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Journal articles on the topic 'Sparse Antenna Array'

Author: Grafiati

Published: 4 June 2021

Last updated: 1 February 2022

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1

Wang, Ting, Ke-Wen Xia, and Ning Lu. "Pattern Synthesis for Sparse Arrays by Compressed Sensing and Low-Rank Matrix Recovery Methods." International Journal of Antennas and Propagation 2018 (2018): 1–11. http://dx.doi.org/10.1155/2018/6403269.

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Antenna array pattern synthesis technology plays a vital role in the field of smart antennas. It is well known that the pattern synthesis of homogeneous array is the key topic of pattern synthesis technology. But this technology needs plenty of homogeneous array elements to meet the antenna requirements. So, a novel pattern synthesis technology for sparse array based on the compressed sensing (CS) and low-rank matrix recovery (LRMR) methods is proposed. The proposed technology predominantly includes the design of sparse array, the recovery of homogeneous array, and the synthesis of antenna array pattern. The simulation result shows that an antenna array with low gain and strong directivity can be arbitrarily built by the use of a small amount of sparse array elements and it is useful for the miniaturization and economical efficiency of the antenna system.

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2

Chen, Zhikun, Tao Li, Dongliang Peng, and Kang Du. "Two-Dimensional Beampattern Synthesis for Polarized Smart Antenna Array and Its Sparse Array Optimization." International Journal of Antennas and Propagation 2020 (June 13, 2020): 1–13. http://dx.doi.org/10.1155/2020/2196049.

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Polarized smart antenna array has attracted considerable interest due to its capacity of matched reception or interference suppression for active sensing systems. Existing literature does not take full advantage of the combination of polarization isolation and smart antennas and only focuses on uniform linear array (ULA). In this paper, an innovative synthesis two-dimensional beampattern method with a null that has cross-polarization for polarized planar arrays is proposed in the first stage. This method aims to further enhance the capability of interference suppression whose optimization problem can be solved by second-order conic programming. In the second stage, a new sparse array-optimized method for the polarized antenna array is proposed to reduce the high cost caused by the planar array that is composed of polarized dipole antennas. Numerical examples are provided to demonstrate the advantages of the proposed approach over state-of-the-art methods.

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3

Lu, Junqi, and Yongxin Guo. "Compact Planar Sparse Array Antenna with Optimum Element Dimensions for SATCOM Ground Terminals." International Journal of Antennas and Propagation 2015 (2015): 1–11. http://dx.doi.org/10.1155/2015/806981.

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A novel antenna array architecture for low-cost and compact SATCOM mobile terminal is presented. Based on equal-amplitude aperiodic phased array with fewer active chain numbers, it possesses advantages including lower weight, less cost, and higher power efficiency compared to conventional periodic phased arrays. It is implemented with printed patch antenna so that it guarantees compactness. The elements position and dimensions are jointly designed, with an effective sparse array synthesis strategy that takes actual patch antenna design constraint into consideration, to obtain a maximum array aperture efficiency. Executable and practical approach for variable dimension patch antenna designing, including defect substrate element and small scale array, is introduced and utilized to implement proposed sparse array. Full-wave simulation results demonstrate the advantages of proposed array antenna as well as the effectiveness of corresponding design approach.

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4

Li, Yanfei, and Yang Li. "Investigation on SIW Slot Antenna Array with Beam Scanning Ability." International Journal of Antennas and Propagation 2019 (January 6, 2019): 1–7. http://dx.doi.org/10.1155/2019/8293624.

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A sparse substrate integrated waveguide (SIW) slot antenna array and its application on phase scanning are studied in this paper. The genetic algorithm is used to optimize the best arrangement for 8-element and 7-element sparse arrays over an aperture of 4.5λ0. Antenna arrays with feeding networks, for steering the main beam pointing to 0° and −15°, are demonstrated with the SIW technology. The comparison between the sparse array and the conventional uniformly spaced array with the same aperture are presented, which suggest that the same beam width can be obtained with the gain decreased by 0.5 or 1 dBi and the number of element reduced by 2 or 3, respectively. The sparse antenna array with beam scanning ability presented in this paper shows that, while the beam scanning in the range of ±15°, the gain fluctuation is less than 0.3 dBi and the side lobe level is lower than −10 dB.

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5

Sandi, E., F. Y. Zulkifli, and E. T. Rahardjo. "A Hybrid Technique Using Combinatorial Cyclic Difference Sets and Binomial Amplitude Tapering for Linear Sparse Array Antenna Design." Advanced Electromagnetics 5, no. 3 (December 6, 2016): 73. http://dx.doi.org/10.7716/aem.v5i3.432.

