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Physics-Informed Information Exploitation in Radar Remote Sensing

A Special Issue of Remote Sensing (ISSN 2072-4292) belonging to the section "Engineering Remote Sensing".

Deadline for manuscript submissions: 28 February 2027 | Viewed by 295

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Guest Editor
School of Information and Electronics, Beijing Institute of Technology, Beijing 100081, China
Interests: radar signal processing; space target detection and imaging; space situational awareness; ISAR/InISAR imaging
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
Department of Electronic Electrical and Systems Engineering, University of Birmingham, Birmingham, UK
Interests: SAR/ISAR imaging and their applications in millimeter-wave and terahertz radar systems
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Driven by the growing demand for extracting complex physical characteristics, target detection, recognition, and tracking in radar remote sensing have evolved from acquiring basic attributes such as position, velocity, and shape to retrieving sophisticated target physical properties. The application of novel radar architectures and advanced processing techniques has unlocked unprecedented potential for radar remote sensing technology, while traditional data-driven methods often lack physical interpretability and robustness in complex scenarios.

The primary focus of this Special Issue is to explore how to leverage radar system architectures, signal characteristics, and target physical properties to fully exploit deep-seated information such as scattering mechanisms, comprehensive motion signatures, fine target structures, symmetry/asymmetry features, working states, and mission intentions, as well as the spatiotemporal evolution characteristics of all these features, and conversely, how to utilize prior physical information of targets to optimize radar systems, signal processing, and sensing strategies, and overall remote sensing performance in complex scenarios.

Suggested themes: Physics-based remote sensing models, feature-based signal processing, multi-source information fusion, physical property retrieval, remote sensing performance optimization, complex scenario adaptation.

Article types: Original research papers, review articles, short communications, and technical notes.

Dr. Junling Wang
Dr. Bangjie Zhang
Guest Editors

Manuscript Submission Information

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Keywords

  • physics-based remote sensing models
  • novel radar architectures
  • scattering mechanisms
  • feature-based signal processing
  • multi-source information fusion
  • motion-constrained target detection and tracking
  • information-constrained target recognition
  • physical property retrieval
  • spatiotemporal feature correlation
  • feature-based performance optimization

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Published Papers (1 paper)

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Research

32 pages, 44743 KB  
Article
Exploiting Projection Trajectories Discrepancy for Multipath Suppression and Detailed Feature Extraction of Buildings in SAR Adjacent Sub-Aperture Images
by Yi Zhang, Daoxiang An, Di Wang, Jinxing Li and Leping Chen
Remote Sens. 2026, 18(18), 3164; https://doi.org/10.3390/rs18183164 - 15 Sep 2026
Abstract
In synthetic aperture radar (SAR) imagery of built-up areas, multipath effects generate false targets that closely resemble genuine structural features, severely hindering refined interpretation of building structures. Existing methods based on interferometric SAR, tomographic SAR, or full-angle circular SAR (CSAR), while effective in [...] Read more.
In synthetic aperture radar (SAR) imagery of built-up areas, multipath effects generate false targets that closely resemble genuine structural features, severely hindering refined interpretation of building structures. Existing methods based on interferometric SAR, tomographic SAR, or full-angle circular SAR (CSAR), while effective in 3D information extraction, impose stringent requirements on radar systems, data acquisition conditions, and prior information, rendering them less applicable to time-critical scenarios with limited observation constraints. To address this issue, this paper proposes a multipath suppression and detailed feature extraction method for buildings based on projection offset discrepancies across adjacent sub-aperture images. First, a projection offset model for elevated target points and a multipath effect model between elevated targets are established, theoretically revealing that the projections of elevated targets and multipath ghosts are offset to opposite sides of the target in successive sub-aperture images. Building upon this theoretical foundation, a complete image-domain processing pipeline is developed: an improved iterative watershed algorithm for robust building region segmentation, non-edge Hough transform combined with Thresholded Connected Component Analysis clustering for wall line extraction, multi-dimensional feature-based Hungarian algorithm for wall matching and tracking across sub-apertures, and normalized cross-correlation (NCC) for pixel-level offset estimation. Based on the distinct offset characteristics, building structures are categorized into three classes—stationary walls, elevated structures, and multipath ghosts—enabling simultaneous multipath suppression and structural extraction. Experimental results on Ku-band UAV-borne circular SAR data demonstrate that the proposed method requires only a small number of sub-aperture images with narrow angular spans to effectively distinguish different scattering structures, suppress multipath ghosts, and extract major structural details, providing a viable solution for building interpretation in SAR imagery under observation-constrained scenarios. Full article
(This article belongs to the Special Issue Physics-Informed Information Exploitation in Radar Remote Sensing)
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