Special Issue "Advanced Technology Related to Radar Signal, Imaging, and Radar Cross-Section Measurement"

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

Deadline for manuscript submissions: 30 April 2019

Special Issue Editors

Guest Editor
Prof. Dr. Hirokazu Kobayashi

Department of Electronics, Information and Communication Engineering, Osaka Institute of Technology, Osaka, Osaka Prefecture 535-8585, Japan
Website | E-Mail
Interests: radar imaging; inverse synthetic aperture radar; electromagnetic modeling; radar cross-section theory and measurement; radar beam scanning; radar signal processing
Guest Editor
Dr. Toshifumi Moriyama

Graduate School of Engineering, Nagasaki University, 1-14 Bunkyo-machi, Nagasaki 852-8521, Japan
Website | E-Mail
Interests: radar polarimetry; inverse scattering; microwave remote-sensing; wireless sensor networks

Special Issue Information

Dear Colleagues,

A radar system is made of many elemental and hard/software technologies. Recent applications are expanding to short distance radar, such as security, nondestructive observation, and aerial monitoring, as well as long distance radar, such as remote-sensing, surveillance, and weather observation. In these various applications, the key technologies supporting radar are essentially the signal, image, and data processing in order to detect a target more explicitly, which includes synthetic aperture imaging, compressive sensing, multiple input multiple output (MIMO) processing, and radar beam scanning, in a broad sense. On the other hand, radar cross-section (RCS) evaluation and electromagnetic modeling technologies of radar targets are also important to develop future smart radar.

The aim of this Special Issue of Electronics is to present state-of-the-art investigations in various radar-important technologies for future applications. We invite researchers to contribute original and unique articles, as well as sophisticated review articles. Topics include, but not limited to, the following areas:

  • radar imaging technology
  • inverse synthetic aperture radar imaging
  • inverse electromagnetic scattering
  • short-distance radar
  • collision-avoidance radar
  • subsurface and ground penetrating radar
  • microwave remote sensing image analysis
  • RCS near-field to far-field transformation
  • radar electromagnetic modeling and simulation
  • target recognition
  • radar data fusion

Prof. Dr. Hirokazu Kobayashi
Dr. Toshifumi Moriyama
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 papers will be 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 monthly 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 850 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

  • radar imaging technology
  • inverse synthetic aperture radar imaging
  • inverse electromagnetic scattering
  • short-distance radar
  • collision-avoidance radar
  • subsurface and ground penetrating radar
  • microwave remote sensing image analysis
  • RCS near-field to far-field transformation
  • radar electromagnetic modeling and simulation
  • target recognition
  • radar data fusion

Published Papers (4 papers)

View options order results:
result details:
Displaying articles 1-4
Export citation of selected articles as:

Research

Open AccessArticle Position Estimation of Automatic-Guided Vehicle Based on MIMO Antenna Array
Electronics 2018, 7(9), 193; https://doi.org/10.3390/electronics7090193
Received: 5 August 2018 / Revised: 4 September 2018 / Accepted: 7 September 2018 / Published: 11 September 2018
PDF Full-text (513 KB) | HTML Full-text | XML Full-text
Abstract
The existing positioning methods for the automatic guided vehicle (AGV) in the port can not achieve high location precision, Therefore, a novel multiple input multiple output (MIMO) antenna radar positioning scheme is proposed in this paper. The positioning problem for AGV is considered,
[...] Read more.
The existing positioning methods for the automatic guided vehicle (AGV) in the port can not achieve high location precision, Therefore, a novel multiple input multiple output (MIMO) antenna radar positioning scheme is proposed in this paper. The positioning problem for AGV is considered, and the joint estimation problem for direction of departure (DoD) and direction of arrival (DoA) is addressed in the multiple-input multiple-output (MIMO) radar system. With the radar detect the transponder and estimate the DoA/DoD, the relative location between the transponder and the AGV can be obtained. The corresponding Cramér–Rao lower bounds (CRLBs) for the target parameters are also derived theoretically. Finally, we compare the positioning accuracy of the traditional global position system (GPS) with the proposed MIMO radar system. Simulation results show that the proposed method can achieve better performance than the traditional GPS. Full article
Figures

