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Improvement of DDM Preprocessing for the Simulation of the GRAVES Radar Densified sparse array for Space Surveillance and Tracking

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IEEE ANTENNAS AND WIRELESS PROPAGATION LETTERS 2020年第8期19卷 1434-1438页

作者： Barka, Andre Jouade, Antoine Univ Toulouse French Aerosp Lab ONERA Electromagnetism & Radar Dept F-31055 Toulouse France

In a recent work (A. Jouade and A. Barka, "Massively parallel implementation of FETI-2LM methods for the simulation of the sparse receiving array evolution of the GRAVES radar system for space surveillance and tracking, IEEE Access, vol. 7, pp. 128968-128979, 2019), we have discussed our implementation of the finite-element tearing and interconnecting (FETI) method and the domain decomposition method (DDM) for the full-wave simulation of the large GRAVES sparse array (60 m diameter disk). Owing to the nonregular distribution of the antennas of the sparse array, such simulations in reasonable times are not accessible with existing FETI methods optimized for repetitive geometries, which do not benefit from an effective parallelization technique. A particularity of the preprocessing step of our DDM is that the complete sparse array mesh is not built upstream of the resolution of the electromagnetic problem. Each subdomain in our decomposition is equipped with its own local mesh, belonging to a limited set of unit-cell meshes, generated separately. Initially, a total of 13 692 subdomains were chosen among three types of subdomains, considering those corresponding to antennas (200), air subdomains (800), and ground plane subdomains (12 592). This simulation has required 13 692 Intel Xeon Broadwell E5-2680v4 processing cores equipped with 4 GB of memory, each handling one subdomain. A new strategy is shown, which requires only 2408 cores for the same simulation, leading to an 82.41% reduction in the required number of cores, as well as a 30% reduction in the simulation time.

关键词： Aerospace control bistatic radar domain decomposition Doppler radar finite-element tearing and interconnecting (FETI) low-earth orbit (LEO) satellites parallel machines radar tracking space surveillance and tracking sparse array supercomputers

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Synthesis of sparse array With Sum and Difference Patterns Under Minimum Element Spacing Control by Alternating Linear Programming Optimization

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IEEE ANTENNAS AND WIRELESS PROPAGATION LETTERS 2021年第6期20卷 1028-1032页

作者： Wu, Pan Liu, Yanhui Liu, Foxiang Yang, Shiwen Hu, Jun Xiamen Univ Inst Electromagnet & Acoust Xiamen 361005 Fujian Peoples R China Univ Elect Sci & Technol China Sch Elect Sci & Engn Chengdu 611731 Peoples R China Univ Elect Sci & Technol China Yangtze Delta Reg Inst Quzhou 324000 Peoples R China

A novel method based on alternating linear programming optimization is presented to synthesize sparse linear arrays with sum and difference patterns. This method can find the optimized element positions and excitations shared for both sum and difference patterns with accurate control of multiregion sidelobe distribution and difference pattern null slope. In addition, the constraints on the minimum element spacing and dynamic range ratio of the obtained excitations can be also appropriately incorporated into this alternating optimization process. Two synthesis examples with different pattern shape requirements are conducted to validate the effectiveness and advantages of the proposed method.

关键词： Optimization Minimization Shape Upper bound Programming Linear antenna arrays Radar tracking Alternating linear programming optimization (ALPO) minimum element spacing control sparse array sum and difference patterns

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A variational Bayesian strategy for solving the DOA estimation problem in sparse array

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DIGITAL SIGNAL PROCESSING 2019年 90卷 28-35页

作者： Yang, Jie Yang, Yixin Lu, Jieyi Northwestern Polytech Univ Minist Ind & Informat Technol Key Lab Ocean Acoust & Sensing Xian 710072 Shaanxi Peoples R China

This paper reformulates the problem of direction-of-arrival (DOA) estimation for sparse array from a variational Bayesian perspective. In this context, we propose a hierarchical prior for the signal coefficients that amounts marginally to a sparsity-inducing penalty in maximum a posterior (MAP) estimation. Further, the specific hierarchy gives rise to a variational inference technique which operates in latent variable space iteratively. Our hierarchical formulation of the prior allow users to model the sparsity of the unknown signal with a high degree, and the corresponding Bayesian algorithm leads to sparse estimators reflecting posterior information beyond the mode. We provide experimental results with synthetic signals and compare with state-of-the-art DOA estimation algorithm, in order to demonstrate the superior performance of the proposed approach. (C) 2019 Elsevier Inc. All rights reserved.