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Reducing system complexity and cost in synthesizing a sparse array antenna design is a challenging task for practical communication systems, such as radar systems and space communication. In this paper, a hybrid technique to synthesize a linear sparse array antenna design is described. This technique is developed using two methods. The first method is a combinatorial approach that applies cyclic difference sets (CDS) integers to significantly reduce the number of antenna elements. The approach and procedure used to apply the new CDS method to configure a linear sparse array, with significant reduction of the spatial antenna dimension, is described. The second method, applied to the array result of the first method, is amplitude tapering using a binomial array approach to reduce the sidelobes level (SLL). The simulation and measurement results of the sample sparse array design showed that the SLL was reduced in comparison to the sparse array design using only the combinatorial CDS method.

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6

Shi, Shuli, Yougen Xu, Junpeng Zhuang, Kang Zhao, Yulin Huang, and Zhiwen Liu. "Tri-polarized Sparse Array Design for Mutual Coupling Reduction in Direction Finding and Polarization Estimation." Electronics 8, no. 12 (December 17, 2019): 1557. http://dx.doi.org/10.3390/electronics8121557.

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Multi-polarized antenna arrays have the ability to provide both the direction and polarization information of the incident signals, which is important in radar, sonar, wireless communication, remote sensing, and so on. In this paper, a diversely polarized linear array of sparsely located but identically oriented tri-polarized vector antennas (VAs) is designed for estimating the direction-of-arrival (DOA) and polarization parameters of the incident signals in the presence of antenna mutual coupling (MC). In order to reduce the inter-VA MC, a new type of sparse array geometry is proposed, wherein the minimum inter-VA spacing is constrained to be no less than one signal wavelength. Considering the intra-VA MC effect, a full-wave electromagnetic simulation is introduced to fit the manifold vector of an isolated VA. Based on the sparse VA array, a polarimetric subspace scheme is proposed for DOA and polarization estimation. When the knowledge about the intra-VA MC is a priori unavailable, an algebraic polarimetric blind scheme is also provided for DOA estimation. Computer simulations and real-world experiments (using an S-band 24-channel tri-polarized array system) validate the efficacy of the designed array geometry along with the parameter estimation methods.

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7

Jiao, Jian, and Xue Jiao Zheng. "Extended Sparse Multipath Channel Capacity Estimation Based on Adaptive Array Configuration." Advanced Materials Research 765-767 (September 2013): 2728–31. http://dx.doi.org/10.4028/www.scientific.net/amr.765-767.2728.

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A virtual representation of the sparse multipath wireless channel model is proposed based on a physical wireless channel, the channel corresponds to a delay in Doppler scattering angle, uniform sampling in signal space dimensions. This virtual representation model, through the antenna array configuration extension on MIMO channel capacity was estimated. The simulation results show that the three typical antenna array configuration enough that the performance of channel optimal at all SNR conditions can be approximated, reconfigurable arrays can achieve channel capacity expansion purposes.

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8

Han, Yubing, and Jian Wang. "Adaptive Beamforming Based on Compressed Sensing with Smoothedl0Norm." International Journal of Antennas and Propagation 2015 (2015): 1–10. http://dx.doi.org/10.1155/2015/959856.

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An adaptive beamforming based on compressed sensing with smoothedl0norm for large-scale sparse receiving array is proposed in this paper. Because of the spatial sparsity of the arriving signal, compressed sensing is applied to sample received signals with a sparse array and reduced channels. The signal of full array is reconstructed by using a compressed sensing reconstruction method based on smoothedl0norm. Then an iterative linearly constrained minimum variance beamforming algorithm is adopted to form antenna beam, whose main lobe is steered to the desired direction and nulls to the directions of interferences. Simulation results and Monte Carlo analysis for linear and planar arrays show that the beam performances of our proposed adaptive beamforming are similar to those of full array antenna.

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9

Yepes, Leonardo F., David H. Covarrubias, Miguel A. Alonso, and Ramon Ferrus. "Hybrid Sparse Linear Array Synthesis Applied to Phased Antenna Arrays." IEEE Antennas and Wireless Propagation Letters 13 (2014): 185–88. http://dx.doi.org/10.1109/lawp.2014.2301012.

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10

Shi, Wanlu, Yingsong Li, Luyu Zhao, and Xiaoguang Liu. "Controllable Sparse Antenna Array for Adaptive Beamforming." IEEE Access 7 (2019): 6412–23. http://dx.doi.org/10.1109/access.2018.2889877.

