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Electronics
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Sparse Array Design, Processing and Application
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Sparse Array Design, Processing and Application

A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Circuit and Signal Processing".

Deadline for manuscript submissions: closed (15 April 2024) | Viewed by 6362

Special Issue Editors

Dr. Jianfeng Li

E-Mail Website
Guest Editor
1. College of Electronic and Information Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China
2. Key Laboratory of Dynamic Cognitive System of Electromagnetic Spectrum Space (Nanjing University of Aeronautics and Astronautics), Ministry of Industry and Information Technology, Nanjing 211106, China
Interests: array signal processing; direction-of-arrival estimation; source localization
Special Issues, Collections and Topics in MDPI journals
Dr. Meng Sun

E-Mail Website
Guest Editor
1. College of Electronic and Information Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China
2. Key Laboratory of Dynamic Cognitive System of Electromagnetic Spectrum Space (Nanjing University of Aeronautics and Astronautics), Ministry of Industry and Information Technology, Nanjing 211106, China
Interests: direction-of-arrival estimation; spectrum analysis

Special Issue Information

Dear Colleagues,

Antenna arrays have been used widely in the field of radar, sonar, wireless communications, and medical imaging. With the increasing demand for better spatial processing performance, the element number in antenna arrays increases greatly, which leads to massive antenna arrays. However, the adjacent distance between elements of massive antenna arrays is usually restricted to half wavelength of incoming signals, which leads to high power consumption and manufacturing costs. Compared with traditional compact antenna arrays, sparse arrays have larger array aperture, greater degrees of freedom (DOF), and smaller mutual coupling. Meanwhile, sparse arrays can achieve higher resolution and resolve more sources than that of uniform arrays with the same number of antennas.

In recent years, sparse arrays have attracted significant attention. However, there are still some problems in sparse array design, processing, and application—for example, both the array aperture and number of antennas are limited in some applications, and the impinging signals are usually correlated or even coherent due to the multipath effect.

Therefore, there are urgent requirements for the new sparse array structure and the corresponding signal processing methods in order to obtain high-precision, high-resolution, and large-capacity parameter estimation in different applications. This Special Issue invites contributions on the latest developments and advances in robust processing methods, schemes, or architectures for sparse array and its parameter estimation methods.

Topics to be covered include but are not limited to the following:

  • Sparse array design with limited array aperture and limited number of sensors;
  • Sparse array design facing multipath effect;
  • Sparse array design under array motion;
  • Sparse array design with reduced mutual coupling;
  • Direction of arrival estimation using sparse array;
  • Coherent signal processing in sparse array;
  • Multidimensional sparse arrays;
  • Distributed sparse arrays;
  • Data fusion for multiple sparse arrays;
  • Robust detection or estimation methods in sparse array radar systems.

Dr. Jianfeng Li
Dr. Meng Sun
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Electronics is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • sparse array
  • direction of arrival estimation
  • coherent signals
  • multidimension array
  • distributed array
  • array motion
  • array radar

Published Papers (6 papers)

