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Electronics
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Microwave Imaging Technology
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Microwave Imaging Technology

A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Microwave and Wireless Communications".

Deadline for manuscript submissions: closed (31 October 2023) | Viewed by 3436

Special Issue Editor

Prof. Dr. Andon Lazarov

E-Mail Website1 Website2
Guest Editor
Information Department, Nikola Vaptsarov Naval Academy, 9002 Varna, Bulgaria
Interests: SAR; ISAR systems; models; imaging algorithms
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Systems that exploit reflected or absorbed electromagnetic waves from or in the object or its thermal electromagnetic emission to produce images of the observed scene and objects in it are referred to as microwave imaging systems with wide areas of applications. The penetrating properties of the electromagnetic waves define their applications, whether in content determination of multicomponent materials such as soils and minerals in the Earth, deep space investigation, medical diagnostic and therapeutic applications, or in other areas of use. The properties of the reflectivity of the electromagnetic waves are used in object detection and location, as well as object imaging through thick obstacles such as walls, on the Earth’s surface and subsurface, in the air and near space.

Microwave imaging has continued developing in both practical and theoretical directions and includes mathematical modeling, signal and image processing methods and algorithms, materials and electromagnetic and electronic devices, etc. Special attention has also been given to new radar imaging technologies as monostatic, bi-static and multi-static synthetic aperture radar systems and holographic microwave imaging systems. The main aim of this Special Issue is to collect and popularize the scientific contributions of authors from across the world working in the aforementioned areas and in all the pertinent applicative contexts that have provided recent advances in microwave imaging, including hardware design, image reconstruction methods and algorithms, as well as computational instruments and experimental verification under realistic conditions.

Topics of interest for this Special Issue include, but are not limited to:

  • Models of electromagnetic scattering emission.
  • Linear and non-linear inversion problems, methods to solve and achievable performance.
  • Passive and/or non-cooperative source microwave imaging.
  • Information theoretical approaches for data selection and performance computation.
  • SAR, ISAR, BiSAR, InSAR modeling and imaging algorithms.
  • Numerical solution of the inversion problem and efficient inversion algorithms.
  • Hardware devices for microwave imaging, antenna array in microwave imaging.
  • Experimental in situ verification.
  • Antenna deconvolution and clutter rejection for near- and very near-zone configuration.
  • Phase-only data microwave imaging.

Prof. Dr. Andon Lazarov
Guest Editor

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

  • electromagnetic inverse problems
  • microwave imaging
  • SAR/ISAR technology
  • radiometry
  • thermal passive radioemission

Published Papers (3 papers)