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11

Geiss, Johanna, Erik Sippel, Markus Hehn, and Martin Vossiek. "Antenna Array Calibration Using a Sparse Scene." IEEE Open Journal of Antennas and Propagation 2 (2021): 349–61. http://dx.doi.org/10.1109/ojap.2021.3061935.

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12

Yoo, Junhyuk, Wonjin Sung, and In-Kyung Kim. "2D-OPC Subarray Structure for Efficient Hybrid Beamforming over Sparse mmWave Channels." International Journal of Antennas and Propagation 2021 (June 15, 2021): 1–9. http://dx.doi.org/10.1155/2021/6680566.

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Millimeter-wave (mmWave) communication is a key technology of 5G new radio (NR) mobile communication systems. Efficient beamforming using a large antenna array is important to cope with the significant path loss experienced in the mmWave spectrum. The existing fully digital beamforming scheme requires a separate radio frequency (RF) chain for each antenna, which results in an excessive hardware cost and consumption power. Under these circumstances, hybrid beamforming which approaches the performance of fully digital beamforming while reducing the complexity is a promising solution for the mmWave multiuser transmission. By extending the existing hybrid beamforming strategies, this paper proposes a novel architecture which effectively reduces the hardware cost and complexity for large antenna arrays. The proposed scheme includes multiple subarrays in the form of uniform planar array (UPA) which are allowed to be overlapped in the two-dimensional space. The corresponding antenna structure is referred to as the two-dimensional overlapped partially connected (2D-OPC) subarray structure. We evaluate the performance of the proposed scheme to suggest performance-complexity trade-offs in designing versatile antenna arrays for efficient beamforming over the mmWave channel.

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13

Liang, Lei, Yachao Jiang, Jialing Liu, Hailin Li, and Jianjiang Zhou. "Pattern Synthesis of Time-Modulated Sparse Array by an OPM-CVX Algorithm." Mathematical Problems in Engineering 2020 (April 14, 2020): 1–15. http://dx.doi.org/10.1155/2020/5491921.

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This paper addresses the constrained multiobjective optimization problem of time-modulated sparse arrays. The synthesis objective is to find an optimal element arrangement and associated excitation strategy of sparse arrays, which realize the balance of radiation power and sideband suppression performance with minimum number of elements, and suppress side lobe level simultaneously. A novel hybrid algorithm based on orthogonal perturbation method and convex optimization (OPM-CVX) for the synthesis of time-modulated sparse antenna array is presented in this paper. In order to satisfy the main lobe beamforming and side lobe suppression of sparse arrays, the proposed method optimizes element positions with minimum array numbers by orthogonal perturbation method and optimizes excitations of array element with dynamic range ratio constraint by convex optimization. Furthermore, a trapezoidal pulse time-modulated switching function is proposed to find the balance of radiation power and sideband suppression performance. The numerical results indicate that the proposed algorithm can be an effective approach for synthesis problems of time-modulated sparse arrays.

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14

Samaiyar, Aman, Dong-Chan Son, Mohamed Elmansouri, and Dejan Filipovic. "Simultaneous Transmit and Receive with Shared-Aperture Arrays." Applied Computational Electromagnetics Society 35, no. 11 (February 5, 2021): 1356–57. http://dx.doi.org/10.47037/2020.aces.j.351147.

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An approach based on shared aperture antenna array is researched for simultaneous transmit and receive (STAR) applications. The proposed configuration is a 10×10 antenna array of circularly-polarized (CP) elements with 50 elements, somewhat sparsely distributed, dedicated for Tx while the remaining elements dedicated for Rx. The high isolation is achieved between Tx and Rx elements at the expense of higher sidelobe levels, which is an inherent property of sparse antenna arrays. To demonstrate the performance of the proposed STAR configuration, numerical modelling is conducted using multilevel fast multipole method (MLFMM) solver in Altair FEKO.

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15

Chen, Zhi-Kun, Feng-Gang Yan, Xiao-Lin Qiao, and Yi-Nan Zhao. "Sparse Antenna Array Design for MIMO Radar Using Multiobjective Differential Evolution." International Journal of Antennas and Propagation 2016 (2016): 1–12. http://dx.doi.org/10.1155/2016/1747843.