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Research

13 pages, 342 KiB  
Article
Sparse Non-Uniform Linear Array-Based Propagator Method for Direction of Arrival Estimation
by Hanting Mo, Yi Tong, Yanjiao Wang, Kaiwei Wang, Dongxiang Luo and Wenlang Li
Electronics 2023, 12(18), 3755; https://doi.org/10.3390/electronics12183755 - 06 Sep 2023
Viewed by 734
Abstract
A novel approach that does not require the number of sources as a priori is proposed to estimate the direction of arrival (DOA) based on a sparse non-uniform linear antenna array. To ensure the identifiability of the DOA, a specific configuration scheme of [...] Read more.
A novel approach that does not require the number of sources as a priori is proposed to estimate the direction of arrival (DOA) based on a sparse non-uniform linear antenna array. To ensure the identifiability of the DOA, a specific configuration scheme of sparse array is designed. Based on this specific sparse array, firstly the fourth-order cumulant (FOC) is adopted to eliminate the impact imposed by Gaussian noise. Secondly, to circumvent eigenvalue decomposition or singular value decomposition, a propagator is constructed by using a Hermitian FOC matrix and a hyperparameter. Finally, a projection onto an irregular Toeplitz set is proposed to further improve estimation accuracy. Full article
(This article belongs to the Special Issue Sparse Array Design, Processing and Application)
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10 pages, 407 KiB  
Article
Deep Learning-Based Time Delay Estimation Using Ground Penetrating Radar
by Feng Lin, Meng Sun, Shiyu Mao and Bin Wang
Electronics 2023, 12(9), 2141; https://doi.org/10.3390/electronics12092141 - 07 May 2023
Viewed by 1265
Abstract
Time delay estimation (TDE) is of great interest for the thickness estimation of pavement using ground penetrating radar (a non-destructive testing tool that uses electromagnetic waves to probe civil engineering material), which determines the difference between the times of arrival of two incoming [...] Read more.
Time delay estimation (TDE) is of great interest for the thickness estimation of pavement using ground penetrating radar (a non-destructive testing tool that uses electromagnetic waves to probe civil engineering material), which determines the difference between the times of arrival of two incoming signals or backscattered echoes. However, conventional TDE methods suffer performance degradation because of limited resolution for thin layers and highly correlated backscattered echoes. In this paper, a deep neural network (DNN)-based TDE method is proposed. Firstly, a new DNN is constructed to classify and train the backscattered echoes; then, the time delays of the backscattered echoes can be estimated through the proposed DNN. The proposed method is based on the data processing of the backscattered echoes, which is more robust to the noise than conventional subspace-based methods (MUSIC, ESPRIT) and compressive sensing-based methods (OMP). The proposed method can directly process coherent backscattered echoes without decorrelation procedures, compared with MUSIC and ESPRIT. In addition, the proposed method is more powerful in resolving the close backscattered echoes than that of OMP. Simulation results show the efficiency of the proposed method in terms of signal-to-noise ratio (SNR) and BΔτ products. (The BΔτ products indicate the resolution of GPR, B is the frequency bandwidth of GPR and Δτ is the time delay between two incoming signals or backscattered echoes). Full article
(This article belongs to the Special Issue Sparse Array Design, Processing and Application)
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16 pages, 10028 KiB  
Article
1-Bit Hexagonal Meander-Shaped Wideband Electronically Reconfigurable Transmitarray for Satellite Communications
by Qasim Ali, Yu Xiao, Shozab Shafiq, Wenhao Tan, Waseem Shahzad, Syed Muzahir Abbas and Houjun Sun
Electronics 2023, 12(9), 1957; https://doi.org/10.3390/electronics12091957 - 22 Apr 2023
Cited by 1 | Viewed by 1206
Abstract
This paper proposes a hexagonal meander-shaped wideband electronically reconfigurable transmitarray (HMRTA) at Ku band for satellite communications and radar applications. The proposed transmitarray offers high gain, low profile, and wideband characteristics with beam-scanning and beam-forming features. The cascaded structure is a low-profile and [...] Read more.
This paper proposes a hexagonal meander-shaped wideband electronically reconfigurable transmitarray (HMRTA) at Ku band for satellite communications and radar applications. The proposed transmitarray offers high gain, low profile, and wideband characteristics with beam-scanning and beam-forming features. The cascaded structure is a low-profile and compact transmitarray. The transmitter (Tx) layer has an angular hexagonal patch with a meandered shape and resonating parasitic patches to enhance the bandwidth. The receiver (Rx) layer comprises a two-part hexagonal receiver patch and a dual ring impedance-matching receiver layer. The current reversal phenomena have executed the 180° phase shift by integrating two diodes in opposite directions. The measured results of a unit cell achieve a minimum insertion loss of 0.86 dB and 0.92 dB for state I and state II. The maximum insertion loss is 2.58 dB from 14.12 GHz to 18.02 GHz and is about 24.83% at 16.5 GHz. The full-wave simulations of a 20 × 20 space-fed reconfigurable transmitarray were performed. Good radiation patterns at all scanning angles of two principal planes are achieved, and the cross-polarization level remains less than −20 dB. The simulated 3 dB gain fluctuation bandwidth of the array is 15.85~18.35 GHz, and the wideband characteristics are verified. The simulation results show that the array can perform beam scanning ±60° in the elevation (y-z) plane and obtain the beam-scanning characteristics for ±60° in the Azimuth (x-z) plane. Full article
(This article belongs to the Special Issue Sparse Array Design, Processing and Application)
