong Wu, Linlong Shankar, Bhavani M. R. Univ Luxembourg Interdisciplinary Ctr Secur Reliabil & Trust SnT Luxembourg Luxembourg

ISBN: (纸本)9781665413688

Beampattern synthesis is a key problem in many wireless applications. With the increasing scale of MIMO antenna array, it is highly desired to conduct beampattern synthesis on a sparse array to reduce the power and hardware cost. In this paper, we consider conducting beampattern synthesis and sparse array construction jointly. In the formulated problem, the beampattern synthesis is designed by minimizing the matching error to the beampattern template, and the Shannon entropy function is first introduced to impose the sparsity of the array. Then, for this nonconvex problem, an iterative method is proposed by leveraging on the alternating direction multiplier method (ADMM) and the majorization minimization (MM). Simulation results demonstrate that, compared with the benchmark, our approach achieves a good trade-off between array sparsity and beampattern matching error with less runtime.

关键词： sparse array Shannon entropy function beampattern synthesis majorization-minimization ADMM

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Robust Variational Bayesian Inference for Direction-of-Arrival Estimation With sparse array

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IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY 2022年第8期71卷 8591-8602页

作者： Liu, Ying Zhang, Zongyu Zhou, Chengwei Yan, Chenggang Shi, Zhiguo Zhejiang Univ Coll Informat Sci & Elect Engn Hangzhou 310027 Peoples R China Zhejiang Univ State Key Lab Ind Control Technol Hangzhou 310027 Peoples R China Hangzhou Dianzi Univ Sch Automat Hangzhou 310018 Peoples R China Zhejiang Univ Int Joint Innovat Ctr Haining 314400 Peoples R China

Conventional direction-of-arrival (DOA) estimation algorithms are sensitive to array imperfections and outliers, making it challenging to realize accurate estimates in real applications. Facing the challenge, we propose a robust variational Bayesian inference based DOA estimation algorithm using the linear sparse array in this paper, where accurate DOA estimation with increased number of degrees of freedom (DOFs) is realized. With the mixture of von Mises model, a prior-grid scheme is further proposed to alleviate the computational burden introduced by the Bayesian variational inference framework. Since there is no restriction on the prior knowledge of the number of sources, the proposed algorithm is friendly to actual scenarios. Simulation results demonstrate the effectiveness of the proposed algorithm.

关键词： Direction-of-arrival estimation Estimation Sensor arrays Sensors Bayes methods Inference algorithms sparse matrices Direction-of-arrival estimation gain-phase error outlier sparse array variational Bayesian inference

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A Multiscale sparse array of Spatially Spread Electromagnetic-Vector-Sensors for Direction Finding and Polarization Estimation

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IEEE ACCESS 2018年 6卷 9807-9818页

作者： Yang, Minglei Ding, Jin Chen, Baixiao Yuan, Xin Xidian Univ Natl Lab Radar Signal Proc Xian 710071 Shaanxi Peoples R China Nokia Bell Labs Murray Hill NJ 07974 USA

In this paper, a multiscale sparse array, which is composed of spatially-spread electromagnetic-vector-sensors (SS-EMVSs), is proposed to estimate the direction-of-arrivals (DOA) and polarizations of multiple sources. The SS-EMVS is composed of three orthogonally oriented but spatially noncollocated dipoles to measure the electric field and three orthogonally oriented but spatially noncollocated loops to measure the magnetic field, simultaneously. In this paper, an array of SS-EMVSs is placed along the y-axis, and this sparse array is composed of two sub-arrays, i.e., the first n(1) SS-EMVSs with inter-sensor spacing D-1, and the last n(2) SS-EMVSs with inter-sensor spacing D-2, with D-2 = mD(1);m > 1 is an integer and D-1 is larger than a half-wavelength of the incident signal. Thereby, a multiscale sparse array is constructed, which is capable of providing high accuracy estimates of DOA and polarizations of multiple sources. The vector-cross-product algorithm is used to obtain the unambiguous but low-accuracy estimations of direction cosines, and the different inter-sensor spacings are used to estimate high-accuracy but ambiguous estimations of direction cosines. Following this, a multiscale disambiguation algorithm is developed to obtain high-accuracy and unambiguous estimations of direction cosines, thus the elevation angles, azimuth angles, as well as the polarization parameters of multiple sources. Simulation results verify the superior performance of the proposed multiscale SS-EMVS array.