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A two-stage design approach is proposed to address the sparse antenna array design for multiple-input multiple-output radar. In the first stage, the cyclic algorithm (CA) is used to establish a covariance matrix that satisfies the beam pattern approximation for a full array. In the second stage, a sparse antenna array with a beam pattern is designed to approximate the desired beam pattern. This paper focuses on the second stage. The optimization problem for the sparse antenna array design aimed at beam pattern synthesis is formulated, where the peak side lobe (PSL) is weakly constrained by the mean squared error. To solve this optimization problem, the differential evolution (DE) algorithm with multistrategy is introduced and PSL suppression is treated as an inequality constraint. However, in doing so, a new multiobjective optimization problem is created. To address this new problem, a multiobjective differential evolution algorithm based on Pareto technique is proposed. Numerical examples are provided to demonstrate the advantages of the proposed approach over state-of-the-art methods, including DE and genetic algorithm.

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16

Semenov, Aleksandr N., Vladimir I. Krainy, and Ivan A. Rodichev. "Monopulse angle estimation with MIMO radar." ITM Web of Conferences 30 (2019): 15018. http://dx.doi.org/10.1051/itmconf/20193015018.

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In this article a generalization of the amplitude monopulse method for angle estimation for radars with multiple input and multiple output (MIMO) elements is discussed. Bearing characteristics for sparse virtual antenna arrays are presented. A reconstructed image of the radiation source is presented for two cases of direction finding: based on calculation of the correlation integral and based on weighted sum of signals over the aperture of the virtual antenna array.

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17

Goswami, Sivaranjan, Kandarpa Kumar Sarma, and Kumaresh Sarmah. "Synthesis of a Sparse 2D-Scanning Array using Particle Swarm Optimization for Side-Lobe Reduction." WSEAS TRANSACTIONS ON COMMUNICATIONS 20 (August 10, 2021): 112–16. http://dx.doi.org/10.37394/23204.2021.20.14.

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Synthesis of sparse arrays is a promising area of research for a wide range of applications including radar and millimeter-wave wireless communication. The design goal of array thinning problems is to reduce the number of elements of an array without significantly affecting its performance. This work presents a technique for synthesizing a sparse phased-array antenna from a 16×16 uniform rectangular array (URA). The proposed approach reduces the number of elements by 50% without any significant increase in the peak sidelobe level (PSLL) for all possible scan angles in the azimuthal and elevation plans within a finite range of scan angles. The synthesis includes an artificial neural network (ANN) model for estimation of the excitation weights of the URA for a given scan-angle. The weights of the sparse array are computed by the Hadamard product of the weight matrix of the URA with a binary matrix that is obtained using particle swarm optimization (PSO) to minimize the PSLL.

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18

Roberts, William, Luzhou Xu, Jian Li, and Petre Stoica. "Sparse Antenna Array Design for MIMO Active Sensing Applications." IEEE Transactions on Antennas and Propagation 59, no. 3 (March 2011): 846–58. http://dx.doi.org/10.1109/tap.2010.2103550.

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19

Minvielle, Pierre, Emilia Tantar, Alexandru-Adrian Tantar, and Philippe Berisset. "Sparse Antenna Array Optimization With the Cross-Entropy Method." IEEE Transactions on Antennas and Propagation 59, no. 8 (August 2011): 2862–71. http://dx.doi.org/10.1109/tap.2011.2158941.

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20

Li, Ming, Haiping Wei, Jiahao Zhao, Qingchang Tao, and Zheng You. "A Novel Linear Sparse Array with Reconfigurable Pixel Antenna Elements." International Journal of Antennas and Propagation 2020 (April 23, 2020): 1–13. http://dx.doi.org/10.1155/2020/3624563.

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In this paper, on the basis of multifunctional reconfigurable pixel antenna (RPA) elements, a novel linear sparse array with an attractive compound reconfigurability is presented. It has the potential advantages of its beam scanning with low gain fluctuation, low sidelobe in two orthogonal planes, and polarization reconfigurable performance. Specifically, an RPA with simultaneous polarization and pattern reconstruction capabilities, consisting of the driven patch and the parasitic pixels on the same layer of dielectric substrate, is firstly designed, which can work in several operation modes corresponding to steerable beam directions θ=0°;θxoz=25°, 45°;θyoz=15° with two circular polarizations in X-band. Cross-slot coupling feed is used to improve polarization reconstruction capability and reduce the complexity of hybrid reconstruction topology optimization. Then, those RPAs are integrated into the 1×8 linear sparse array to realize the reconfiguration of two circular polarizations and beam steering in xoz- and yoz-plane. Simulation results show that the gain fluctuation and sidelobe level of the array during beam scanning have significant advantages over the previous phased array, and the generation of antenna grating lobes is avoided. Moreover, both RPA element and RPA array prototypes have been fabricated and measured to testify the efficiency. The measured results agree well with the simulated ones, which indicates the application potential in the field of modern wireless communication system of the proposed linear sparse array.

