Shahzad Gishkori, David Wright, Liam Daniel, Marina Gashinova, Bernard Mulgrew
In this paper, we propose a novel concept of cross-learning, in order to improve SAR images by learning from the camera images. We use a multi-level abstraction approach to materialise knowledge transfer between the two modalities. We also compare the performance of other possible approaches. We provide experimental results on real data to validate the proposed concept.
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Array SAR 3D Sparse Imaging Based on Regularization by Denoising Under Few Observed Data
针对少观测数据下稀疏成像目标信息丢失问题，提出基于去噪正则化（RED）和近端梯度下降类方法的阵列SAR 3D稀疏成像框架，利用去噪算子构建先验项，提高重建精度并保留结构信息，实验验证其优越性。
Synthetic aperture radar (SAR) imagery can provide useful information in a multitude of applications, including climate change, environmental monitoring, meteorology, high dimensional mapping, ship monitoring, or planetary exploration. In this paper, we investigate solutions to a number of inverse problems encountered in SAR imaging. We propose a convex proximal splitting method for the optimization of a cost function that includes a non-convex Cauchy-based penalty. The convergence of the overall cost function optimization is ensured through careful selection of model parameters within a forwa…
For 3D Synthetic Aperture Radar (SAR) imaging, one typical approach is to achieve the cross-track 1D focusing for each range-azimuth pixel after obtaining a stack of 2D complex-valued images. The cross-track focusing is the main difficulty as its aperture length is limited and the antenna positions are usually non-uniformly distributed. Sparsity regularization methods are widely used to tackle these problems. However, these methods are of obvious limitations. The most well-known ones are their heavy computational burdens and unsatisfied stabilities. In this letter, an efficient deep network-ba…
SPHR-SAR-Net: Superpixel High-resolution SAR Imaging Network Based on Nonlocal Total Variation
针对传统高分辨率SAR成像忽略非局部信息、散斑难滤除及计算复杂度高的问题，提出SPHR-SAR-Net，通过结合非凸非局部全变分复合正则化并展开为深度展开网络，实现快速且准确的高分辨率SAR成像。
repetition frequency (PRF). Given the system complexity and resource constraints, it is often difficult to achieve high imaging performance and low ambiguity without compromising the swath. In this paper, we propose a joint optimization framework for sparse strip SAR imaging algorithms and azimuth undersampling patterns based on a deep convolutional neural network, combined with matched filter (MF) approximate measurement operators and inverse MF operators, referred to as MF-JMoDL-Net, for sparse SAR imaging methods. Compared with conventional sparse SAR imaging, MF-JMoDL-Net enables us to all…
ICEYE microsatellite SAR constellation status update: Evaluation of first commercial imaging modes
本文报告了ICEYE星座的最新状态，并描述了首批 operational 成像模式的特性。
3D Near-Field Virtual MIMO-SAR Imaging Using FMCW Radar Systems at 77 GHz
本研究结合虚拟MIMO FMCW雷达与SAR技术，提出77 GHz频段的3D近场高分辨率成像方案，实现了紧凑低成本、高速低复杂度的3D毫米波成像系统。
In this paper, SAR image reconstruction with joint phase error estimation (autofocusing) is formulated as an inverse problem. An optimization model utilising a sparsity-enforcing Cauchy regularizer is proposed, and an alternating minimization framework is used to solve it, in which the desired image and the phase errors are optimized alternatively. For the image reconstruction sub-problem (f-sub-problem), two methods are presented capable of handling the problem's complex nature, and we thus present two variants of our SAR image autofocusing algorithm. Firstly, we design a complex version of t…
Millimeter-wave radars are being increasingly integrated into commercial vehicles to support advanced driver-assistance system features. A key shortcoming for present-day vehicular radar imaging is poor azimuth resolution (for side-looking operation) due to the form factor limits on antenna size and placement. In this paper, we propose a solution via a new multiple-input and multiple-output synthetic aperture radar (MIMO-SAR) imaging technique, that applies coherent SAR principles to vehicular MIMO radar to improve the side-view (angular) resolution. The proposed 2-stage hierarchical MIMO-SAR …
Waveform Design for Joint Communication and SAR Imaging Under Random Signaling
针对传统SAR系统无法传输通信信息的问题，提出基于OFDM信号的JCASAR系统，利用LS估计器与RCMC实现成像，并通过最小化MSE优化波形设计，实现通信与成像性能的灵活折衷。
Near-Field SAR Imaging of Moving Targets on Roads