关键词： Sensor arrays direction-of-arrival (DOA) estimation polarization estimation direction finding sparse array nested array electromagnetic-vector-sensor

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1.5-D sparse array for Millimeter-Wave Imaging Based on Compressive Sensing Techniques

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IEEE TRANSACTIONS ON ANTENNAS AND PROPAGATION 2018年第4期66卷 2008-2015页

作者： Zamani, Hojatollah Fakharzadeh, Mohammad Sharif Univ Technol Elect Engn Dept Tehran *** Iran

The goal of this paper is to reduce the antenna count in a millimeter (mm)-wave imaging system by proposing both hardware and software solutions. The concept of image sparsity in the transform domain is utilized to present the compressive sensing (CS) formulation for both mono-static and multistatic imaging at mm-wave frequencies. To reduce the complexity of the imaging system and reconstruction process, we introduce 1.5-D array structure, which is a random sparse array with orthogonal element locations. It is shown that the peak signal-to-noise ratio (PSNR) of the reconstructed image obtained by a 1.5-D array with 65% sparsity is very close to the PSNR of a uniform 2-D array for mono-static imaging. Moreover, for multistatic imaging, it is illustrated that a high-quality image is reconstructed with 92% reduction in antenna elements, which significantly reduces the cost, scan time, and system complexity. Furthermore, a 1.5-D array of 16 patch antennas with 60% sparsity, operating from 29 to 32 GHz is designed and implemented to investigate the performance of the proposed 1.5-D array for imaging, as well as the presented CS-based reconstruction method. Measurements show that the quality of the reconstructed image using this 1.5-D array with CS-based reconstruction is very close to a full 2-D array;for example, the PSNR achieved for the reconstructed image of a knife is 33 dB referenced to a uniform 2-D array. The proposed reconstruction method results in 6-11 dB improvement in PSNR compared with the conventional reconstruction methods with a reasonable increase in computing load.

关键词： Compressive sensing (CS) millimeter (mm)-wave imaging mono-static multistatic sparse array

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A Novel Ultra-Wideband Wide-angle Scanning sparse array Antenna using Genetic Algorithm

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APPLIED COMPUTATIONAL ELECTROMAGNETICS SOCIETY JOURNAL 2023年第2期38卷 100-108页

作者： Jiang, Z. N. Zheng, Y. Xuan, X. F. Nie, N. Y. Hefei Univ Technol Sch Elect Sci & Appl Phys Hefei 230009 Peoples R China Southeast Univ Natl Mobile Commun Res Lab Nanjing 210096 Jiangsu Peoples R China

A single-element antenna is usually unable to meet the communication requirements of the wire-less system and the main solution is to use an array antenna. The desire to reduce the weight and cost of the array antenna gave rise to the sparse array. A lin-early polarized sparse array antenna with ultra-wideband wide-angle scanning characteristics based on a genetic algorithm (GA) is developed in this paper. The antenna array consists of 40 units, which are arranged by a rectangular array with a side length of 300 mm. Com-pared to the conventional periodic array, the proposed sparse array has reduced about 190 antenna elements. The sparse array can achieve S11 < -10 dB in the ultra-wideband of 2.7-12 GHz (120%). Experimental results for the proposed antenna exhibit an azimuth scanning angle of & PLUSMN;45 & DEG;, and a pitching scanning angle of & PLUSMN;30 & DEG;.

关键词： genetic algorithm (GA) linearly polar-ized sparse array ultra-wideband wide-angle scanning

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