关键词： Direction-of-arrival (DOA) estimation sparse array Hierarchical prior Maximum a posteriori (MAP) Variational inference

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Grating-lobe-free optical phased array with 2-D circular sparse array aperture and high-efficiency phase calibration

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NANOPHOTONICS 2024年第1期13卷 29-37页

作者： Lian, Daixin Zhao, Shi Li, Wenlei Chen, Jingye Dai, Daoxin Shi, Yaocheng Zhejiang Univ Coll Opt Sci & Engn Ctr Opt & Electromagnet Res Int Res Ctr Adv PhotonState Key Lab Modern Opt In Zijingang Campus Hangzhou 310058 Peoples R China Zhejiang Univ Coll Opt Sci & Engn Ningbo Innovat Ctr Ningbo Campus Ningbo 315100 Peoples R China Jiaxing Key Lab Photon Sensing & Intelligent Imagi Jiaxing 314000 Peoples R China Zhejiang Univ Intelligent Opt & Photon Res Ctr Jiaxing Res Inst Jiaxing 314000 Peoples R China Zhejiang Univ Ningbo Res Inst Ningbo 315100 Peoples R China

An optical phased array (OPA) with 2-D circular sparse array aperture has been proposed and demonstrated in the silicon integrated photonic platform. The sparse distribution of the antenna array can realize no grating lobes in 2-D full field of view (FOV). To achieve fast and accurate phase calibration for OPA, an improved rotating element electric field vector algorithm based on golden section search method (GSS-REV) has also been proposed and verified. The 32-element antenna sparse distribution of the proposed OPA is designed and fabricated. A far-field beam steering measurement across 20(degrees) x 20(degrees) range features the side lobe suppression ratio (SLSR) of larger than 4.81 dB and a full width at half-maximum (FWHM) of approximately 0.63(degrees) x 0.59(degrees). The resolvable points are derived to be similar to 1076. The OPA chip has also been demonstrated on range measurement with frequency-modulated continuous-wave (FMCW) system.

关键词： silicon optical phased array sparse array phase calibration

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Analysis of Key Parameters of Spatial Power Combination of sparse array Time Reversal Signals

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IETE JOURNAL OF RESEARCH 2024年第9期70卷 7302-7312页

作者： Chen, Qiuju Zhang, Kai Li, Wei Zhang, Yi Univ Sci & Technol China Hefei 230026 Peoples R China Hefei Univ Adv Mfg Engn Coll Hefei 230601 Peoples R China Anhui Jianzhu Univ Anhui Prov Key Lab Intelligent Bldg & Bldg Energy Hefei Peoples R China

Based on the principle of spatial power combination of sparse array time reversed signals, the relationship of distances between constructive interference points to cross angle of beams and viewing angles has been analyzed. Then the formulas of distances between adjacent constructive points at 360-degree views are derived. Considering that the distance between constructive interference points around target is frequently needed to be less than target's antenna size, The variation law of the view range with beam crossover angle has been simulated and analyzed with MATLAB when the above conditions are met at the same frequency and without errors. On this basis, array deployment recommendations are summed up. In addition, the effects of the received time window length and the difference of the distance between each array element and the target point on the synthesized power have been analyzed. Finally, the spatial power combination simulation experiments of the sparse array time-reversed signal have been carried out. The experimental results show that the methods and conclusions of this paper can provide theoretical basis and reference for the research and application of sparse array power combination technology in long-range wireless energy delivery, high-power microwave weapons, electronic warfare, etc.

关键词： sparse array spatial power combination time reversal

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2D-DOA Estimation Based on Higher-Order SVD-Based Using EMVS sparse array

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CIRCUITS SYSTEMS AND SIGNAL PROCESSING 2023年第3期43卷 1755-1772页

作者： Gao, Mingzhou Zhang, Zhe Yan, Chaojun Wen, Fangqing China Three Gorges Univ Hubei Prov Engn Technol Res Ctr Construct Qual Tes Yichang 443002 Peoples R China Hubei Univ Automot Technol Inst Vehicle Informat Control & Network Technol Shiyan 442002 Peoples R China

In this paper, we propose a tensor-based subspace algorithm for the two-dimensional direction of arrival (2D-DOA) estimation using a sparse array equipped with electromagnetic vector sensors (EMVS). Our approach capitalizes on the multidimensional characteristics of the collected data by arranging its covariance into a fourth-order tensor. Through the application of higher-order singular value decomposition, we improve signal subspace estimation compared to existing methods. To further enhance our algorithm, we integrate spatial rotation invariance techniques and vector cross-product methods. This combination enables automatic angle estimation without the need for pairing and without compromising aperture loss. Our proposed algorithm exhibits superior estimation performance, particularly in challenging scenarios characterized by low signal-to-noise ratios and limited snapshot availability. To validate the effectiveness and enhancements of our approach, we conduct numerical simulation experiments.

关键词： Electromagnetic vector sensor sparse array Angle estimation Higher-order singular value decomposition

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A sparse array Direction-Finding Approach Under Impulse Noise

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CIRCUITS SYSTEMS AND SIGNAL PROCESSING 2023年第9期42卷 5579-5601页

作者： Du, Yanan Gao, Hongyuan Liu, Yapeng Cheng, Jianhua Chen, Menghan Harbin Engn Univ Coll Informat & Commun Engn Harbin Peoples R China Harbin Engn Univ Coll Intelligent Syst Sci & Engn Harbin 150001 Peoples R China

To address the issue that existing direction-finding approaches perform poorly under impulse noise and do not work well in underdetermined scenarios, a novel sparse array direction-finding approach on the background of impulse noise is proposed in this work. The approach introduces an infinite norm Gaussian kernel to restrain the impulse noise and obtains accurate estimates via the maximum likelihood algorithm. Meanwhile, a novel quantum transient search optimization (QTSO) algorithm is designed to solve the corresponding cost function. In addition, we prove the convergence of QTSO and derive the Cramer-Rao bound of sparse array direction finding in the presence of impulse noise. Compared with some traditional direction-finding approaches, the proposed approach shows excellent performance through simulation results in different schemes, which can also be a general framework to address other complex direction-finding problems.

