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Advances in SAR: Sensors, Methodologies, and Applications II

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

Deadline for manuscript submissions: closed (31 August 2023) | Viewed by 9839

Special Issue Editors


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Guest Editor
Surrey Space Centre, Department of Electrical and Electronic Engineering, Faculty of Engineering and Physical Sciences, University of Surrey, Guildford GU1 3LY, UK
Interests: remote sensing; synthetic aperture radar; maritime surveillance; disaster monitoring
Special Issues, Collections and Topics in MDPI journals

E-Mail Website
Guest Editor
Surrey Space Centre, Department of Electrical and Electronic Engineering, Faculty of Engineering and Physical Sciences, University of Surrey, Guildford GU1 3LY, UK
Interests: synthetic aperture radar; automatic identification system; maritime domain awareness; data association

Special Issue Information

Dear Colleagues,

Synthetic Aperture Radar (SAR) is a rapidly growing remote sensing research area encompassing various related fields. The historical barriers previously preventing the widespread use of SAR data—the cost and the complexity of SAR image processing—have been overcome thanks to open source policies, new commercial constellations and educational efforts aimed at filling an important skills gap. As a result, SAR has been increasingly adopted in modeling and monitoring Earth’s resources and processes, as well as in operational environments to ensure early warnings, detection and surveillance.

This Special Issue hopes to capture the richness, variety and impact of the latest research in SAR, from technology advancements enabling the development of high-spatial-resolution-based applications to constellations and swarms providing high revisit times, as well as improvements in well-established techniques and new methodologies in data processing and applications.

Papers focusing on the following areas are welcome:

  • SAR sensors and systems;
  • SAR missions, swarms and constellations (both SAR-based only and multi-source);
  • SAR techniques (interferometry, polarimetry, tomography etc.);
  • SAR signal and image processing;
  • SAR applications (from disaster monitoring to surveillance and security, land classification, etc.)
  • Data fusion methodologies with SAR data.

Dr. Raffaella Guida
Dr. Maximilian Rodger
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 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

  • synthetic aperture radar
  • sensors
  • missions
  • techniques
  • signal processing
  • image processing
  • applications

Published Papers (8 papers)

