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Multistatic TomoSAR 3D Imaging Technique via Matrix Completion for Structured Targets

IEEE Transactions on Geoscience and remote sensing 2025年

作者： Wang, Chaodong Li, Zhongyu Hai, Yu Wei, Shunjun Wu, Junjie Yang, Jianyu University of Electronic Science and Technology of China School of Information and Communication Engineering Chengdu611731 China

Multistatic three-dimensional synthetic aperture radar (3D SAR) has shown significant potential in rapid 3D imaging. Compared to traditional multi-pass or array 3D imaging systems, it achieves high-resolution imaging in a single pass. However, due to the introduction of multiple radar systems, decoherence factors such as multi-channel and synchronization cause serious degradation in data quality, posing challenges for accurate reconstruction. To address this issue, this paper proposes a data recovery algorithm based on matrix completion (MC) for 3D imaging of structured targets. The structural characteristics of architectural targets introduce a low-rank property into the data, stemming from the inherent correlation among adjacent pixels. Utilizing the principle of matrix completion, combined with the sparsity of scattering points in elevation, a low-rank and sparse joint completion model is established. Furthermore, the Truncated Schatten-p Norm and Sparse Regularizer-Alternating Direction Method of Multipliers (TSPN-ADMM) algorithm is adopted for solving. Additionally, considering that this recovery method reconstructs the 2D complex image, a Filter-MC processing framework is proposed to further enhance the performance. Finally, both simulation and real data verify the effectiveness of the proposed recovery method and framework. © 2025 IEEE.

关键词： radar imaging

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SARLink: Satellite Backscatter Connectivity using synthetic aperture radar 25

SARLink: Satellite Backscatter Connectivity using Synthetic ...

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Proceedings of the 23rd ACM conference on Embedded Networked Sensor Systems

作者： Geneva Ecola Bill Yen Ana Banzer Morgado Bodhi Priyantha Ranveer Chandra Zerina Kapetanovic Electrical Engineering Stanford University Stanford CA USA Microsoft Redmond WA USA

ISBN: (纸本)9798400714795

SARLink is a passive satellite backscatter communication system that uses existing spaceborne synthetic aperture radar (SAR) imaging satellites to provide connectivity in remote regions. It achieves orders of magnitude more range than traditional backscatter systems, enabling communication between a passive ground node and a satellite in low earth orbit. The system is composed of a cooperative ground target, a SAR satellite, and a data processing algorithm. A mechanically modulating reflector was designed to apply amplitude modulation to ambient SAR backscatter signals by changing its radar cross section. These communication bits are extracted from the raw SAR data using an algorithm that leverages subaperture processing to detect multiple bits from a target in a single image dataset. A theoretical analysis of this communication system using on-off keying is presented, including the expected signal model, throughput, and bit error rate. The results suggest a 5.5 ft by 5.5 ft modulating corner reflector could send 60 bits every satellite pass, enough to support low bandwidth sensor data and messages. Using Sentinel-1A, a SAR satellite at an altitude of 693 km, we deployed static and modulating reflectors to evaluate the system. The results, successfully detecting the changing state of a modulating ground target, demonstrate our algorithm's effectiveness for extracting bits, paving the way for ultra-long-range, low-power satellite backscatter communication.

关键词： satellite

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image-processing OF synthetic-aperture radar RANGE AMBIGUOUS signalS

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IEEE TRANSACTIONS ON GEOSCIENCE AND remote sensing 1994年第5期32卷 1114-1117页

作者： TOMIYASU, K Martin Marietta Corporation Philadelphia PA USA

If wide-range swath scenes are illuminated by a synthetic aperture radar with high-pulse repetition frequencies, ambiguous scattered signals from an undesired range may appear in its receiver at the same time from consecutive transmitted pulses. This simplified analysis shows that range ambiguous signal returns result in a defocused image because they are convolved with the phase history of the desired range signal. A satellite borne SAR example is presented.

关键词： image processing synthetic aperture radar signal processing Covariance matrix Speckle Azimuth remote sensing Optical filters Optical noise radar imaging

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Comparison of Widely-used image Restoration Methods for Additive and Multiplicative Noises

Comparison of Widely-used Image Restoration Methods for Addi...

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Digital signal processing and its Applications (DSPA), International conference on

作者： Mohammad Zedan Yury S. Bekhtin dept. Diagnostic Information Technologies National Research University “MPEI” Moscow Russian Federation dept. Automatics and Information Technologies in Control Ryazan State Radio Engieneering University named after V.F. Utkin Ryazan Russian Federation

ISBN: (数字)9798331518752

ISBN: (纸本)9798331518769

This paper evaluates and compares the performance of various image denoising techniques, including wavelet transform, Wiener filtering, non-local means (NLM), denoising autoencoders (DAEs), and feedforward autoencoders. There are cases of additive and multiplicative noises considered where the Gaussian distribution with zero mean stands for the first case and an exponential distribution with unity mean describes the second case (speckle). The experiments have been conducted on the given dataset which contained both still test images and synthetic aperture radar (SAR) images with varying noise levels to analyze the effectiveness of these denoising approaches. The performance of each method is assessed using key image quality metrics: Peak signal-to-Noise Ratio (PSNR), Structural Similarity Index (SSIM), Mean Squared Error (MSE), and Normalized Absolute Error (NAK). The results demonstrate that denoising autoencoders DAEs provide superior performance in terms of structural preservation and noise reduction, particularly in low-noise conditions, while Wiener filtering proves to be computationally efficient and robust under high-noise conditions. These findings offer insights into the selection of effective denoising techniques for noisy images based on specific noise characteristics and application requirements.