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21

Goswami, Sivaranjan, Kumaresh Sarmah, Kandarpa Kumar Sarma, and Nikos E. Mastorakis. "Synthesis of a Sparse Planar Phased Array Antenna with Reduced Side-Lobe Level and Beam-Width using Particle Swarm Optimization." International Journal of Circuits, Systems and Signal Processing 15 (September 8, 2021): 1387–93. http://dx.doi.org/10.46300/9106.2021.15.148.

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Computer aided synthesis of sparse array is a popular area of research worldwide for the application in radar and wireless communication. The trend is observing new heights with the launch of 5G millimeter wave wireless communication. A sparse array has a fewer number of elements than a conventional antenna array. In this work, a sparse array is synthesized from a 16×16 uniform rectangular array (URA). The synthesis includes an artificial neural network (ANN) model for estimation of the excitation weights of the URA for a given scan-angle. The weights of the sparse array are computed by the Hadamard product of the weight matrix of the URA with a binary matrix that is obtained using particle swarm optimization (PSO). The objective function of the optimization problem is formulated to ensure that the PSLL is minimized for multiple scan-angles. It is shown from experimental analysis that apart from minimizing the PSLL, the proposed approach yields a narrower beam-width than the original URA

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22

Zhang, Bo, Wei Liu, and Xiaoming Gou. "Compressive sensing based sparse antenna array design for directional modulation." IET Microwaves, Antennas & Propagation 11, no. 5 (January 26, 2017): 634–41. http://dx.doi.org/10.1049/iet-map.2016.0313.

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23

Wang, Xiangrong, Maria Sabrina Greco, and Fulvio Gini. "Adaptive Sparse Array Beamformer Design by Regularized Complementary Antenna Switching." IEEE Transactions on Signal Processing 69 (2021): 2302–15. http://dx.doi.org/10.1109/tsp.2021.3064183.

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24

Nikolic-Stevanovic, Marija, Jelena Dinkic, Antonije Djordjevic, Jasmin Music, and Lorenzo Crocco. "Sparse localization of breast tumors using quasi-TE polarized antennas." Facta universitatis - series: Electronics and Energetics 30, no. 2 (2017): 187–97. http://dx.doi.org/10.2298/fuee1702187n.

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We develop a three-dimensional (3D) sparse algorithm for localization of breast tumors, using an antenna array and signal processing. Assuming that the prior-knowledge of the breast tissue distribution is available, we develop a model in which the trans-polarization is fully taken into account. By considering various array configurations, we also investigate the robustness of the algorithm to the inaccuracies in the assumed electromagnetic parameters of the breast.

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Yang, Xiao Lin, and Yu Jian Cheng. "Investigation of sparse near‐field focusing array antenna with different topologies." IET Microwaves, Antennas & Propagation 13, no. 11 (March 26, 2019): 1782–87. http://dx.doi.org/10.1049/iet-map.2018.6193.

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Changzheng Ma, Tat Soon Yeo, Hwee Siang Tan, Jun Wang, and Baixiao Chen. "Three-Dimensional ISAR Imaging Using a Two-Dimensional Sparse Antenna Array." IEEE Geoscience and Remote Sensing Letters 5, no. 3 (July 2008): 378–82. http://dx.doi.org/10.1109/lgrs.2008.916071.

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Mandi Sanam, Pourya, Mohammad Javad Seyyed Talebi, Mahmoud Kazemi, Zahra Kavehvash, and Mahdi Shabany. "Thorough approach toward cylindrical MMW image reconstruction using sparse antenna array." IET Image Processing 12, no. 8 (August 1, 2018): 1458–66. http://dx.doi.org/10.1049/iet-ipr.2017.0392.

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28

Famoriji, Oluwole, Zhongxiang Zhang, Akinwale Fadamiro, Rabiu Zakariyya, and Fujiang Lin. "Planar Array Diagnostic Tool for Millimeter-Wave Wireless Communication Systems." Electronics 7, no. 12 (December 3, 2018): 383. http://dx.doi.org/10.3390/electronics7120383.