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Research

23 pages, 26063 KiB  
Article
Comparative Study of Sentinel-1-Focused and Simulated SAR Images Using LiDAR Point Cloud Modeling for Coastal Areas
by Haowen Jia, Pengju Yang and Rui Wu
Electronics 2023, 12(20), 4312; https://doi.org/10.3390/electronics12204312 - 18 Oct 2023
Viewed by 916
Abstract
Aiming at SAR imaging for large coastal scenes, a comprehensive comparative study is performed based on Sentinel-1 raw data, SAR imaging simulation, and Google Maps. A parallel Range-Doppler (RD) algorithm is developed and applied to focus Sentinel-1 raw data for large coastal scenes, [...] Read more.
Aiming at SAR imaging for large coastal scenes, a comprehensive comparative study is performed based on Sentinel-1 raw data, SAR imaging simulation, and Google Maps. A parallel Range-Doppler (RD) algorithm is developed and applied to focus Sentinel-1 raw data for large coastal scenes, and the focused SAR image is compared with the multi-look-processed SAR image using SNAP 9.0.0 software, as well as the corresponding areas of Google Maps. A scheme is proposed to convert the LiDAR point cloud data of the coast into a 3D coastal area digital elevation model (DEM), and a tailored 3D model suitable for RaySAR simulator is obtained after statistical outlier removal (SOR) denoising and down-sampling processing. Comparison results show good agreements, which verify the effectiveness of the parallel RD algorithm as well as the backward ray-tracing-based RaySAR simulator, which serves as a powerful SAR imaging tool due to its high efficiency and flexibility. The cosine similarity between the RaySAR-simulated SAR image and Google Maps achieves 0.93, while cosine similarity reaches 0.85 between Sentinel-1 SAR-focused images with our parallel RD algorithm and multi-look SAR image processed using SNAP software. This article can provide valuable assistance for SAR system performance evaluation, SAR imaging algorithm improvement, and remote sensing applications. Full article
(This article belongs to the Special Issue Microwave Imaging Technology)
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17 pages, 5067 KiB  
Article
Resolution-Enhanced and Accurate Cascade Time-Reversal Operator Decomposition (C-DORT) Approach for Positioning Radiated Passive Intermodulation Sources
by Zheng Guo, Zihan Cheng, Lin Chen and Deshuang Zhao
Electronics 2023, 12(9), 2104; https://doi.org/10.3390/electronics12092104 - 4 May 2023
Cited by 1 | Viewed by 987
Abstract
Attaining a high-resolution and accurate location for a radiated passive intermodulation source (R-PIMS) has been an increasingly interesting problem in modern multi-carrier wireless communication systems. For precisely positioning multiple closely spaced R-PIMSs, a novel imaging method called cascade decomposition of time-reversal operator (C-DORT) [...] Read more.
Attaining a high-resolution and accurate location for a radiated passive intermodulation source (R-PIMS) has been an increasingly interesting problem in modern multi-carrier wireless communication systems. For precisely positioning multiple closely spaced R-PIMSs, a novel imaging method called cascade decomposition of time-reversal operator (C-DORT) was developed. C-DORT constructs a new spectrum calculation by normalizing and multiplying the pseudo-spectrum at each sampled frequency together. The cascade process focuses the pseudo-spectrum at R-PIMS positions to form a highly brightened spectrum peak and to suppress the remained pseudo-spectrum to approximately zero, contributing to distinguishing the closely spaced R-PIMSs. The positioning performance of the positioning resolution, pseudo-spectrum width, positioning accuracy, and imaging robustness are analyzed by numerical simulations. Compared with the conventional central frequency decomposition of time-reversal operator (CF-DORT) and the time domain decomposition of time-reversal operator (TD-DORT) methods, the multiple R-PIMSs, spaced at a distance of diffraction limit, which is the spacing of 1/2 of a wavelength, are distinguished effectively in C-DORT. Additionally, the cross-range pseudo-spectrum full width at half maxima (CRPS-FWHM) is suppressed to the width of 1/4 of a wavelength by multiplication to improve the cross-range resolution in C-DORT. In addition, accurate positioning is obtained by providing the approximately zero positioning root mean square estimation (RMSE) at an SNR ranging from 0 dB to 10 dB. The results show that the proposed C-DORT improves the positioning accuracy and enhances the positioning resolution for locating an R-PIMS. Full article
(This article belongs to the Special Issue Microwave Imaging Technology)
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17 pages, 6276 KiB  
Article
Electromagnetic Imaging of Passive Intermodulation Sources Based on Virtual Array Expansion Synchronous Imaging Compressed Sensing
by Siyuan Liu, Musheng Liang, Zihan Cheng, Xinjie Li, Menglu Ma, Feng Liang and Deshuang Zhao
Electronics 2023, 12(7), 1653; https://doi.org/10.3390/electronics12071653 - 31 Mar 2023
Viewed by 1122
Abstract
Interference caused by passive intermodulation (PIM) has seriously affected system performance. Compressed sensing (CS) can be used to locate radial PIMs. In CS-based electromagnetic imaging methods, the ability to locate the number of targets is usually limited by the number of receiving antennas, [...] Read more.
Interference caused by passive intermodulation (PIM) has seriously affected system performance. Compressed sensing (CS) can be used to locate radial PIMs. In CS-based electromagnetic imaging methods, the ability to locate the number of targets is usually limited by the number of receiving antennas, and there are flooding problems in the imaging results. To solve these problems, traditional methods are used to increase the number of receiving antennas. To reduce the number of receiving antennas and improve the imaging effect, this paper proposes a virtual array expansion synchronous imaging compressed sensing (SI-CS) method. With the full-wave electromagnetic simulation demonstrations, the proposed method exhibits significant improvement in imaging performance compared to the conventional methods. In addition, the proposed method can discriminate between targets in the presence of the flooding problem in which the paraflap is too large and the location of the PIM source cannot be determined by the amplitude value. Full article
(This article belongs to the Special Issue Microwave Imaging Technology)
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