Optical images are rich in spectral information, but difficult to acquire under all-weather conditions, while SAR images can overcome adverse meteorological conditions, but geometric distortion and speckle noise will reduce the quality of SAR images...
Accurate image registration is essential for synthetic aperture radar (SAR) applications such as change detection, image fusion, and deformation monitoring. However, SAR image registration faces challenges including speckle noise, low-texture regions...
Deep neural network-based synthetic aperture radar (SAR) automatic target recognition (ATR) systems are susceptible to attack by adversarial examples, which leads to misclassification by the SAR ATR system, resulting in theoretical model robustness p...
Target recognition in synthetic aperture radar (SAR) imagery suffers from speckle noise and geometric distortion brought by the range-based coherent imaging mechanism. A new SAR target recognition system is proposed, using a SAR-to-optical translatio...
Due to self-motion and sea waves, moving ships are typically defocused in synthetic aperture radar (SAR) images. To focus non-cooperative targets, the inverse SAR (ISAR) technique is commonly used with motion compensation. The hybrid SAR/ISAR approac...
In recent times, the realm of remote sensing has witnessed a remarkable surge in the area of deep learning, specifically in the domain of target recognition within synthetic aperture radar (SAR) images. However, prevailing deep learning models have o...
The study offers a Synthetic Aperture Radar (SAR) imaging concept called Strip-Spot SAR, which uses linear Multiple-Input Multiple-Output (MIMO) radar arrays, which are becoming increasingly attractive for short-range sensing in a variety of growing...
The current methods for removing thick clouds from remote-sensing images face significant limitations, including the integration of thick cloud images with synthetic aperture radar (SAR) ground information, the provision of meaningful guidance for SA...
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 monitorin...
Traditional synthetic aperture radar (SAR) deceptive jamming can effectively generate deceptive scenes or false targets in SAR images. However, these false targets or scenes can be easily distinguished or eliminated by the multichannel SAR system. To...
The registration of optical and SAR images has always been a challenging task due to the different imaging mechanisms of the corresponding sensors. To mitigate this difference, this paper proposes a registration algorithm based on a pseudo-SAR image...
Modern Synthetic Aperture Radar (SAR) missions provide an unprecedented massive interferometric SAR (InSAR) time series. The processing of the Big InSAR Data is challenging for long-term monitoring. Indeed, as most deformation phenomena develop slowl...
In contrast to the well-investigated field of Synthetic Aperture Radar (SAR)-to-Optical translation, this study explores the lesser-investigated domain of Optical-to-SAR translation, which is a challenging field due to the ill-posed nature of this tr...
Synthetic aperture radar (SAR) imagery is widely used for target detection in complex backgrounds and adverse weather conditions. However, high-precision detection of rotated small targets remains challenging due to severe speckle noise, significant...
The fusion of synthetic aperture radar (SAR) and visible images offers complementary spatial and spectral information, enabling more reliable and comprehensive scene interpretation. However, SAR speckle noise and the intrinsic modality gap pose signi...
The unique imaging modality of synthetic aperture radar (SAR) has posed significant challenges for object detection, making it more complex to acquire and interpret than optical images. Recently, numerous studies have proposed cross-domain adaptive m...
For the spaceborne synthetic aperture radar (SAR), it is difficult to obtain high resolution and wide width at the same time. This paper proposes a novel imaging system based on tandem SAR satellites, where one obtains coarse resolution and wide swat...
In the application of change detection satellite remote sensing images, synthetic aperture radar (SAR) images have become a more important data source. This paper proposes a new end-to-end SAR image change network architecture—TransUNet++SAR&md...
Synthetic Aperture Radar (SAR) image change detection aims to detect changes with images of the same area acquired at different times. It has wide applications in environmental monitoring, urban planning and resource management. Traditional change de...
Edge detection in Synthetic Aperture Radar (SAR) images has been a challenging task due to the speckle noise. Ratio-based edge detectors are robust operators for SAR images that provide constant false alarm rates, but they are only optimal for step e...
In producing orthophoto mosaic in a large area from spaceborne synthetic aperture radar (SAR) images, SAR image matching from adjacent orbits is a technical difficulty due to the speckle noise and different imaging mechanism between azimuth and range...
Synthetic Aperture Radar (SAR) imagery is a vital tool for flood mapping due to its capability to acquire images day and night in almost any weather and to penetrate through cloud cover. In rural areas, SAR backscatter intensity can be used to detect...
SAR tomography (TomoSAR) extends SAR interferometry (InSAR) to image a complex 3D scene with multiple scatterers within the same SAR cell. The phase calibration method and the super-resolution reconstruction method play a crucial role in 3D TomoSAR i...
Estimation of forest biomass with synthetic aperture radar (SAR) and interferometric SAR (InSAR) observables has been surveyed in 186 peer-reviewed papers to identify major research pathways in terms of data used and retrieval models. Research evalua...
Convolutional neural networks (CNNs) have been widely used in SAR image recognition and have achieved high recognition accuracy on some public datasets. However, due to the opacity of the decision-making mechanism, the reliability and credibility of...
Interferometric Synthetic Aperture Radar (InSAR) and Differential Interferometric Synthetic Aperture Radar (DInSAR) have shown numerous applications for subsidence monitoring. In the past 10 years, the Persistent Scatterer InSAR (PSI) and Small BAsel...
