Article
Geochemistry & Geophysics
Tao Li, Dongliang Peng, Zhikun Chen, Baofeng Guo
Summary: The study introduces a superpixel-level CFAR detector based on truncated Gamma statistics, which improves target detection performance in real SAR images through superpixel segmentation and automatic clutter truncation.
IEEE GEOSCIENCE AND REMOTE SENSING LETTERS
(2021)
Article
Geochemistry & Geophysics
Lapo Miccinesi, Alberto Michelini, Massimiliano Pieraccini
Summary: This article proposes an acquisition modality and image processing technique to mitigate blurring in GBSAR images caused by moving clutter. By filtering out high-frequency clutter and using high-frequency sampling, the authors have demonstrated the effectiveness of these methods in a realistic quarry scenario.
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
(2021)
Article
Geochemistry & Geophysics
Dong-Xiao Yue, Feng Xu, Alejandro C. Frery, Yaqiu Jin
Summary: This article extends the discussion on SAR image statistical modeling to spatial correlation analysis, focusing on SAR spatial correlation models and clutter simulation methods. It summarizes two types of spatial correlation models and reviews four clutter simulation methods based on different distributions, providing references for further research in this area.
IEEE GEOSCIENCE AND REMOTE SENSING MAGAZINE
(2021)
Article
Geochemistry & Geophysics
Simon Zwieback, Franz J. Meyer
Summary: The study found pervasive deviations from Gaussianity in repeat-pass radar interferometric data, especially in areas with naturally heterogeneous surfaces. Permanent texture has a significant impact on intensity heterogeneity related to phase heterogeneity. Accounting for heterogeneity has a moderate impact on phase estimates and estimated uncertainty in deformation analyses, but can improve phase estimation accuracy and uncertainty estimates in inherently heterogeneous areas.
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
(2021)
Article
Engineering, Electrical & Electronic
Tao Li, Dongliang Peng, Sainan Shi
Summary: This article proposes a ship detection method that combines complex signal kurtosis and clutter truncation, improving detection accuracy and efficiency through optimized clutter modeling and detection processes.
IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING
(2022)
Article
Geochemistry & Geophysics
Jie Zhou, Junhao Xie, Xingxing Liao, Chang Sun
Summary: This article introduces the concept of quantile and its relation to truncation depth, and proposes quantile truncated statistics (QTS) based on this concept. QTS provides a reasonable explanation for truncation depth and allows for well-founded and controllable selection of the depth. Additionally, the article derives maximum likelihood estimation (MLE) based on QTS (QTS-MLE) for the parameters of the probability density function (pdf). The article also explores the performance of QTS-MLE in estimating parameters in Weibull background, and proposes the QTS-CFAR detector based on QTS-MLE.
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
(2022)
Article
Geochemistry & Geophysics
Mateusz Malanowski, Rafal Rytel-Andrianik, Krzysztof Kulpa, Krzysztof Stasiak, Marek Ciesielski, Jaroslaw Kulpa
Summary: This article presents detailed geometric analyses of ground clutter in bistatic passive airborne radars. Analytic closed-form solutions are derived for finding the intersection of iso-ranges and iso-velocities, allowing clutter bistatic coordinates to be easily converted. The theoretical clutter distribution on the range-velocity map is compared with real-life data, showing good agreement between theory and measurement.
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
(2022)
Article
Geochemistry & Geophysics
Michael K. Newey, Joshua M. Kantor, Gerald R. Benitz
Summary: This work focuses on improving SAR autofocus methods for moving targets, incorporating higher motion order terms to improve image quality and reduce blurring in target signatures.
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
(2022)
Article
Multidisciplinary Sciences
Jingang Wang, Songbin Li
Summary: Radar detection of maritime targets is important for marine environment monitoring. Pulse-compression radar is universally used for civil maritime detection in inshore coastal areas due to its low cost. However, the complex sea clutter affects the received radar echoes and traditional mathematical methods struggle to accurately differentiate sea clutter from maritime targets. Inspired by recent advancements in deep learning, the proposed SALA-LSTM structure integrates adaptive convolution to better model the sequence correlation of radar echoes and improves radar target detection performance.
SCIENTIFIC REPORTS
(2023)
Article
Geochemistry & Geophysics
Xueqian Wang, Gang Li, Antonio Plaza, You He
Summary: DSLIC is a new density-based superpixel segmentation method for marine SAR images. By pre-screening subimages with high-density clutter pixels, computational efficiency and memory savings can be improved. In the local clustering stage, sparsity proximity is considered to reduce the coexistence of sparse target pixels and high-density clutter pixels.
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
(2022)
Article
Environmental Sciences
Wenhao Zhang, Yajun Li, Zhengqi Zheng, Lin Xu, Zhicheng Wang
Summary: High frequency radar has a wide monitoring range and low range resolution, which can contain multiple targets or outlier interference phenomena. The key to multi-target detection in background clutter is determining the attributes of targets or outliers. This paper proposes a new method for multi-target detection based on the ordered statistics constant false alarm detector (OS-CFAR), utilizing the sparse characteristics of the target and introducing regularization processing to eliminate interfering targets. Simulation and measured data demonstrate the effectiveness of the algorithm in counteracting interference and providing reliable target detection.
Article
Geochemistry & Geophysics
Ming-Dian Li, Xing-Chao Cui, Si-Wei Chen
Summary: Ship monitoring using synthetic aperture radar (SAR) is an important application, with constant false alarm rate (CFAR) methods commonly used for ship detection. However, challenges arise in dense ship detection near shorelines. A new superpixel-level CFAR detector is proposed, incorporating a labeling procedure for discriminating between pure clutter superpixels and mixture superpixels, as well as a nonlocal topology strategy for adaptive threshold estimation. The proposed method outperforms traditional CFAR detectors and recent superpixel methods in detecting inshore dense ship regions.
IEEE GEOSCIENCE AND REMOTE SENSING LETTERS
(2022)
Article
Engineering, Electrical & Electronic
Xueqian Wang, You He, Gang Li, Antonio J. Plaza
Summary: Superpixel segmentation is an important technique for image analysis, and a new Fisher vector-based adaptive superpixel segmentation algorithm has been developed to address issues such as low contrast in marine SAR images. This algorithm fuses intensity, spatial, and multiorder features to improve segmentation performance, and adaptive adjustments of feature weights are made to maintain superpixel compactness, demonstrating enhanced segmentation and detection performance in SAR images.
IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING
(2021)
Article
Geochemistry & Geophysics
Floriane Madeleine Schreiber, Sebastien Angelliaume, Charles-Antoine Guerin
Summary: The two-scale model based on Bragg tilting is widely used to model radar cross section from the sea surface, but it has difficulties in consistently describing the polarized sea clutter statistics in the upper microwave band. A simple correction proposed in this study brings the model in better agreement with observations, allowing for a more accurate description of polarized sea clutter statistics in the upper microwave regime.
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
(2021)
Article
Chemistry, Multidisciplinary
Wenjie Shen, Jie Zhi, Yanping Wang, Jinping Sun, Yun Lin, Yang Li, Wen Jiang
Summary: Ground-Based Synthetic Aperture Radar (GBSAR) has advantages in building structure monitoring and mine slope deformation retrieval. Circular Scanning GBSAR (CS-GBSAR) provides 3D imaging compared with traditional GBSAR modes, but suffers from strong sidelobes. This paper proposes a new CFAR-based method for 3D point cloud extraction in CS-GBSAR, which has been validated using real data.
APPLIED SCIENCES-BASEL
(2023)