关键词： Direction finding sparse array Impulse noise Quantum transient search optimization Infinite norm Gaussian kernel Cramer-Rao bound

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Low elevation and range joint estimation method with metre wave frequency diverse array-multiple input multiple output radar based on sparse array

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IET RADAR SONAR AND NAVIGATION 2022年第7期16卷 1176-1187页

作者： Wang, Hongzhen Zheng, Guimei Liu, Yibin Song, Yuwei Air Force Engn Univ Xian Peoples R China

Frequency diverse array-multiple input multiple output (FDA-MIMO) radar not only has the advantage of waveform diversity but also can realise azimuth-range correlation map, so it can realise high precision azimuth-range joint estimation and has the ability to distinguish different range unit targets in the same azimuth. However, the existing research mainly adopts uniform linear array (ULA) model and mainly focusses on incoherent targets. At present, the elevation-range joint estimation algorithm of metre wave FDA-MIMO radar based on ULA has the problems of sharp decline in angle-range measurement accuracy of ultra-low altitude targets and large fluctuation of elevation-range measurement accuracy with changing elevation. In order to solve the above difficult problems, starting from the perspective of reducing the influence of multipath effect by array structure, this paper innovatively combines sparse array with FDA-MIMO radar, establishes the low elevation-range joint estimation model of metre wave FDA-MIMO radar based on sparse array, and puts forward the low elevation-range joint estimation method suitable for this model, and it fills the gap of low elevation-range measurement method based on sparse array metre wave FDA-MIMO radar. Simulation experiments compare two typical sparse arrays with ULA of equal array elements, which verify the superiority of low elevation-range measurement performance of monostatic metre wave FDA-MIMO radar based on sparse array and the effectiveness of the proposed method.

关键词： frequency diverse array joint elevation-range estimation metre wave MIMO radar sparse array

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Source localization for sparse array using nonnegative sparse Bayesian learning

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SIGNAL PROCESSING 2016年 127卷 37-43页

作者： Hu, Nan Sun, Bing Wang, Jiajun Dai, Jisheng Chang, Chunqi Soochow Univ Sch Elect & Informat Engn Suzhou 215006 Jiangsu Peoples R China Jiangsu Univ Sch Elect & Informat Engn Zhenjiang 212013 Jiangsu Peoples R China Shenzhen Univ Sch Biomed Engn Shenzhen 518060 Peoples R China

The problem of source localization is addressed for sparse arrays, which have the special array geometry to increase the degree of freedom (DOF), and a nonnegative sparse signal recovery (SSR) problem is formulated for the virtual array response model of sparse arrays. A novel method is developed in the framework of nonnegative sparse Bayesian learning (NNSBL), which obviates presetting any hyperparameter, and an expectation-maximization (EM) algorithm is exploited for solving this NNSBL problem. Without a priori knowledge of the source number, the proposed method yields superior performances in the underdetermined condition illustrated by numerical simulations. (C) 2016 Elsevier B.V. All rights reserved.

关键词： Direction-of-arrival sparse array Nonnegative sparse Bayesian learning Expectation-maximization

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A Four-Corner-Fed Slotted Waveguide sparse array for Near-Field Focusing

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IEEE ACCESS 2020年 8卷 203048-203057页

作者： Wu, Yaxiang Jiang, Bolin Zhang, Miao Hirokawa, Jiro Liu, Qing Huo Xiamen Univ Inst Electromagnet & Acoust Xiamen 361005 Peoples R China Tokyo Inst Technol Dept Elect & Elect Engn Tokyo 1528552 Japan Duke Univ Dept Elect & Comp Engn Durham NC 27708 USA

This article presents a double-layer four-corner-fed slotted waveguide sparse array antenna designed for the near-field-focused applications in the X-band. Generally, it is challenging to realize the ideal phase distribution of the near-field focused array antenna, especially for the near-field focusing array antenna with a focal distance less than 5 lambda. We propose a four-corner-feed structure associated with appropriate waveguide dimensions to realize approximately ideal phase distribution for a focus at 1.5 lambda. The sparse array based on the particle swarm optimization is adopted to suppress the sidelobes and the grating lobes on the focal plane caused by the residual phase errors. A test antenna is designed at the center frequency of 10 GHz, and is fabricated by Direct Metal Laser Sintering technique for demonstration. It is verified by the experiment that we achieve satisfying near-field focusing effects, especially in terms of the focal spot size and sidelobe levels on the focal plane 45 mm away from the antenna aperture.

关键词： Slotted waveguide array sparse array near-field focusing short focal distance tranverse slot particle swarm optimization direct metal laser sintering technique

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