Figure 1

Open AccessArticle Saliency Preprocessing Locality-Constrained Linear Coding for Remote Sensing Scene Classification
Electronics 2018, 7(9), 169; https://doi.org/10.3390/electronics7090169
Received: 30 July 2018 / Revised: 22 August 2018 / Accepted: 26 August 2018 / Published: 30 August 2018
PDF Full-text (3324 KB) | HTML Full-text | XML Full-text
Abstract
Locality-constrained Linear Coding (LLC) shows superior image classification performance due to its underlying properties of local smooth sparsity and good construction. It encodes the visual features in remote sensing images and realizes the process of modeling human visual perception of an image through
[...] Read more.
Locality-constrained Linear Coding (LLC) shows superior image classification performance due to its underlying properties of local smooth sparsity and good construction. It encodes the visual features in remote sensing images and realizes the process of modeling human visual perception of an image through a computer. However, it ignores the consideration of saliency preprocessing in the human visual system. Saliency detection preprocessing can effectively enhance a computer’s perception of remote sensing images. To better implement the task of remote sensing image scene classification, this paper proposes a new approach by combining saliency detection preprocessing and LLC. This saliency detection preprocessing approach is realized using spatial pyramid Gaussian kernel density estimation. Experiments show that the proposed method achieved a better performance for remote sensing scene classification tasks. Full article
Figures

Figure 1

Open AccessArticle Designing Constant Modulus Sequences with Good Correlation and Doppler Properties for Simultaneous Polarimetric Radar
Electronics 2018, 7(8), 153; https://doi.org/10.3390/electronics7080153
Received: 12 July 2018 / Revised: 15 August 2018 / Accepted: 17 August 2018 / Published: 20 August 2018
PDF Full-text (418 KB) | HTML Full-text | XML Full-text
Abstract
Simultaneous polarimetric radar transmits a pair of orthogonal waveforms both of which must have good auto- and cross-correlation properties. Besides, high Doppler tolerance is also required in measuring the highly maneuvering targets. A new method for the design of sequences with good correlation
[...] Read more.
Simultaneous polarimetric radar transmits a pair of orthogonal waveforms both of which must have good auto- and cross-correlation properties. Besides, high Doppler tolerance is also required in measuring the highly maneuvering targets. A new method for the design of sequences with good correlation and Doppler properties is proposed. We formulate a fourth-order polynomial, but unconstrained, minimization problem. An iterative algorithm based on the gradient method on the phases is applied to solve it. Numerical results demonstrate the superiority of the proposed algorithm compared to the previous state-of-the-art method. Full article
Figures

Figure 1

Open AccessArticle An Inverse Synthetic Aperture Ladar Imaging Algorithm of Maneuvering Target Based on Integral Cubic Phase Function-Fractional Fourier Transform
Electronics 2018, 7(8), 148; https://doi.org/10.3390/electronics7080148
Received: 11 July 2018 / Revised: 11 August 2018 / Accepted: 13 August 2018 / Published: 15 August 2018
PDF Full-text (5731 KB) | HTML Full-text | XML Full-text
Abstract
When imaging maneuvering targets with inverse synthetic aperture ladar (ISAL), dispersion and Doppler frequency time-variation exist in the range and cross-range echo signal, respectively. To solve this problem, an ISAL imaging algorithm based on integral cubic phase function-fractional Fourier transform (ICPF-FRFT) is proposed
[...] Read more.
When imaging maneuvering targets with inverse synthetic aperture ladar (ISAL), dispersion and Doppler frequency time-variation exist in the range and cross-range echo signal, respectively. To solve this problem, an ISAL imaging algorithm based on integral cubic phase function-fractional Fourier transform (ICPF-FRFT) is proposed in this paper. The accurate ISAL echo signal model is established for a space maneuvering target that quickly approximates the uniform acceleration motion. On this basis, the chirp rate of the echo signal is quickly estimated by using the ICPF algorithm, which uses the non-uniform fast Fourier transform (NUFFT) method for fast calculations. At the best rotation angle, the range compression is realized by FRFT and the range dispersion is eliminated. After motion compensation, separation imaging of strong and weak scattering points is realized by using ICPF-FRFT and CLEAN technique and the azimuth defocusing problem is solved. The effectiveness of the proposed method is verified by a simulation experiment of an aircraft scattering point model and real data. Full article
Figures

Figure 1

Back to Top