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Research

14 pages, 2467 KiB  
Article
An Enhanced Saline Soil Dielectric Constant Model Used for Remote Sensing Soil Moisture and Salinity Retrieval
by Liang Gao, Xiaoning Song, Xiaotao Li, Jianwei Ma, Pei Leng, Weizhen Wang and Xinming Zhu
Remote Sens. 2024, 16(3), 452; https://doi.org/10.3390/rs16030452 - 24 Jan 2024
Viewed by 672
Abstract
The soil dielectric constant model is essential for retrieving soil properties based on microwave remote sensing. However, the existing saline soil dielectric constant models perform poorly in simulating the dielectric constant of soil with high water content and salinity. In this study, the [...] Read more.
The soil dielectric constant model is essential for retrieving soil properties based on microwave remote sensing. However, the existing saline soil dielectric constant models perform poorly in simulating the dielectric constant of soil with high water content and salinity. In this study, the Wang Yueru (WYR) saline soil dielectric constant model, which was demonstrated to perform well in describing the effect of salinity and moisture on the dielectric constant, was validated based on experimental measurements of soil samples under different water content and salinity degrees. Furthermore, we adjusted the model form, refitted the empirical coefficient in the model, and finally acquired a two-stage model for simulating the soil dielectric constant. The enhanced model was validated under different soil moisture and salinity ranges using experimental measurements of soil samples. Compared to the original model, the proposed model exhibits a larger improvement in simulating the soil dielectric constant, and the RMSE of the simulated results dramatically decreased from 7.3 to 1.6, especially for soil with high salinity and water content. On this basis, a model suitable for L-band microwave was established. This model is of great significance for studying soil dielectric characteristics and retrieving soil parameters based on L-band data. Furthermore, this model can be used to retrieve soil salinity and water content using microwave remote sensing under a broadened application situation, such as in saline-alkali soils, wetlands, and salt marshes. Full article
(This article belongs to the Special Issue Advances in SAR: Sensors, Methodologies, and Applications II)
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20 pages, 6432 KiB  
Article
A Multi-Domain Joint Novel Method for ISAR Imaging of Multi-Ship Targets
by Yangyang Zhang, Ning Xu, Ning Li and Zhengwei Guo
Remote Sens. 2023, 15(19), 4878; https://doi.org/10.3390/rs15194878 - 08 Oct 2023
Cited by 1 | Viewed by 893
Abstract
As a key object on the ocean, regulating civilian and military ship targets more effectively is a very important part of maintaining maritime security. One of the ways to obtain high-resolution images of ship targets is the inverse synthetic aperture radar (ISAR) imaging [...] Read more.
As a key object on the ocean, regulating civilian and military ship targets more effectively is a very important part of maintaining maritime security. One of the ways to obtain high-resolution images of ship targets is the inverse synthetic aperture radar (ISAR) imaging technique. However, in the actual ISAR imaging process, ship targets in a formation often lead to complicated motion conditions. Due to the close distance between the ship targets, the rough imaging results of the targets cannot be completely separated in the image domain, and the small differences in motion parameters lead to overlapping phenomena in the Doppler history. Therefore, for situations in which ship formation targets with little difference in motion parameters are included in the same radar beam, this paper proposes a multi-domain joint ISAR separation imaging method for multi-ship targets. First, the method performs echo separation using the Hough transform (HT) with the minimum entropy autofocus method in the image domain. Secondly, the time–frequency curve is extracted in the time–frequency domain using the short-time Fourier transform (STFT) for time–frequency analysis, which solves the problem of the ship formation targets being aliased on both echo and Doppler history after range compression and achieves the purpose of separating the echo signals of the sub-ship targets with high accuracy. Eventually, better-focused images of each target are obtained via further motion compensation and precise imaging. Finally, the effectiveness of the proposed method is verified using a simulation and measured data. Full article
(This article belongs to the Special Issue Advances in SAR: Sensors, Methodologies, and Applications II)
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26 pages, 20702 KiB  
Article
DSF-Net: A Dual Feature Shuffle Guided Multi-Field Fusion Network for SAR Small Ship Target Detection
by Zhijing Xu, Jinle Zhai, Kan Huang and Kun Liu
Remote Sens. 2023, 15(18), 4546; https://doi.org/10.3390/rs15184546 - 15 Sep 2023
Cited by 1 | Viewed by 1227
Abstract
SAR images play a crucial role in ship detection across diverse scenarios due to their all-day, all-weather characteristics. However, detecting SAR ship targets poses inherent challenges due to their small sizes, complex backgrounds, and dense ship scenes. Consequently, instances of missed detection and [...] Read more.
SAR images play a crucial role in ship detection across diverse scenarios due to their all-day, all-weather characteristics. However, detecting SAR ship targets poses inherent challenges due to their small sizes, complex backgrounds, and dense ship scenes. Consequently, instances of missed detection and false detection are common issues. To address these challenges, we propose the DSF-Net, a novel framework specifically designed to enhance small SAR ship detection performance. Within this framework, we introduce the Pixel-wise Shuffle Attention module (PWSA) as a pivotal step to strengthen the feature extraction capability. To enhance long-range dependencies and facilitate information communication between channels, we propose a Non-Local Shuffle Attention (NLSA) module. Moreover, NLSA ensures the stability of the feature transfer structure and effectively addresses the issue of missed detection for small-sized targets. Secondly, we introduce a novel Triple Receptive Field-Spatial Pyramid Pooling (TRF-SPP) module designed to mitigate the issue of false detection in complex scenes stemming from inadequate contextual information. Lastly, we propose the R-tradeoff loss to augment the detection capability for small targets, expedite training convergence, and fortify resistance against false detection. Quantitative validation and qualitative visualization experiments are conducted to substantiate the proposed assumption of structural stability and evaluate the effectiveness of the proposed modules. On the LS-SSDDv1.0 dataset, the mAP5095 demonstrates a remarkable improvement of 8.5% compared to the baseline model. The F1 score exhibits a notable enhancement of 6.9%, surpassing the performance of advanced target detection methods such as YOLO V8. Full article
