Synthetic Aperture Radar

Also known as SAR

Synthetic Aperture Radar (SAR) combines microwave echoes collected as a sensor moves to form detailed images, including in darkness and cloudy weather, but images are affected by speckle and viewing geometry. Research develops signal-processing methods such as sparse reconstruction and interferometric SAR (InSAR), alongside deep-learning approaches for recognition, detection, segmentation, and change mapping. CNNs, Transformers, state-space models, self-supervised pretraining, and physics-informed scattering priors are used to learn from limited labels and transfer across sensors; optical imagery and generative models also support cross-modal tasks. A central challenge is balancing robust performance across sensors, terrain, and acquisition conditions with physical fidelity, efficient computation, and reliable evaluation on real-world data.

Latest papers

70 papers4 papers in the last four weeks, down 33% on the four weeks before. 0.0% of all new papers.

Revealing Inter-Channel Modality Discriminability: Channel Selective Interaction Fusion Network for Optical-SAR Object Detection
Oct 20, 2026Haojie Li, Yuanfei Huang, Lingfei Song +2Object Detection Multimodal Object Detection
School of Artificial Intelligence, Beijing Normal University · Beijing Key Laboratory of Artificial Intelligence for Education · Engineering Research Center of Intelligent Technology and Educational Application, Ministry of Education
Data-Efficient ConvNeXt Pretraining for High-Resolution Sentinel-1 GRD SAR Representation Learning
Oct 15, 2026Yuki Natsume, Sang-Ho Yun, Chai Kiat YeoSelf-Supervised Pre-Training Masked Autoencoders
College of Computing and Data Science, Nanyang Technological University, Singapore · Earth Observatory of Singapore, Nanyang Technological University, Singapore · Asian School of the Environment, Nanyang Technological University, Singapore +1
Hybrid++: The Bridge between PDE Models and Deep Learning for Gamma Noise Removal
Oct 6, 2026Mahipal Jetta, Sujato DuttaSynthetic Aperture Radar Image Denoising
Mahindra University
Extending Dynamic World Surface Water Mapping to Sentinel-1 with AlphaEarth Embeddings
Oct 5, 2026Rohit Mukherjee, Frederick Policelli, Beth Tellman +4Remote Sensing Image Segmentation Remote Sensing
Pacific Northwest National Laboratory, Richland, WA 99354 USA
GeoSET: Generalist Foundation Model for SAR-to-EO Image Translation
Sep 26, 2026Jeonghyeok Do, Munchurl KimImage-to-Image Translation Geospatial Foundation Models
Korea Advanced Institute of Science and Technology (KAIST)
Learned Compression of SAR Phase-History Data: A Rate-Honest Feasibility Study on GOTCHA
Sep 25, 2026Alizishaan KhatriSynthetic Aperture Radar Convolutional Autoencoder
Wrynx Inc
Enhancing Foundation Models for Imbalanced SAR Ship Classification via Targeted Oversampling
Sep 15, 2026Ch Muhammad Awais, Marco Reggiannini, Davide MoroniClass-Imbalanced Learning Remote Sensing
Institute of Science and Technology, National Research Council, Pisa, Italy
Cross-modal learning for SAR target recognition using optical vision foundation models
Sep 7, 2026Lucas Hirsch, James R. Hopgood, Javid Khan +2Cross-Modal Alignment Cross-Modal Representation Transfer
School of Engineering, University of Edinburgh, United Kingdom · Leonardo UK, United Kingdom · School of Engineering and Physical Sciences, Heriot-Watt University, United Kingdom
Bridging Modalities and Tasks: A Unified Hierarchical ViT for SAR-to-Optical Translation and Semantic Segmentation
Sep 4, 2026Siyuan Liu, Xuze Zhang, Yongshun Wang +3Image-to-Image Translation Semantic Segmentation
School of Automation, Northwestern Polytechnical University, Xi’an 710129, China · School of Cybersecurity, Northwestern Polytechnical University, Xi’an 710129, China
Lightweight Adaptation of General-Purpose VLMs for Multispectral and SAR Image Understanding
Sep 2, 2026Shanji Liu, Kelu Yao, Junxiao Xue +5Synthetic Aperture Radar VLM Adaptation
Zhejiang University · Zhejiang Lab
FiLM-GPNet: Geometry-Aware Pseudo-Supervised Phase Restoration with Zero-Shot Generalization for Large Temporal InSAR Stacks
Aug 29, 2026Getnet Demil, Muhammad Farhan Humayun, Tomi Westerlund +2Aleatoric Uncertainty Synthetic Aperture Radar
University of Turku Turku, Finland
QUASAR: A Quantum-Classical Neural Network for SAR Satellite Physical-Layer Authentication
Aug 20, 2026Vincenzo Sammartino, Nathanael Denis, Roberto Di PietroWireless Communications Synthetic Aperture Radar
University of Pisa, Pisa, Italy · King Abdullah University of Science and Technology (KAUST), Thuwal, Saudi Arabia
SED-FOD: Scattering-Aware Expert Decomposition for Few-Shot Cross-Sensor SAR Object Detection
Aug 19, 2026Shu Yang, Zhen Chen, Zhiyu Jiang +2Synthetic Aperture Radar Few-Shot Domain Adaptation
National Key Laboratory of Microwave Imaging Technology, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100190, China, and also with the School of Electronic, Electrical and Communication Engineering, University of Chinese Academy of Sciences, Beijing 100049, China.
To Remove or Not to Remove Clouds: A Comparative Analysis and Fusion of Raw SAR and Synthetic NDWI for Overcast Water Segmentation
Aug 18, 2026Saleh Sakib Ahmed, Sara Nowreen, M. Sohel RahmanRemote Sensing Image Segmentation Multi-Source Image Fusion
