Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
7.9
5.0
Journals
Remote Sensing
Special Issues
Advanced Technologies in Small Radar Based Systems, Processing and Imaging
remotesensing-logo
Submit to Remote Sensing Review for Remote Sensing Propose a Special Issue

Journal Menu

► Journal Menu

Journal Browser

► Journal Browser
share announcement

Advanced Technologies in Small Radar Based Systems, Processing and Imaging

A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Remote Sensing Image Processing".

Deadline for manuscript submissions: closed (31 October 2022) | Viewed by 2105

Special Issue Editor

Prof. Dr. Dusan Gleich

E-Mail Website
Guest Editor
Faculty of Electrical Engineering and Computer Science, University of Maribor, Koroška cesta 46, SI-2000 Maribor, Slovenia
Interests: synthetic aperture radar image enhancement; small-radar development; deep learning for SAR image enhancement; data interpretation, short-range radar development, radar signal processing, through the wall imaging, soil moisture estimation, and machine vision
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Through the rapid development of range imaging sensors and new signal processing techniques for radar data processing and radar data interpretation, miniature radar systems, applied in environmental monitoring, can form air underwater using unnamed aerial vehicles platforms, ground vehicles or even remote sensing. Therefore, advances in miniature radar design, radar processing and radar data interpretation have received great interest due to their great potential for environmental monitoring. The latest advances in radar design focus on a low consumption, combining lidar and radar technologies, and using deep learning in the process of radar image formation and data interpretation.

This Special Issue aims to present the latest research and application results for the field of advanced small-radar design, radar processing techniques and intelligent radar data interpretation techniques used in the remote sensing.

For this Special Issue, we welcome contributions that focus on, but are rnot limited to, the following:

  • Novel small-radar designs attached to UAV;
  • Small-radar systems used for environment monitoring;
  • GPR data processing and analysis;
  • Deep learning, architectures, and convolutional neural networks for data interpretation and image formation;
  • Improvements in information interpretation using deep learning model capabilities;
  • Machine learning techniques for radar data classification and information extraction;
  • Physical parameter extraction from radar data using inversion methods or deep learning;
  • Software-defined radio used for environment monitoring;
  • THz radars for material classification;
  • Antenna design for small radars;
  • Systems and methods for land mine detection.

Prof. Dr. Dusan Gleich
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. Remote Sensing 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 2700 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

  • ground-penetrating radar
  • UAV
  • small-radar design
  • radar image formation
  • deep learning
  • classification of radar images
  • object detection in radar imaging
  • antenna design for small radars
  • THz radars for material classification

Published Papers (1 paper)

Order results
Result details
Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:

Other

16 pages, 6570 KiB  
Technical Note
Near-Field 3D Sparse SAR Direct Imaging with Irregular Samples
by Shiqi Xing, Shaoqiu Song, Sinong Quan, Dou Sun, Junpeng Wang and Yongzhen Li
Remote Sens. 2022, 14(24), 6321; https://doi.org/10.3390/rs14246321 - 13 Dec 2022
Cited by 4 | Viewed by 1546
Abstract
Sparse imaging is widely used in synthetic aperture radar (SAR) imaging. Compared with the traditional matched filtering (MF) methods, sparse SAR imaging can directly image the scattered points of a target and effectively reduce the sidelobes and clutter in irregular samples. However, in [...] Read more.
Sparse imaging is widely used in synthetic aperture radar (SAR) imaging. Compared with the traditional matched filtering (MF) methods, sparse SAR imaging can directly image the scattered points of a target and effectively reduce the sidelobes and clutter in irregular samples. However, in view of the large-scale computational complexity of sparse reconstruction with raw echo data, traditional sparse reconstruction algorithms often require huge computational expense. To solve the above problems, in this paper, we propose a 3D near-field sparse SAR direct imaging algorithm for irregular trajectories, adopting a piece of preliminary information in the SAR image to update the dictionary matrix dimension, using the Gaussian iterative method, and optimizing the signal-processing techniques, which can achieve 3D sparse reconstruction in a more direct and rapid manner. The proposed algorithm was validated through simulations and empirical study of irregular scanning scenarios and compared with traditional MF and sparse reconstruction methods, and was shown to significantly reduce the computation time and effectively preserve the complex information of the scenes to achieve high-resolution image reconstruction. Full article
(This article belongs to the Special Issue Advanced Technologies in Small Radar Based Systems, Processing and Imaging)
►▼ Show Figures

Figure 1

Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:
 
Displaying articles 1-1
Back to TopTop