(This article belongs to the Special Issue Advances in SAR: Sensors, Methodologies, and Applications II)
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21 pages, 10813 KiB  
Article
High-Resolution and Wide-Swath 3D Imaging for Urban Areas Based on Distributed Spaceborne SAR
by Yaqian Yang, Fubo Zhang, Ye Tian, Longyong Chen, Robert Wang and Yirong Wu
Remote Sens. 2023, 15(16), 3938; https://doi.org/10.3390/rs15163938 - 09 Aug 2023
Cited by 2 | Viewed by 992
Abstract
Tomographic synthetic aperture radar (TomoSAR) obtains elevation resolution by adding multiple baselines successively in the direction perpendicular to the line of sight, thereby realizing three-dimensional (3D) reconstruction of complex scenes and significantly promoting the development of the 3D application field. However, a large [...] Read more.
Tomographic synthetic aperture radar (TomoSAR) obtains elevation resolution by adding multiple baselines successively in the direction perpendicular to the line of sight, thereby realizing three-dimensional (3D) reconstruction of complex scenes and significantly promoting the development of the 3D application field. However, a large data redundancy and long mapping time in traditional 3D imaging lead to a large data transmission burden, low efficiency, and high costs. To solve the above problems, this paper proposes a distributed SAR high-resolution and wide-swath (HRWS) 3D imaging technology scheme. The proposed scheme overcomes the size limitation of traditional single-satellite antennas through the multi-channel arrangement of multiple satellites in the elevation direction to achieve HRWS imaging; meanwhile, the distributed SAR system is integrated with tomographic processing technology to realize 3D imaging of difficult areas by using the elevation directional resolution of TomoSAR systems. HRWS 3D SAR increases the baseline length and channel number by transmission in turn, which leads to excessive pulse repetition frequency and causes echoes of different pulse signals to overlap in the same receiving cycle, resulting in range ambiguity and thus seriously affecting the quality of the 3D reconstruction. To solve this problem, this paper proposes a range ambiguity resolution algorithm based on multi-beam forming and verifies it on the measured data from airborne array SAR. Compared with the traditional TomoSAR, the distributed HRWS 3D SAR scheme proposed in this paper can obtain a greater mapping bandwidth with the same resolution in a single flight, thereby enhancing the time correlation, reducing data redundancy, and greatly improving mapping efficiency. Full article
(This article belongs to the Special Issue Advances in SAR: Sensors, Methodologies, and Applications II)
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24 pages, 4258 KiB  
Article
An Improved UAV Bi-SAR Imaging Algorithm with Two-Dimensional Spatial Variant Range Cell Migration Correction and Azimuth Non-Linear Phase Equalization
by Junjie Yan, Linghao Li, Han Li, Meng Ke, Xinnong Ma and Xinshuai Sun
Remote Sens. 2023, 15(15), 3734; https://doi.org/10.3390/rs15153734 - 27 Jul 2023
Viewed by 790
Abstract
The transmitter and receiver of unmanned aerial vehicle (UAV) bistatic synthetic aperture radar (Bi-SAR) are respectively carried on different UAV platforms, which has the advantages of flexible movement and strong concealment, and has broad application prospects in remote sensing fields. However, the range [...] Read more.
The transmitter and receiver of unmanned aerial vehicle (UAV) bistatic synthetic aperture radar (Bi-SAR) are respectively carried on different UAV platforms, which has the advantages of flexible movement and strong concealment, and has broad application prospects in remote sensing fields. However, the range cell migration (RCM) and azimuth non-linear phase (ANP) of UAV Bi-SAR are seriously spatially variant along the range and azimuth directions, while the UAV Bi-SAR has a short operating range, complex trajectory and wide azimuth beam. Aiming at the problem that the RCM and ANP of UAV Bi-SAR in spotlight mode are difficult to correct and equalize due to the severe two-dimensional (2D) spatial variation, an RCM correction (RCMC) and ANP equalization (ANPE) method based on Doppler domain blocking is proposed. First, the azimuth spatial variance of RCM is eliminated by Doppler blocking, and the range spatial variant RCMC is realized by RNCS. Second, by combining Doppler blocking with azimuth nonlinear chirp scaling (ANCS), this method can adapt to ANPE with larger width and more severe spatial variation. At last, the criteria of Doppler blocking are given in detail, and the effectiveness of the proposed method is verified by UAV Bi-SAR real data and computer simulation. Full article
(This article belongs to the Special Issue Advances in SAR: Sensors, Methodologies, and Applications II)
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26 pages, 25669 KiB  
Article
P-Band UAV-SAR 4D Imaging: A Multi-Master Differential SAR Tomography Approach
by Zhen Wang, Yangkai Wei, Zegang Ding, Jian Zhao, Tao Sun, Yan Wang, Han Li and Tao Zeng
Remote Sens. 2023, 15(9), 2459; https://doi.org/10.3390/rs15092459 - 07 May 2023
Cited by 1 | Viewed by 1523
Abstract