关键词： Wavelet transforms Wiener filters Additives PSNR Autoencoders Speckle radar polarimetry Computational efficiency image restoration Noise level

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Recent Advances in synthetic aperture radar remote sensing-Systems, Data processing, and Applications

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IEEE GEOSCIENCE AND remote sensing LETTERS 2017年第11期14卷 2013-2016页

作者： Sun, Hongbo Shimada, Masanobu Xu, Feng Nanyang Technol Univ Temasek Labs Singapore 637553 Singapore Tokyo Denki Univ Sch Sci & Engn Tokyo 3500394 Japan Fudan Univ Key Lab Informat Sci Electromagnet Waves MoE Shanghai 200433 Peoples R China

This letter closes a special stream consisting of selected papers from the fifth Asia-Pacific conference on synthetic aperture radar in 2015 (APSAR 2015). The latest research results and outcomes from APSAR 2015, particularly on the synthetic aperture radar (SAR) systems/subsystems design, data processing techniques, and various SAR applications in remote sensing, are summarized and presented. All these results represent the recent advances in SAR remote sensing. Hopefully, this letter can provide some references for SAR researchers/engineers and stimulate the future development of SAR technology for remote sensing.

关键词： radar imaging remote sensing signal processing synthetic aperture radar (SAR)

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VGRSS: Datasets and Models for Visual Grounding in remote sensing Ship images

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IEEE Transactions on Geoscience and remote sensing 2025年 63卷

作者： Chen, Yaxiong Zhan, Liwen Zhao, Yichen Xiong, Shengwu Lu, Xiaoqiang Wuhan University of Technology Sanya Science and Education Innovation Park Sanya572000 China Wuhan University of Technology School of Computer Science and Artificial Intelligence Wuhan430070 China Shanghai Artificial Intelligence Laboratory Shanghai200232 China Wuhan College Interdisciplinary Artificial Intelligence Research Institute Wuhan430212 China Fuzhou University College of Physics and Information Engineering Fuzhou350108 China

This paper introduces a task named Visual Grounding of remote sensing Ship images (VGRSS). The goal of VGRSS is to locate ship objects in remote sensing images guided by natural language. Extensive research has been conducted on multimodal processing of remote sensing images and text to retrieve rich information from remote sensing images using natural language. However, due to the unique characteristics of remote sensing ship images, ship localization using natural language remains a challenge. Therefore, in this work, we construct datasets for the VGRSS task and explore deep learning models. Specifically, our contributions can be summarized as follows: First, we construct two remote sensing ship datasets for visual grounding. One is based on the optical remote sensing dataset, named RSSVG, while the other is based on the synthetic aperture radar (SAR) dataset, named SARVG. Second, we propose a Language-Guided Visual Feature Enhancement (LVFE) module. This module enhances visual features through language guidance before Visual-Linguistic Fusion. Third, we propose a Visual-Linguistic Fusion (VLF) module based on multimodal feature stacking. This module inputs the stacked language and visual features, and then performs feature fusion using a Transformer, enabling effective cross-modal interaction and integration. Fourth, we introduce a novel loss calculation method by incorporating Enhanced Intersection over Union (EIoU) into the loss function. Finally, we benchmark extensive state-of-the-art (SOTA) natural image visual grounding methods on the constructed RSSVG and SARVG datasets, then provide insightful analysis based on the results. This work offers valuable insights for developing better VGRSS models. © 2025 IEEE.

关键词： Deep learning

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Scattering Guided image Despeckling : A Score-Based Diffusion Approach in Frequency Domain

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IEEE Geoscience and remote sensing Letters 2025年

作者： Dong, Sihao Xiao, Xiayang Pan, Mingjun Inner Mongolia University of Science and Technology School of Automation and Electrical Engineering Inner Mongolia Baotou014010 China School of Information Science and Technology Shanghai200433 China China Mobile Internet Company Limited Guangzhou510030 China Peking University Shenzhen Graduate School School of Electronic and Computer Engineering Shenzhen China