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In this paper, a diagnostic tool or procedure based on Bayesian compressive sensing (BCS) is proposed for identification of failed element(s) which manifest in millimeter-wave planar antenna arrays. With adequate a priori knowledge of the reference antenna array radiation pattern, a diagnostic problem of faulty elements was formulated. Sparse recovery algorithms, including total variation (TV), mixed ℓ 1 / ℓ 2 norm, and minimization of the ℓ 1 , are readily available in the literature, and were used to diagnose the array under test (AUT) from measurement points, consequently providing faster and better diagnostic schemes than the traditional mechanisms, such as the back propagation algorithm, matrix method algorithm, etc. However, these approaches exhibit some drawbacks in terms of effectiveness and reliability in noisy data, and a large number of measurement data points. To overcome these problems, a methodology based on BCS was adapted in this paper. From far-field radiation pattern samples, planar array diagnosis was formulated as a sparse signal recovery problem where BCS was applied to recover the locations of the faults using relevance vector machine (RVM). The resulted BCS approach was validated through simulations and experiments to provide suitable guidelines for users, as well as insight into the features and potential of the proposed procedure. A Ka-band ( 28.9 GHz ) 10 × 10 rectangular microstrip patch antenna array that emulates failure with zero excitation was designed for far-field measurements in an anechoic chamber. Both simulated and measured far-field samples were used to test the proposed approach. The proposed technique is demonstrated to detect diagnostic problems with fewer measurements provided the prior knowledge of the array radiation pattern is known, and the number of faults is relatively smaller than the array size. The effectiveness and reliability of the technique is verified experimentally and via simulation. In addition to a faster diagnosis and better reconstruction accuracy, the BCS-based technique shows more robustness to additive noisy data compared to other compressive sensing methods. The proposed procedure can be applied to next-generation transceivers, aerospace systems, radar systems, and other communication systems.

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Sandi, Efri, Ratna Addafiah, and Pitoyo Yuliatmojo. "Low-cost array antenna design for S-Band maritime radar by using sparse array method." IOP Conference Series: Materials Science and Engineering 508 (May 2, 2019): 012126. http://dx.doi.org/10.1088/1757-899x/508/1/012126.

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Cao, Zhenxin, Haiyang Geng, Zhimin Chen, and Peng Chen. "Sparse-Based Millimeter Wave Channel Estimation With Mutual Coupling Effect." Electronics 8, no. 3 (March 25, 2019): 358. http://dx.doi.org/10.3390/electronics8030358.

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The imperfection of antenna array degrades the communication performance in the millimeter wave (mmWave) communication system. In this paper, the problem of channel estimation for the mmWave communication system is investigated, and the unknown mutual coupling (MC) effect between antennas is considered. By exploiting the channel sparsity in the spatial domain with mmWave frequency bands, the problem of channel estimation is converted into that of sparse reconstruction. The MC effect is described by a symmetric Toeplitz matrix, and the sparse-based mmWave system model with MC coefficients is formulated. Then, a two-stage method is proposed by estimating the sparse signals and MC coefficients iteratively. Simulation results show that the proposed method can significantly improve the channel estimation performance in the scenario with unknown MC effect and the estimation performance for both direction of arrival (DOA) and direction of departure (DoD) can be improved by about 8 dB by reducing the MC effect about 4 dB.

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Tian, Hongliang. "The Synthesis of Sparse Antenna Array Based on Improved Mind Evolution Algorithm." International Journal of Education and Management Engineering 1, no. 5 (November 29, 2011): 1–9. http://dx.doi.org/10.5815/ijeme.2011.05.01.

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QI, Yaolong, Weixian TAN, Xueming PENG, Yanping WANG, and Wen HONG. "Application of Optimized Sparse Antenna Array in Near Range 3D Microwave Imaging." IEICE Transactions on Communications E96.B, no. 10 (2013): 2542–52. http://dx.doi.org/10.1587/transcom.e96.b.2542.

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LYULYAKIN, Andrey, Iakov CHERNYAK, and Motoyuki SATO. "Optimization of a Sparse Array Antenna for 3D Imaging in Near Range." IEICE Transactions on Electronics E102.C, no. 1 (January 1, 2019): 46–50. http://dx.doi.org/10.1587/transele.e102.c.46.

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Zhang, Bo, Wei Liu, Jingxiao Ma, Zichen Qi, Junwei Zhang, Liang Han, Yang Li, Xiaonan Zhao, Cuiping Zhang, and Cheng Wang. "Sparse Antenna Array Based Positional Modulation Design With a Low-Complexity Metasurface." IEEE Access 8 (2020): 177640–46. http://dx.doi.org/10.1109/access.2020.3027285.

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35

Wang, Xiangrong, Aboulnasr Hassanien, and Moeness G. Amin. "Sparse transmit array design for dual-function radar communications by antenna selection." Digital Signal Processing 83 (December 2018): 223–34. http://dx.doi.org/10.1016/j.dsp.2018.08.016.