Due to its rapid deployment, high-flexibility, and high-accuracy advantages, the unmanned-aerial-vehicle (UAV)-based differential synthetic aperture radar (SAR) tomography (D-TomoSAR) technique presents an attractive approach for urban risk monitoring. With its sufficiently long spatial and temporal baselines, it offers elevation and velocity resolution beyond [...] Read more.
Due to its rapid deployment, high-flexibility, and high-accuracy advantages, the unmanned-aerial-vehicle (UAV)-based differential synthetic aperture radar (SAR) tomography (D-TomoSAR) technique presents an attractive approach for urban risk monitoring. With its sufficiently long spatial and temporal baselines, it offers elevation and velocity resolution beyond the dimensions of range and azimuth, enabling four-dimensional (4D) SAR imaging. In the case of P-band UAV-SAR, a long spatial-temporal baseline is necessary to achieve high enough elevation-velocity dimensional resolution. Although P-band UAV-SAR maintains temporal coherence, it still faces two issues due to the extended spatial baseline, i.e., low spatial coherence and high sidelobes. To tackle these problems, we introduce a multi-master (MM) D-TomoSAR approach, contributing three main points. Firstly, the traditional D-TomoSAR signal model is extended to a MM one, which improves the average coherence coefficient and the number of baselines (NOB) as well as suppresses sidelobes. Secondly, a baseline distribution optimization processing is proposed to equalize the spatial–temporal baseline distribution, achieve more uniform spectrum samplings, and reduce sidelobes. Thirdly, a clustering-based outlier elimination method is employed to ensure 4D imaging quality. The proposed method is effectively validated through computer simulation and P-band UAV-SAR experiment. Full article
(This article belongs to the Special Issue Advances in SAR: Sensors, Methodologies, and Applications II)
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23 pages, 23025 KiB  
Article
Extraction and Analysis of Radar Scatterer Attributes for PAZ SAR by Combining Time Series InSAR, PolSAR, and Land Use Measurements
by Ling Chang, Anurag Kulshrestha, Bin Zhang and Xu Zhang
Remote Sens. 2023, 15(6), 1571; https://doi.org/10.3390/rs15061571 - 13 Mar 2023
Cited by 2 | Viewed by 1491
Abstract
Extracting meaningful attributes of radar scatterers from SAR images, PAZ in our case, facilitates a better understanding of SAR data and physical interpretation of deformation processes. The attribute categories and attribute extraction method are not yet thoroughly investigated. Therefore, this study recognizes three [...] Read more.
Extracting meaningful attributes of radar scatterers from SAR images, PAZ in our case, facilitates a better understanding of SAR data and physical interpretation of deformation processes. The attribute categories and attribute extraction method are not yet thoroughly investigated. Therefore, this study recognizes three attribute categories: geometric, physical, and land-use attributes, and aims to design a new scheme to extract these attributes of every coherent radar scatterer. Specifically, we propose to obtain geometric information and its dynamics over time of the radar scatterers using time series InSAR (interferometric SAR) techniques, with SAR images in HH and VV separately. As all InSAR observations are relative in time and space, we convert the radar scatterers in HH and VV to a common reference system by applying a spatial reference alignment method. Regarding the physical attributes of the radar scatterers, we first employ a Random Forest classification method to categorize scatterers in terms of scattering mechanisms (including surface, low-, high-volume, and double bounce scattering), and then assign the scattering mechanism to every radar scatterer. We propose using a land-use product (i.e., TOP10NL data for our case) to create reliable labeled samples for training and validation. In addition, the radar scatterers can inherit land-use attributes from the TOP10NL data. We demonstrate this new scheme with 30 Spanish PAZ SAR images in HH and VV acquired between 2019 and 2021, covering an area in the province of Friesland, the Netherlands, and analyze the extracted attributes for data and deformation interpretation. Full article
(This article belongs to the Special Issue Advances in SAR: Sensors, Methodologies, and Applications II)
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21 pages, 7762 KiB  
Article
Lightweight SAR: A Two-Bit Strategy
by Shiqi Liu, Bo Zhao, Lei Huang, Bing Li and Weimin Bao
Remote Sens. 2023, 15(2), 310; https://doi.org/10.3390/rs15020310 - 05 Jan 2023
Cited by 1 | Viewed by 1463
Abstract
By benefiting from one-bit sampling, the system deployment of synthetic aperture radar (SAR) can be greatly simplified. However, it usually requires a high oversampling rate to avoid the apparent degradation in imagery, which counteracts the storage-saving advantages. In this paper, a two-bit lightweight [...] Read more.
By benefiting from one-bit sampling, the system deployment of synthetic aperture radar (SAR) can be greatly simplified. However, it usually requires a high oversampling rate to avoid the apparent degradation in imagery, which counteracts the storage-saving advantages. In this paper, a two-bit lightweight SAR imaging strategy is proposed to take the advantage of one-bit quantization in simplification but get rid of the requirement of sampling at a high rate. Specifically, based on one-bit quantization, an extra bit after an appropriate phase shifting is introduced to suppress the harmonics resulting from the nonlinear effect of quantization. In this way, the awkward nonlinearity in conventional one-bit schemes can be tackled by the nonlinearity generated with the newly introduced bit. Hence, this improves the imaging quality. In addition, the proposed method does not rely on fast sampling. The harmonic suppression effect is retained under low-sampling-rate conditions. Therefore, the amount of data acquired will decrease dramatically. This will benefit the whole process of imaging and, consequently, lighten the system burden and cost. The theoretical analysis and experimental results showcase the superiority of the proposed method. Full article
(This article belongs to the Special Issue Advances in SAR: Sensors, Methodologies, and Applications II)
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