Computer Science and Engineering, Bangladesh University of Engineering and Technology, Palashi, Dhaka, Bangladesh. · Institute of Water and Flood Management, Bangladesh University of Engineering and Technology, Palashi, Dhaka, Bangladesh.
SAR2Agri: Learning SAR Intensity Representations for Agricultural Monitoring
Aug 11, 2026Moti Rattan Gupta, Anupam SobtiRepresentation Learning Agricultural Remote Sensing
Plaksha University, Mohali, Punjab, India
Hardware-Aware Deployment of Joint SAR Compression and Despeckling on FPGA
Aug 11, 2026Cédric Léonard, Francescopaolo Sica, Martin SchulzLearned Image Compression Edge Computing
Technical University of Munich, Munich, Germany · Remote Sensing Technology Institute, German Aerospace Center (DLR), Weßling, Germany · Department of Aerospace Engineering, University of the Bundeswehr Munich, Neubiberg, Germany
OSSDD - a New Open Dataset for Sentinel-1 Ship Detection
Aug 3, 2026Horst Hammer, Sylvia Hochstuhl, Antje Thiele +4Object Detection Synthetic Aperture Radar
Fraunhofer Institute of Optronics, System Technologies and Image Exploitation - IOSB, Gutleuthausstraße 1, Ettlingen, 76275, Germany · Karlsruhe Institute of Technology - KIT, Kaiserstraße 12, Karlsruhe, 76131, Germany · HENSOLDT Sensors GmbH, Wörthstraße 85, Ulm, 89077, Germany
WGDnet: Wishart-guided Geometric-aware Deep Network for PolSAR Image Classification
Jul 26, 2026Junfei Shi, Haojia Zhang, Yu Cheng +1Convolutional Neural Networks Synthetic Aperture Radar
Direction-adaptive Mamba: Spatial-Frequency Dual-Domain Collaborative Learning for PolSAR Image Classification
Jul 26, 2026Junfei Shi, Yu Cheng, Haojia Zhang +3Mamba Frequency-Domain Feature Learning
SARATR-X-v2: Scale-Aware Structural Pre-Training for SAR Foundation Models
Jul 25, 2026Weijie Li, Yafei Song, Yongxiang Liu +7Self-Supervised Pre-Training Synthetic Aperture Radar
College of Electronic Science and Technology, National University of Defense Technology, Changsha 410073, China
PriSAR: 3D Geometric-Prior-Guided Diffusion for Parameter-Controlled SAR Image Generation
Jul 25, 2026Fan Zhang, Xuanting Wu, Fei Ma +2Diffusion Model Guidance Diffusion-Based Image Generation
College of Information Science and Technology, Beijing University of Chemical Technology, Beijing 100029, China · 2Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100190, China
Deep Sigma Point Processes for RCS Modeling in Spaceborne SAR Imagery
Jul 23, 2026Khalid El-Darymli, Christoph H. Gierull, Katerina Biron +1Uncertainty Quantification Synthetic Aperture Radar
Defence Research and Development Canada, Ottawa, Ontario, Canada · Memorial University, St. John’s, NL, Canada
$γ$ -Bridge: A Look-Parametric Diffusion Bridge
Jul 21, 2026Xuran Hu, Yujie Zhu, Tengxi Wang +2Diffusion Models for Image Restoration Physics-Guided Image Restoration
Urban Governance and Design Thrust, Society Hub, The Hong Kong University of Science and Technology (Guangzhou), Guangzhou, China · Faculty of Science and Engineering, Macquarie University, NSW 2109, Sydney, Australia · School of Geography and Planning, Ningxia University, Yinchuan, China
Fast Generation of Representative Synthetic Dataset with Salsa to Train ATR Models with Electromagnetic Couplings Data-Augmentation
Jul 21, 2026Benjamin Camus, Julien Houssay, Corentin Le Barbu +3Synthetic Data Generation Synthetic Aperture Radar
DGA.MI · Scalian DS 2 rue Antoine Becquerel 35700 Rennes, France · DGA Maîtrise de l’Information BP 7 35998 Rennes CEDEX 9, France
SAR Vessel Detection and Gross Tonnage Estimation from Heterogeneous Datasets for Dark Vessel Identification
Jul 20, 2026Davide Paltrinieri, Andrea Diecidue, Roberto Basla +3Object Detection Synthetic Aperture Radar
Politecnico di Milano, Milano, Italy
Millimeter Wave Radar: From Synthetic Aperture to Probabilistic Mapping
Jul 11, 2026Jui-Te Huang, Ruoyang Xu, Michael KaessMillimeter-Wave Radar mmWave Radar Sensing
Computer Science, Robotics Institute, Carnegie Mellon University, PA, USA · School of Computer Science, Robotics Institute, Carnegie Mellon University, PA, USA
Context-Aware Slum Mapping in Sub-Saharan Africa Using Sentinel-1 Texture and Local Climate Zones
Jul 8, 2026Peterson Chepkilot, Babak Memar, Paolo GambaRemote Sensing Image Understanding Camera-Radar Fusion
Department of Civil, Building and Environmental Engineering, Sapienza University of Rome, 00184 Rome, Italy · Department of Electrical, Computer and Biomedical Engineering, University of Pavia, 27100 Pavia, Italy
A Generalized Deep Non-negative Matrix Factorization Approach for SAR Automatic Target Recognition
Jul 8, 2026Yunhong Zhang, Changjie Cao, Zhongli Zhou +4Non-Negative Matrix Factorization Remote Sensing
SAMBA: A Scatter-Guided Masked Bidirectional Mamba Foundation Model for SAR Target Recognition
Jun 30, 2026Ke Wang, Xiaoyi Pan, Zhaoyu Gu +4Mamba Self-Supervised Pre-Training
College of Electronic Science and Technology, National University of Defense Technology, Changsha 410073, China
High-Resolution Flood Mapping With Sentinel-1 and Sentinel-2 via Misalignment-Robust Cross-Sensor Learning and Generative Despeckling
Jun 29, 2026David Ma, Jeremy Feinstein, Shreya Pandit +2Remote Sensing Image Segmentation Flood Inundation Mapping
Argonne National Laboratory, Lemont, IL 60439 USA · Ohlone College, Fremont, CA 94539 USA

