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Processing Methods and Techniques of Spaceborne SAR with Ultra-High Resolution

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

Deadline for manuscript submissions: closed (31 August 2026) | Viewed by 8471

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Editors

Prof. Dr. Guangcai Sun

E-Mail Website
Guest Editor

School of Electronic Engineering, Xidian University, Xi’an 710071, China
Interests: synthetic apeture radar (SAR) imaging; real-time radar imaging processor; SAR image processing
Special Issues, Collections and Topics in MDPI journals

Dr. Wenkang Liu

E-Mail Website
Guest Editor

Academy of Advanced Interdisciplinary Research, Xidian University, Xi’an, 710071, China
Interests: spaceborne SAR processing techniques; design novel spaceborne radar systems; interdisciplinary remote sensing

Prof. Dr. Vito Pascazio

E-Mail Website
Guest Editor

Dipartimento di Ingegneria, Università degli Studi di Napoli “Parthenope”, 80143 Napoli, Italy
Interests: synthetic aperture radar (SAR) image processing; SAR interferometry; SAR tomography; GB-SAR; ground penetrating radars; through-the-wall imaging, and deep learning techniques to radar and remote sensing imaging
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

In recent years, advanced spaceborne SAR missions have exploited the limits of their capabilities in achieving higher resolution. However, the lengthened synthetic aperture time generally exaggerates the orbit curvature and introduces strong spatial variance into the signals, which significantly increases the complexity of the processing techniques. In particular, the focusing quality of spaceborne ultra-high-resolution (UHR) SAR is severely dependent on the topography. Therefore, the requirements on the DEM quality to assist the accommodation as well as specifically designed accommodation methods need to be addressed to assure well focusing. Ultra-high resolution also poses a challenge to interferometric applications due to the difficulties associated with co-registration, caused by its sensitivity to fluctuating terrains. Moreover, spaceborne UHR SAR faces a large processing burden due to the significant size of the raw data. However, increasing the synthetic aperture time may also lead to the development of some novel application techniques, such as stereo SAR imaging in a single pass, multi-view-angle image fusion, 3D deformation monitoring, and atmosphere measuring.

This Special Issue will present papers that address the topic of “Processing Methods and Techniques of Spaceborne SAR with Ultra-High Resolution” and the use of innovative focusing algorithms, processing frameworks, specified cluster systems with a high focusing quality and high efficiency, and innovative applications and processing techniques in interferometry, stereo SAR imaging, multi-view-angle image fusion, and 3D deformation monitoring.

Suggested themes and article types for submissions:

UHR spaceborne SAR mission.
Challenges and potentials of spaceborne UHR SAR.
Innovative focusing algorithms, processing framework for spaceborne UHR SAR.
Processing techniques of stereo SAR imaging with spaceborne UHR SAR.
Processing techniques of multi-view-angle image fusion with spaceborne UHR SAR.
Processing techniques of 3D deformation monitoring with spaceborne UHR SAR.
Other remote sensing applications with spaceborne UHR SAR, such as in atmosphere and ocean observation and etc.

Prof. Dr. Guangcai Sun
Dr. Wenkang Liu
Prof. Dr. Vito Pascazio
Guest Editors

Quan Chen
Guest Editor Assistant
Shanghai Institute of Satellite Engineering, Shanghai 201109, China
Email: chenquan_cc@163.com

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Keywords

spaceborne SAR
ultra-high-resolution (UHR)
focusing algorithm
interferometry
stereo SAR imaging
multi-view-angle image fusion
3D deformation monitoring

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Published Papers (5 papers)

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Research

23 pages, 6677 KB

Open AccessArticle

Fine-Grained 3D Building Reconstruction and Floor Height Estimation from Ultra-High-Resolution TomoSAR Data Using Geometric Constraints