本文提出一种单通道SAR快速反向投影算法，利用多级插值和粗图像聚合，在近场圆形轨迹聚束模式下高效检测道路上的移动与静止车辆并生成高保真图像。
Fast and Robust LRSD-based SAR/ISAR Imaging and Decomposition
本文提出了一种快速且统一的联合SAR成像框架，通过稳健的LRSD分解和增强图像背景中的稀疏物体和低秩特征，以提高成像质量和降低计算成本。
In the next generations of cellular communication networks, higher density of base stations and higher frequency bands will be adopted. If being reflected by targets, the communication signal also brings information of the targets, in addition to the communication messages, to the receivers. In this paper, it is proposed to leverage the reflected communication signals to reconstruct an image of the environment. Due to the analogy to traditional synthetic aperture radar (SAR) and inverse SAR (ISAR), the principles of SAR and ISAR, namely the tomography via Fourier transformation, are adopted wi…
This paper deals with the analysis, estimation, and compensation of trajectory errors in automotive-based Synthetic Aperture Radar (SAR) systems. First of all, we define the geometry of the acquisition and the model of the received signal. We then proceed by analytically evaluating the effect of an error in the vehicle's trajectory. Based on the derived model, we introduce a motion compensation (MoCo) procedure capable of estimating and compensating constant velocity motion errors leading to a well-focused and well-localized SAR image. The procedure is validated using real data gathered by a 7…
Efficient 3-D Near-Field MIMO-SAR Imaging for Irregular Scanning Geometries
针对车载、无人机等场景下不规则扫描几何的近场SAR成像难题，提出可数学分解任意采样几何、抑制多基地成像伪影的新算法，实现高分辨率高效成像，适配边缘计算受限场景。
This paper presents a quadrature compressive sampling (QuadCS) and associated fast imaging scheme for synthetic aperture radar (SAR). Different from other analog-to-information conversions (AIC), QuadCS AICs using independent spreading signals sample the SAR echoes due to different transmitted pulses. Then the resulting sensing matrix has lower correlation between any two columns than that by a fixed spreading signal, and better SAR image can be reconstructed. With proper setting of the spreading signals in QuadCS, the sensing matrix has the structures suitable for fast computation of matrix-v…
Fast High-Quality Enhanced Imaging Algorithm for Layered Dielectric Targets Based on MMW MIMO-SAR System
本文针对非均匀MIMO-SAR系统，在DT-FDA基础上结合ADMM框架和最优正则化参数搜索，提出一种快速高质量介电目标成像算法，在聚焦、旁瓣抑制和三维精度上优于IBP和DT-FDA，并大幅提升成像效率。
Implementation of Real-Time Automotive SAR Imaging
针对车载SAR成像实时性需求，本文通过分析基于反向投影算法的成像过程，在GPU上测试多种优化方案，结合所有措施后用标准GPU可在30ms内重建30m×30m、8192个线性调频脉冲的高分辨率图像，证明车载SAR实时实现可行。
Automotive synthetic aperture radar (SAR) systems are rapidly emerging as a candidate technological solution to enable a high-resolution environment mapping for autonomous driving. Compared to lidars and cameras, automotive-legacy radars can work in any weather condition and without an external source of illumination, but are limited in either range or angular resolution. SARs offer a relevant increase in angular resolution, provided that the ego-motion of the radar platform is known along the synthetic aperture. In this paper, we present the results of an experimental campaign aimed at assess…
3D-Image Reconstruction using MIMO-SAR FMCW Radar
针对传统SAR成像局限于二维信息的问题，本文提出一种结合虚拟MIMO FMCW雷达与SAR技术的快速时域重建算法，实现了毫米波频段的高分辨率三维雷达成像。
Synthetic aperture radar (SAR) tomography (TomoSAR) enables the reconstruction and three-dimensional (3D) localization of targets based on multiple two-dimensional (2D) observations of the same scene. The resolving along the elevation direction can be treated as a line spectrum estimation problem. However, traditional super-resolution spectrum estimation algorithms require multiple snapshots and uncorrelated targets. Meanwhile, as the most popular TomoSAR imaging method in modern years, compressed sensing (CS) based methods suffer from the gridding mismatch effect which markedly degrades the i…
In this paper, we present an approach for ground moving target imaging (GMTI) and velocity recovery using synthetic aperture radar. We formulate the GMTI problem as the recovery of a phase-space reflectivity (PSR) function which represents the strengths and velocities of the scatterers in a scene of interest. We show that the discretized PSR matrix can be decomposed into a rank-one, and a highly sparse component corresponding to the stationary and moving scatterers, respectively. We then recover the two distinct components by solving a constrained optimization problem that admits computational…