When it comes to deep learning-based methods for despeckling synthetic aperture radar (SAR) images, maintaining spatial structure, ensuring process stability as well as achieving fast inference are still major challenges. To address these issues, a novel method named SGID (Scattering Guided image Despeckling), which is based on the wavelet - transform - conditioned diffusion model for SAR despeckling, has been proposed. First, the core component of this approach is the Adaptive Scattering Extraction Module (ASEM), which is designed to preserve the spatial structure of images effectively. It achieves the preservation of spatial structure by leveraging SAR imaging principles to adaptively extract scattering points, thereby retaining critical spatial information. Second, considering that speckle noise in SAR images is mainly concentrated in the high-frequency region, this study has designed a High-Frequency Despeckling Module (HFDM). This module adopts a direction-aware adaptive weight allocation strategy, aiming to precisely regulate the weight allocation of high-frequency components in all directions during the processing, so as to maximize the coherence and consistency of the high-frequency detail structures in the images. At last, the entire processing workflow is conducted in the frequency domain, which contributes significantly to the improvement of inference speed. Experimental results demonstrate that the proposed method achieves state-of-the-art (SOTA) performance in both spatial structure preservation and despeckling quality. Besides, its inference speed is 0.19 seconds, which is 67 times faster than that of comparable diffusion model-based methods. The code for this study will be publicly available at https://***/SihaoDong/SGID. © 2004-2012 IEEE.

关键词： Speckle

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SPACE-TIME-FREQUENCY processing OF synthetic-aperture radar signalS

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IEEE TRANSACTIONS ON AEROSPACE AND ELECTRONIC SYSTEMS 1994年第2期30卷 341-358页

作者： BARBAROSSA, S FARINA, A ALENIA SPA AERITALIA & SELENIA DEPT RADARI-00131 ROMEITALY

The subject of this work is the detection and high resolution microwave imaging of objects moving on the ground and observed by an airborne radar. The proposed approach is based on a combined space-time and time-frequency processing. The space-time processing makes use of a linear array antenna and exploits the radar motion for filtering the received echoes in order to improve as much as possible the signal-to-disturbance ratio. The signal is then mapped onto the time-frequency domain, by computing its Wigner-Ville distribution, for a further filtering and for estimating its instantaneous frequency, necessary for the formation of a high resolution image of the moving object.

关键词： aircraft instrumentation antenna arrays array signal processing echo suppression filtering and prediction theory linear systems microwave imaging parameter estimation radar theory remote sensing by radar signal detection signal processing synthetic apert Echo cancellers Parameter estimation linear antenna arrays array signal processing Linear system signal processing radar theory Antenna arrays Microwave imaging signal acquisition radar remote sensing

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SARChat-Bench-2M: A Multi-Task Vision-Language Benchmark for SAR image Interpretation

arXiv

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arXiv 2025年

作者： Ma, Zhiming Xiao, Xiayang Dong, Sihao Wang, Peidong Wang, HaiPeng Pan, Qingyun School of Information Science and Technology Fudan University Shanghai China China Mobile Internet Company Ltd. Guangzhou China The School of Automation and Electrical Engineering Inner Mongolia University of Science and Technology Baotou China School of Computer Science and Engineering Northeastern University Shenyang China China Mobile Group Guangdong Co. Ltd. Guangzhou Branch Guangzhou China

As a powerful all-weather Earth observation tool, synthetic aperture radar (SAR) remote sensing enables critical military reconnaissance, maritime surveillance, and infrastructure monitoring. Although Vision language models (VLMs) have made remarkable progress in natural language processing and image understanding, their applications remain limited in professional domains due to insufficient domain expertise. This paper innovatively proposes the first large-scale multimodal dialogue dataset for SAR images, named SARChat-2M, which contains approximately 2 million high-quality image-text pairs, encompasses diverse scenarios with detailed target annotations. This dataset not only supports several key tasks such as visual understanding and object detection tasks, but also serves as the first visual-language benchmark in the SAR domain. Through this work, we enable and evaluate VLMs’ capabilities in SAR image interpretation, providing a paradigmatic framework for constructing multimodal datasets across various remote sensing vertical domains. Through experiments on 16 mainstream VLMs, the effectiveness of the dataset has been fully verified. The project will be released at https://***/JimmyMa99/SARChat. Copyright © 2025, The Authors. All rights reserved.

关键词： Visual languages

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image processing, signal processing, and synthetic aperture radar for remote sensing

Image Processing, Signal Processing, and Synthetic Aperture ...

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Laser radar Ranging and Atmospheric Lidar Techniques

The proceedings contain 19 papers. The topics discussed include: laser long-path absorption experiment using retroreflector in space (RIS) on the ADEOS satellite;time walk compensated SPAD: multiple photons versus single photon operation;two-color SLR experiments at the GSFC 1.2m telescope;space lidar mission concepts for climate studies;some peculiarities in determining the range of the earth's surface with a spaceborne lidar 'Balkan-1' from the space station 'Mir';peculiarities of standardization efforts for lidar measurements;comparison of ERS-2 SAR wind measurements with an airborne Doppler lidar wind measurement;laser ranging and remote sensing;NASDA ELISE (MDS-LIDAR) program;LITE results, performance characteristics, and data archive;the WLRS streak camera experiment;and optical characteristics of the retroreflector in space (RIS) on the ADEOS satellite.

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