by Haoyuan Chen, Wenkang Liu, Quan Chen, Lei Cui and Mengdao Xing

Remote Sens. 2026, 18(7), 1073; https://doi.org/10.3390/rs18071073 - 2 Apr 2026

Cited by 2 | Viewed by 856

Abstract

The automatic generation of semantic Level of Detail (LOD) 2 models from TomoSAR point clouds is frequently compromised by elevation side-lobes, data sparsity, and inherent geometric distortions. In particular, the energy dispersion caused by side-lobes blurs vertical structures, making the extraction of floor details and accurate floor height estimation significantly challenging. To overcome these limitations, we present a refined reconstruction framework that tightly couples tomographic imaging mechanisms with building geometric priors. For fine-grained vertical reconstruction, we employ a geometry-constrained inverse projection strategy that concentrates scattered energy back onto the building façade to mitigate side-lobe interference. This is complemented by a Global Coherent Integration method, utilizing spectral analysis to robustly recover periodic floor patterns and estimate average floor heights. In the horizontal domain, we address the conflict between noise suppression and feature preservation through a separation-of-axes morphological strategy. Unlike traditional isotropic filtering, this approach processes orthogonal directions independently to bridge data gaps while strictly maintaining sharp building corners and recovering fine substructures. Validated on airborne Ku-band datasets, the proposed method demonstrates the capability to produce topologically complete and semantically rich urban models from sparse radar observations. Full article

(This article belongs to the Special Issue Processing Methods and Techniques of Spaceborne SAR with Ultra-High Resolution)

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24 pages, 4069 KB

Open AccessArticle

High-Precision HRWS SAR Phase Error Estimation with Inaccurate Baseline: A Joint-Pixel-Based Image Subspace Approach

by Jixia Fan, Quan Chen, Jixiang Xiang, Xiaojie Ding, Wenxin Zhao and Guangcai Sun

Remote Sens. 2025, 17(21), 3554; https://doi.org/10.3390/rs17213554 - 27 Oct 2025

Viewed by 1025

Abstract

HRWS (high resolution and wide swath, HRWS) SAR always suffers channel phase error in the multichannel reconstruction stage and results in a lower imaging quality. The image domain error estimation method can achieve superior performance by utilizing the signal-to-noise ratio (SNR) advantage. Nevertheless, in practice, the inevitable baseline error in HRWS SAR will lead to the inability of multichannel images to be registered in azimuth time and reduction of the channel phase error estimation accuracy. Considering that the joint-pixel model can fully contain the coherent information in such a case, a novel multichannel phase error estimation method is proposed. In this paper, by establishing a multichannel signal model in the image domain, an image domain subspace-based phase error estimation method based on joint-pixel selection and vector construction is derived. The proposed method can weaken the influence of subspace estimation inaccuracy caused by the inaccurate azimuth baseline and avoid the large amount of calculation caused by iterative elimination of baseline error and phase error in traditional algorithms, thus further improving computational efficiency. Simulation experiments and real acquired HRWS SAR data processing validate the estimation accuracy of the proposed method. Full article

(This article belongs to the Special Issue Processing Methods and Techniques of Spaceborne SAR with Ultra-High Resolution)

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37 pages, 94699 KB

Open AccessArticle

Two-Dimensional Spatial Variation Analysis and Correction Method for High-Resolution Wide-Swath Spaceborne Synthetic Aperture Radar (SAR) Imaging

by Zhenyu Hou, Pin Li, Zehua Zhang, Zhuo Yun, Feng He and Zhen Dong

Remote Sens. 2025, 17(7), 1262; https://doi.org/10.3390/rs17071262 - 2 Apr 2025

Cited by 1 | Viewed by 1283

Abstract

With the development and application of spaceborne Synthetic Aperture Radar (SAR), higher resolution and a wider swath have become significant demands. However, as the resolution increases and the swath widens, the two-dimensional (2D) spatial variation between different targets in the scene and the radar becomes very pronounced, severely affecting the high-precision focusing and high-quality imaging of spaceborne SAR. In previous studies on the correction of two-dimensional spatial variation in spaceborne SAR, either the models were not accurate enough or the computational efficiency was low, limiting the application of corresponding algorithms. In this paper, we first establish a slant range model and a signal model based on the zero-Doppler moment according to the spaceborne SAR geometry, thereby significantly reducing the impact of azimuth spatial variation in two-dimensional spatial variation. Subsequently, we propose a Curve-Sphere Model (CUSM) to describe the ground observation geometry of spaceborne SAR, and based on this, we establish a more accurate theoretical model and quantitative description of two-dimensional spatial variation. Next, through modeling and simulation, we conduct an in-depth analysis of the impact of two-dimensional spatial variation on spaceborne SAR imaging, obtaining corresponding constraints and thresholds and concluding that in most cases, only one type of azimuth spatial variation needs to be considered, thereby greatly reducing the demand and difficulty of two-dimensional spatial variation correction. Relying on these, we propose a two-dimensional spatial variation correction method that combines range blocking and azimuth nonlinear chirp scaling processing and analyze its scalability to be applicable to more general cases. Finally, the effectiveness and applicability of the proposed method are validated through both simulation experiments and real data experiments. Full article