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Wang, Xiangrong, and Elias Aboutanios. "Sparse array design for multiple switched beams using iterative antenna selection method." Digital Signal Processing 105 (October 2020): 102684. http://dx.doi.org/10.1016/j.dsp.2020.102684.

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Compaleo, Jacob, and Inder J. Gupta. "Spectral Domain Sparse Representation for DOA Estimation of Signals with Large Dynamic Range." Sensors 21, no. 15 (July 30, 2021): 5164. http://dx.doi.org/10.3390/s21155164.

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Recently, we proposed a Spectral Domain Sparse Representation (SDSR) approach for the direction-of-arrival estimation of signals incident to an antenna array. In the approach, sparse representation is applied to the conventional Bartlett spectra obtained from snapshots of the signals received by the antenna array to increase the direction-of-arrival (DOA) estimation resolution and accuracy. The conventional Bartlett spectra has limited dynamic range, meaning that one may not be able to identify the presence of weak signals in the presence of strong signals. This is because, in the conventional Bartlett spectra, uniform weighting (window) is applied to signals received by various antenna elements. Apodization can be used in the generation of Bartlett spectra to increase the dynamic range of the spectra. In Apodization, more than one window function is used to generate different portions of the spectra. In this paper, we extend the SDSR approach to include Bartlett spectra obtained with Apodization and to evaluate the performance of the extended SDSR approach. We compare its performance with a two-step SDSR approach and with an approach where Bartlett spectra is obtained using a low sidelobe window function. We show that an Apodization Bartlett-based SDSR approach leads to better performance with just single-step processing.

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Reinoso Chisaguano, Diego Javier, and Minoru Okada. "Low Complexity Submatrix Divided MMSE Sparse-SQRD Detection for MIMO-OFDM with ESPAR Antenna Receiver." VLSI Design 2013 (April 30, 2013): 1–11. http://dx.doi.org/10.1155/2013/206909.

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Multiple input multiple output-orthogonal frequency division multiplexing (MIMO-OFDM) with an electronically steerable passive array radiator (ESPAR) antenna receiver can improve the bit error rate performance and obtains additional diversity gain without increasing the number of Radio Frequency (RF) front-end circuits. However, due to the large size of the channel matrix, the computational cost required for the detection process using Vertical-Bell Laboratories Layered Space-Time (V-BLAST) detection is too high to be implemented. Using the minimum mean square error sparse-sorted QR decomposition (MMSE sparse-SQRD) algorithm for the detection process the average computational cost can be considerably reduced but is still higher compared with a conventional MIMOOFDM system without ESPAR antenna receiver. In this paper, we propose to use a low complexity submatrix divided MMSE sparse-SQRD algorithm for the detection process of MIMOOFDM with ESPAR antenna receiver. The computational cost analysis and simulation results show that on average the proposed scheme can further reduce the computational cost and achieve a complexity comparable to the conventional MIMO-OFDM detection schemes.

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Yang, Liu, Weidong Xiang, and Guoxin Zheng. "A Study on Vehicle Connectivity for VANETs Adopting Beamforming Antenna Array." Mathematical Problems in Engineering 2017 (2017): 1–6. http://dx.doi.org/10.1155/2017/6240984.

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An analytical mobility model based on Erlang distribution is introduced to portray sparse and dense traffic scenarios in the distributions of time headway. Upon the mobility model, the connectivity probability is then derived in two-way highway when adopting store-forward strategy. Moreover, path losses with and without beamforming antenna array are compared to further study the connectivity under different traffic density scenarios. Meanwhile, the effectiveness of beamforming technology in Vehicular Ad hoc Networks (VANETs) is investigated and concluded through analytical study and simulations.

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K., Raghu, and Prameela Kumari N. "Bayesian learning scheme for sparse DOA estimation based on maximum-a-posteriori of hyperparameters." International Journal of Electrical and Computer Engineering (IJECE) 11, no. 4 (August 1, 2021): 3049. http://dx.doi.org/10.11591/ijece.v11i4.pp3049-3058.

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In this paper, the problem of direction of arrival estimation is addressed by employing Bayesian learning technique in sparse domain. This paper deals with the inference of sparse Bayesian learning (SBL) for both single measurement vector (SMV) and multiple measurement vector (MMV) and its applicability to estimate the arriving signal’s direction at the receiving antenna array; particularly considered to be a uniform linear array. We also derive the hyperparameter updating equations by maximizing the posterior of hyperparameters and exhibit the results for nonzero hyperprior scalars. The results presented in this paper, shows that the resolution and speed of the proposed algorithm is comparatively improved with almost zero failure rate and minimum mean square error of signal’s direction estimate.