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13 pages, 8265 KiB  
Article
Comparison between Compressive Sensing and Non-Uniform Array for a MIMO GBSAR with Elevation Resolution: Simulations and Experimental Tests
by Alessandra Beni, Lapo Miccinesi and Massimiliano Pieraccini
Electronics 2023, 12(5), 1100; https://doi.org/10.3390/electronics12051100 - 23 Feb 2023
Viewed by 893
Abstract
Ground-based synthetic aperture radars (GBSAR) are popular instruments widely used for the monitoring of infrastructures. One of the main problems of ground-based interferometric radars is the elevation ambiguity. Multiple-input multiple-output (MIMO) arrays could solve this problem. This work proposes a study on possible [...] Read more.
Ground-based synthetic aperture radars (GBSAR) are popular instruments widely used for the monitoring of infrastructures. One of the main problems of ground-based interferometric radars is the elevation ambiguity. Multiple-input multiple-output (MIMO) arrays could solve this problem. This work proposes a study on possible MIMO configurations to achieve elevation resolution in ground-based radar measurements. Specifically, two array configurations are compared: a random sparse array suitable for the compressive sensing technique, and a non-uniform array. The two solutions are compared by means of simulations and experimental tests. An ad hoc system has been developed to jointly test the two configurations, and results obtained in a controlled and real urban scenario are shown. It is found that both systems are able to solve elevation ambiguity. The non-uniform array seems to achieve good performance in a general scenario, while the CS processing can outperform the other only after optimization, depending on the specific scenario and application. Full article
(This article belongs to the Special Issue Sparse Array Design, Processing and Application)
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9 pages, 2407 KiB  
Communication
A Direct Position Determination Method under Unknown Multi-Perturbation with Moving Distributed Arrays
by Qiting Zhang, Jianfeng Li, Yawei Tang, Weiming Deng and Xiaofei Zhang
Electronics 2023, 12(4), 1016; https://doi.org/10.3390/electronics12041016 - 17 Feb 2023
Cited by 1 | Viewed by 861
Abstract
Distributed array manifold perturbation, which includes synchronization errors, amplitude-phase errors, and path attenuation, has seriously degraded the accuracy of existing direct position determination (DPD) methods. In this paper, a DPD method under unknown multi-perturbation with moving distributed coprime arrays is advocated for. Firstly, [...] Read more.
Distributed array manifold perturbation, which includes synchronization errors, amplitude-phase errors, and path attenuation, has seriously degraded the accuracy of existing direct position determination (DPD) methods. In this paper, a DPD method under unknown multi-perturbation with moving distributed coprime arrays is advocated for. Firstly, by means of array position interchange, the integrated signals received from distributed arrays can be fused, which contributes to multi-position fusion. Subsequently, by resorting to the orthogonality between the noise subspace and steering vector received via distributed arrays, a quadratic optimization problem is constructed. Finally, we realize multi-parameter decoupling and achieve localization regardless of unknown perturbations. The superiority of the advocated method is substantiated from simulation examples. Full article
(This article belongs to the Special Issue Sparse Array Design, Processing and Application)
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16 pages, 3610 KiB  
Article
Triple Coprime Vector Array for DOA and Polarization Estimation: A Perspective of Mutual Coupling Isolation
by Meng Yang, Qi Yuan, Xin Lai, Beizuo Zhu and Xiaofei Zhang
Electronics 2022, 11(24), 4112; https://doi.org/10.3390/electronics11244112 - 09 Dec 2022
Viewed by 766
Abstract
Traditional polarization-sensitive sensors involve a triplet of spatially collocated, orthogonally oriented, and diversely polarized electric dipoles. However, this kind of sensor has the drawback of severe mutual coupling among the three dipoles due to the characteristic of collocation, as well as low radiation [...] Read more.
Traditional polarization-sensitive sensors involve a triplet of spatially collocated, orthogonally oriented, and diversely polarized electric dipoles. However, this kind of sensor has the drawback of severe mutual coupling among the three dipoles due to the characteristic of collocation, as well as low radiation efficiency because of the short length of the dipoles. Based on this problem, in this study we designed a new array structure called a ‘triple coprime array (TCA)’, equipped with long electric dipoles to obtain higher radiation efficiency. In this structure, the dipoles within different subarrays have orthogonal polarization modes, leading to mutual coupling isolation. The dipole interval of the subarrays is enlarged by means of a pairwise coprime relationship, which further weakens the mutual coupling effect and extends the array aperture. Simultaneously, a stable direction-of-arrival (DOA) and polarization estimation method is proposed. DOA information is accurately refined from the three subarrays without ambiguity problems, with the triple coprime characteristic improving the estimation results. Subsequently, polarization estimates can be obtained using the reconstructed model matrix and the least squares method. Numerous theoretical analyses were conducted and extensive simulation results verified the advantages of the TCA structure in mutual coupling, along with the superiority of the proposed joint DOA and polarization estimation algorithm in terms of estimation accuracy. Full article
(This article belongs to the Special Issue Sparse Array Design, Processing and Application)
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