We propose a new method for SAR image despeckling, which performs nonlocal filtering with a deep learning engine. Nonlocal filtering has proven very effective for SAR despeckling. The key idea is to exploit image self-similarities to estimate the hid...
Maritime application of synthetic aperture radar (SAR) technology for sea-target surveillance and imaging is considered in this study. A SAR scenario, including the kinematics of a SAR satellite and a ship moving on the sea, along with the geometry o...
In spaceborne synthetic aperture radar (SAR) sensors, it is a challenging task to detect ground slow-moving targets against strong clutter background with limited spatial channels and restricted pulse repetition frequency (PRF). In this paper, we eva...
Synthetic aperture radar (SAR) images contain severe speckle noise and weak texture, which are unsuitable for visual interpretation. Many studies have been undertaken so far toward exploring the use of SAR-to-optical image translation to obtain near...
Dense 3D reconstruction from multi-aspect angle synthetic aperture radar (SAR) imagery has gained considerable attention for urban monitoring applications. However, achieving reliable dense matching between multi-aspect SAR images remains challenging...
Holographic synthetic aperture radar tomography (HoloSAR) combines circular synthetic aperture radar (CSAR) and SAR tomography (TomoSAR) to enable a 360° azimuth observation of the considered scene. This imaging mode achieves a high-resolution th...
Abundant datasets are critical to train models based on deep learning technologies for ship detection applications. Compared with optical images, ship detection based on synthetic aperture radar (SAR) (especially the high-Earth-orbit spaceborne SAR l...
Since its launch in 2007, TerraSAR-X has continuously provided spaceborne synthetic aperture radar (SAR) images of our planet with unprecedented spatial resolution, geodetic, and geometric accuracy. This has brought life to the once inscrutable SAR i...
Polarimetric synthetic aperture radar (PolSAR) is widely used in remote sensing applications due to its ability to obtain full-polarization information. Compared to the quad-pol SAR, the dual-pol SAR mode has a wider observation swath and is more com...
Detecting objects in synthetic aperture radar (SAR) imagery has received much attention in recent years since SAR can operate in all-weather and day-and-night conditions. Due to the prosperity and development of convolutional neural networks (CNNs),...
Monitoring aircraft using synthetic aperture radar (SAR) images is a very important task. Given its coherent imaging characteristics, there is a large amount of speckle interference in the image. This phenomenon leads to the scattering information of...
Synthetic Aperture RADAR (SAR) is a radar imaging technique in which the relative motion of the sensor is used to synthesize a very long antenna and obtain high spatial resolution. Several algorithms for SAR data-focusing are well established and use...
Shadows are a special distortion in synthetic aperture radar (SAR) imaging. They often hamper proper image understanding and target recognition but also offer useful information, and therefore, the statistical modeling of SAR image shadows is imperat...
Synthetic aperture radar (SAR) tomography (TomoSAR) is a multibaseline interferometric technique that estimates the power spectrum pattern (PSP) along the perpendicular to the line-of-sight (PLOS) direction. TomoSAR achieves the separation of individ...
Differential synthetic aperture radar interferometry (DInSAR) has been widely applied since the pioneering space-borne experiment in 1989, and subsequently with the launch of the ERS-1 program in 1992. The DInSAR technique is well assessed in the cas...
Three-dimensional SAR imaging of urban buildings is currently a hotspot in the research area of remote sensing. Synthetic Aperture Radar (SAR) offers all-time, all-weather, high-resolution capacity, and is an important tool for the monitoring of buil...
The integration of deep neural networks into sparse synthetic aperture radar (SAR) imaging is explored to enhance SAR imaging performance and reduce the system’s sampling rate. However, the scarcity of training samples and mismatches between th...
In this work, the airborne Synthetic Aperture Radar (SAR) infrastructure developed at the Institute for Electromagnetic Sensing of the Environment (IREA) of the National Research Council of Italy (CNR) is described. This infrastructure allows IREA-CN...
With more and more SAR applications, the demand for enhanced high-quality SAR images has increased considerably. However, high-quality SAR images entail high costs, due to the limitations of current SAR devices and their image processing resources. T...
Synthetic aperture radar (SAR) interferometry has rapidly evolved in the last decade and can be considered today as a mature technology, which incorporates computationally intensive and data-intensive tasks. In this paper, a perspective on the state-...
The automotive synthetic aperture radar (SAR) can obtain two-dimensional (2-D) high-resolution images and has good robustness compared with the other sensors. Generally, the 2-D high-resolution always conflicts with the real-time requirement in conve...
Synthetic aperture radar (SAR) ship detection has been the focus of many previous studies. Traditional SAR ship detectors face challenges in complex environments due to the limitations of manual feature extraction. With the rise of deep learning (DL)...
There is a common need for optical sequence images with high spatiotemporal resolution. As a solution, Synthetic Aperture Radar (SAR)-to-optical translation tends to bring high temporal continuity of optical images and low interpretation difficulty o...
The backprojection (BP) algorithm has been applied to every SAR mode due to its great focusing quality and adaptability. However, the BP algorithm suffers from immense computational complexity. To improve the efficiency of the conventional BP algorit...
of 576