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Huang, Wei, Yongming Huang, Yong Zeng, and Luxi Yang. "Wideband Millimeter Wave Communication With Lens Antenna Array: Joint Beamforming and Antenna Selection With Group Sparse Optimization." IEEE Transactions on Wireless Communications 17, no. 10 (October 2018): 6575–89. http://dx.doi.org/10.1109/twc.2018.2860963.

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Liu, Shi Lin, Xian Qi Lin, Yu Hen Yan, and Yu Lu Fan. "Generation of a High-Gain Bidirectional Transmit–Reflect-Array Antenna With Asymmetric Beams Using Sparse-Array Method." IEEE Transactions on Antennas and Propagation 69, no. 9 (September 2021): 6087–92. http://dx.doi.org/10.1109/tap.2021.3069481.

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Li, Nan. "The Application of Sparse Antenna Array Synthesis Based on Improved Mind Evolutionary Algorithm." International Journal of Intelligent Systems and Applications 3, no. 3 (May 28, 2011): 40–46. http://dx.doi.org/10.5815/ijisa.2011.03.06.

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Cheng, Xiantao, Ying Yang, Binyang Xia, Ning Wei, and Shaoqian Li. "Sparse Channel Estimation for Millimeter Wave Massive MIMO Systems With Lens Antenna Array." IEEE Transactions on Vehicular Technology 68, no. 11 (November 2019): 11348–52. http://dx.doi.org/10.1109/tvt.2019.2938541.

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Vigano, Maria Carolina, Daniel Llorens del Rio, Frederic Bongard, and Stefano Vaccaro. "Sparse Array Antenna for Ku-Band Mobile Terminals Using 1 Bit Phase Controls." IEEE Transactions on Antennas and Propagation 62, no. 4 (April 2014): 1723–30. http://dx.doi.org/10.1109/tap.2014.2301439.

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Gabriel, W. F. "Large-aperture sparse array antenna systems of moderate bandwidth for multiple emitter location." IEEE Transactions on Antennas and Propagation 37, no. 1 (1989): 16–29. http://dx.doi.org/10.1109/8.192159.

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Liu, Linxi, Xuan Zhang, and Peng Chen. "Compressed Sensing-Based DOA Estimation With Antenna Phase Errors." Electronics 8, no. 3 (March 5, 2019): 294. http://dx.doi.org/10.3390/electronics8030294.

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In array signal processing, the direction of arrivals (DOAs) of the received signals are estimatedby measuring the relative phases among antennas; hence, the estimation performance is reducedby the inconsistency among antennas. In this paper, the DOA estimation problem of the uniformlinear array (ULA) is investigated in the scenario with phase errors among the antennas, and adiagonal matrix composed of phase errors is used to formulate the system model. Then, by using thecompressed sensing (CS) theory, we convert the DOA estimation problem into a sparse reconstructionproblem. A novel reconstruction method is proposed to estimate both the DOA and the unknownphase errors, iteratively. The phase errors are calculated by a gradient descent method with thetheoretical expressions. Simulation results show that the proposed method is cost-efficient andoutperforms state-of-the-art methods regarding the DOA estimation with unknown phase errors.

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Gu, Fufei, Long Chi, Qun Zhang, and Feng Zhu. "Single snapshot imaging method in multiple‐input multiple‐output radar with sparse antenna array." IET Radar, Sonar & Navigation 7, no. 5 (June 2013): 535–43. http://dx.doi.org/10.1049/iet-rsn.2011.0363.

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Mirza, Hamid Ali, Muhammad Asif Zahoor Raja, Naveed Ishtiaq Chaudhary, Ijaz Mansoor Qureshi, and Aqdas Naveed Malik. "A Robust Multi Sample Compressive Sensing Technique for DOA Estimation Using Sparse Antenna Array." IEEE Access 8 (2020): 140848–61. http://dx.doi.org/10.1109/access.2020.3011597.

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Bekers, Dave J., Sebastiaan Jacobs, Stefania Monni, Roland J. Bolt, Danilo Fortini, Pasquale Capece, and Giovanni Toso. "A Ka-Band Spaceborne Synthetic Aperture Radar Instrument: A modular sparse array antenna design." IEEE Antennas and Propagation Magazine 61, no. 5 (October 2019): 97–104. http://dx.doi.org/10.1109/map.2019.2932617.

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