(This article belongs to the Special Issue Processing Methods and Techniques of Spaceborne SAR with Ultra-High Resolution)

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24 pages, 7521 KB

Open AccessArticle

High-Resolution High-Squint Large-Scene Spaceborne Sliding Spotlight SAR Processing via Joint 2D Time and Frequency Domain Resampling

by Mingshan Ren, Heng Zhang and Weidong Yu

Remote Sens. 2025, 17(1), 163; https://doi.org/10.3390/rs17010163 - 6 Jan 2025

Cited by 2 | Viewed by 2315

Abstract

A frequency domain imaging algorithm, featured as joint two-dimensional (2D) time and frequency domain resampling, used for high-resolution high-squint large-scene (HHL) spaceborne sliding spotlight synthetic aperture radar (SAR) processing is proposed in this paper. Due to the nonlinear beam rotation during HHL data acquisition, the Doppler centroid varies nonlinearly with azimuth time and traditional sub-aperture approaches and two step approach fail to remove the inertial Doppler aliasing of spaceborne sliding spotlight SAR data. In addition, curved orbit effect and long synthetic aperture time make the range histories difficult to model and introduce space-variants in both range and azimuth. In this paper, we use the azimuth deramping and 2D time-domain azimuth resampling, collectively referred to as preprocessing, to eliminate the aliasing in Doppler domain and correct the range-dependent azimuth-variants of range histories. After preprocessing, the squint sliding spotlight SAR data could be considered as equivalent broadside strip-map SAR during processing. Frequency domain focusing, mainly involves phase multiplication and resampling in 2D frequency and RD domain, is then applied to compensate for the residual space-variants and achieve the focusing of SAR data. Moreover, in order to adapt higher resolution and larger scene cases, the combination of the proposed algorithm and partitioning strategy is also discussed in this paper. Processing results of simulation data and Gaofen-3 experimental data are presented to demonstrate the feasibility of the proposed methods. Full article

(This article belongs to the Special Issue Processing Methods and Techniques of Spaceborne SAR with Ultra-High Resolution)

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28 pages, 47685 KB

Open AccessArticle

Range-Dependent Variance Correction Method for High-Resolution and Wide-Swath Spaceborne Synthetic Aperture Radar Imaging Based on Block Processing in Range Dimension

by Zhenyu Hou, Zehua Zhang, Pin Li, Zhuo Yun, Feng He and Zhen Dong

Remote Sens. 2025, 17(1), 50; https://doi.org/10.3390/rs17010050 - 27 Dec 2024

Cited by 1 | Viewed by 1872

Abstract

With increasing demands for SAR image applications, spaceborne SAR systems are evolving towards higher resolution and wider swath capabilities. However, these advancements lead to more pronounced range-dependent variance effects. Previous research has primarily focused on the impact of range-dependent variance on range cell migration and the quadratic phase of range frequency, while often neglecting the effects of the cubic phase of range frequency. Although some block processing methods have addressed the range-dependent variant cubic phase of range frequency, they lack detailed impact analyses and segmentation criteria. This paper first proposes a Circle–Sphere geometric model to establish a theoretical framework for analyzing range-dependent variance impacts. Through simulation experiments, we validate the theoretical model’s accuracy and develop a numerical analysis of range-dependent variance effects. Building upon this foundation, we introduce a range-dependent variance correction method based on block processing in the range dimension. This method, incorporating valid data area and buffered data area, effectively corrects range-dependent variance while preventing data wrapping and fragmentation. Moreover, our theoretical model for analyzing range-dependent variance impacts provides both theoretical and numerical foundations for block segmentation criteria. The effectiveness and applicability of the proposed method are validated through both simulation experiments and real data experiments using GF3. Full article

(This article belongs to the Special Issue Processing Methods and Techniques of Spaceborne SAR with Ultra-High Resolution)

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