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Special Issue "Applications of Synthetic Aperture Radar (SAR) in Target Detection"

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

Deadline for manuscript submissions: 30 November 2023 | Viewed by 577

Special Issue Editors

“Alessandro Faedo” Institute of Information Science and Technologies (ISTI), National Research Council (CNR), Pisa, Italy
Interests: image analysis; signal analysis; patter recognition
MARUM, Center for Marine Environmental Sciences, University of Bremen, 28359 Bremen, Germany
Interests: synthetic aperture radar; oceanography; signal processing; image processing; pollution and target detection
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Synthetic aperture radar (SAR) is a highly flexible radar system which can obtain medium- to high-resolution images of large areas of Earth. Spaceborne or airborne SAR can be operated all day and almost independently of weather conditions. Due to these advantages, it has been widely used in various areas of aviation and aerospace Earth observation and intelligence reconnaissance, as well as environmental remote sensing and resource exploration.

The detection and tracking of SAR targets have been the subject of long-term research in the field of SAR; however, due to the complexity of target characteristics and interference from the surrounding environment, the detection and tracking of SAR targets face significant challenges. With improvements in the resolution, noise, geolocation and image quality in the latest SAR system, there is more room for research on the applications of synthetic aperture radar in target detection.

This Special Issue of Remote Sensing, “Applications of Synthetic Aperture Radar (SAR) in Target Detection”, is dedicated to the recent advances, challenges and future research priorities in the study of synthetic aperture radar (SAR) technology and its applications in target detection, with an emphasis on the following topics:

  • SAR target modeling;
  • SAR clutter and interference suppression techniques;
  • SAR target detection and tracking in the environment;
  • SAR target detection and tracking in resource exploration.

Dr. Marco Righi
Dr. Domenico Velotto
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at 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.


  • object/target detection and tracking
  • SAR image processing
  • micro-Doppler signatures

Published Papers (1 paper)

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Inshore Ship Detection Based on Multi-Modality Saliency for Synthetic Aperture Radar Images
Remote Sens. 2023, 15(15), 3868; - 04 Aug 2023
Viewed by 430
Synthetic aperture radar (SAR) ship detection is of significant importance in military and commercial applications. However, a high similarity in intensity and spatial distribution of scattering characteristics between the ship target and harbor facilities, along with a fuzzy sea-land boundary due to the [...] Read more.
Synthetic aperture radar (SAR) ship detection is of significant importance in military and commercial applications. However, a high similarity in intensity and spatial distribution of scattering characteristics between the ship target and harbor facilities, along with a fuzzy sea-land boundary due to the strong speckle noise, result in a low detection accuracy and high false alarm rate for SAR ship detection with complex inshore scenes. In this paper, a new inshore ship detection method based on multi-modality saliency is proposed to overcome these challenges. Four saliency maps are established from different perspectives: an ocean-buffer saliency map (OBSM) outlining more accurate coastline under speckle noises; a local stability saliency map (LSSM) addressing pixel spatial distribution; a super-pixel saliency map (SPSM) extracting critical region-based features for inshore ship detection; and an intensity saliency map (ISM) to highlight target pixels with intensity distribution. By combining these saliency maps, ship targets in complex inshore scenes can be successfully detected. The method provides a novel interdisciplinary perspective (surface metrology) for SAR image segmentation, discovers the difference in spatial characteristics of SAR image elements, and proposes a novel robust CFAR procedure for background clutter fitting. Experiments on a public SAR ship detection dataset (SSDD) shows that our method achieves excellent detection performance, with a low false alarm rate, in offshore scenes, inshore scenes, inshore scenes with confusing metallic port facilities, and large-scale scenes. The results outperform several widely used methods, such as CFAR-based methods and super-pixel methods. Full article
(This article belongs to the Special Issue Applications of Synthetic Aperture Radar (SAR) in Target Detection)
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