Oct 20, 2026J/K move · Enter open · S save

Revealing Inter-Channel Modality Discriminability: Channel Selective Interaction Fusion Network for Optical-SAR Object Detection

Haojie Li, Yuanfei Huang, Lingfei Song, Jia Li+1

School of Artificial Intelligence, Beijing Normal University · Beijing Key Laboratory of Artificial Intelligence for Education · Engineering Research Center of Intelligent Technology and Educational Application, Ministry of Education

Object Detection Multimodal Object Detection Multimodal Fusion Synthetic Aperture Radar Cross-Modal Attention

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Synthetic aperture radar (SAR) and optical imagery provide complementary structural and appearance information for remote sensing object detection. However, substantial cross-modal discrepancies and indiscriminate channel interaction inevitably introduce redundant or conflicting features. Since different feature channels encode heterogeneous semantic information and contribute unequally to cross-modal fusion, selectively highlighting task-relevant channels while suppressing redundant ones is essential. To address this issue, we propose the Channel Selective Interaction Fusion Network (CSIF-Net), which performs selective channel-level cross-modal interaction. CSIF-Net first employs a frequency decomposition module to construct frequency-aware SAR inputs, facilitating the separation of structural information from noise-related responses. It then models cross-modal channel relationships through a cross-attention channel selection module and dynamically partitions the features into shared and modality-specific components. Finally, a dual-branch fusion module performs cross-modal interaction and channel realignment for shared features while independently enhancing SAR-specific features, thereby exploiting complementary information and suppressing modality interference. Extensive experiments on the OGSOD 1.0 and M4-SAR datasets demonstrate that CSIF-Net achieves state-of-the-art performance in both horizontal and oriented object detection, surpassing the existing methods by 4.01% and 3.18% gains, respectively.