ARSAR-Net: Adaptively Regularized SAR Imaging Network with Efficient Unfolding
提出ARSAR-Net，通过可学习正则化器实现场景无关的SAR成像，并设计无矩阵求逆的ADMM高效展开，成像质量提升达2.0 dB，速度提升50%。
Integrating Low-Altitude SAR Imaging into UAV Data Backhaul
本文提出一种数据辅助的OFDM-SAR成像框架，利用上行通信数据符号进行传感，通过统一的时频域滤波框架抑制数据随机性，提升动态无人机信道中的高分辨率成像性能。
Extended Spherical Geometry Algorithm for Spaceborne SAR Processing in Stripmap and TOPS Imaging Modes
针对原始SGA仅适用于聚束模式的局限，提出扩展SGA，通过瞬时多普勒质心去除和匹配滤波改进，实现条带与TOPS模式星载SAR高效精确成像。
Exploring ISAC Technology for UAV SAR Imaging
本文探讨在sub-6 GHz频段将无人机作为空中基站，利用ISAC系统实现SAR成像的潜力，提出两种信号处理方法，通过仿真与搭载SDR的无人机实验验证了系统在通信标准约束下对掩埋目标成像的有效性。
Entropy-Based Doppler Centroid Estimation and Speckle Noise Reduction for Spaceborne SAR Imaging
针对星载SAR成像中多普勒质心频率未补偿导致散焦、斑点噪声降低图像质量的问题，提出基于图像熵的多普勒质心小数部分估计方法与斑点噪声抑制算法，经RADARSAT-1卫星数据验证有效提升了成像质量。
The joint interpretation of very high resolution SAR and optical images in dense urban area are not trivial due to the distinct imaging geometry of the two types of images. Especially, the inevitable layover caused by the side-looking SAR imaging geometry renders this task even more challenging. Only until recently, the "SARptical" framework [1], [2] proposed a promising solution to tackle this. SARptical can trace individual SAR scatterers in corresponding high-resolution optical images, via rigorous 3-D reconstruction and matching. This paper introduces the SARptical dataset, which is a data…
Tomographic synthetic aperture radar (TomoSAR) imaging algorithms based on deep learning can effectively reduce computational costs. The idea of existing researches is to reconstruct the elevation for each range-azimuth cell in one-dimensional using a deep-unfolding network. However, since these methods are commonly sensitive to signal sparsity level, it usually leads to some drawbacks like continuous surface fractures, too many outliers, \textit{et al}. To address them, in this paper, a novel imaging network (AETomo-Net) based on multi-dimensional features is proposed. By adding a U-Net-like …
Deep learning (DL)-based tomographic SAR imaging algorithms are gradually being studied. Typically, they use an unfolding network to mimic the iterative calculation of the classical compressive sensing (CS)-based methods and process each range-azimuth unit individually. However, only one-dimensional features are effectively utilized in this way. The correlation between adjacent resolution units is ignored directly. To address that, we propose a new model-data-driven network to achieve tomoSAR imaging based on multi-dimensional features. Guided by the deep unfolding methodology, a two-dimension…
Efficient CNN-based Super Resolution Algorithms for mmWave Mobile Radar Imaging
针对徒手智能手机近场SAR成像中不规则采样数据难获高效高分辨率图像的问题，提出结合前沿SAR处理与深度学习的新型CNN超分辨率架构，经仿真和实证验证可在不规则扫描近场场景下实现高效高分辨雷达成像。
UAV SAR Imaging with 5G NR OFDM Signals in NLOS Environments
提出一种协作ISAC框架，利用5G NR OFDM信号在NLOS环境下进行UAV SAR成像，并开发两阶段CS-SAGE方案实现高精度散射体定位，有效解决了成像退化问题。
We analyze synthetic aperture radar (SAR) imaging of complex ground scenes that contain both stationary and moving targets. In the usual SAR acquisition scheme, we consider ways to preprocess the data so as to separate the contributions of the moving targets from those due to stationary background reflectors. Both components of the data, that is, reflections from stationary and moving targets, are considered as signal that is needed for target imaging and tracking, respectively. The approach we use is to decompose the data matrix into a low rank and a sparse part. This decomposition enables us…
This paper proposes the use of sufficient cyclic prefix (CP) OFDM synthetic aperture radar (SAR) for foliage penetration (FOPEN). The foliage introduces phase and amplitude fluctuation which cause the sidelobes to increase and affects the final image of the obscured targets. The wideband CP-based OFDM SAR inherently eliminates the sidelobes that arise from the interference between targets on the same range line. The integrated sidelobe level ratio (ISLR) of the CP-based OFDM signal along the range direction is lower than that of the random noise signal by 2 dB for foliage penetration applicati…
Unmanned aerial vehicle (UAV) can provide superior flexibility and cost-efficiency for modern radar imaging systems, which is an ideal platform for advanced remote sensing applications using synthetic aperture radar (SAR) technology. In this paper, an energy-efficient passive UAV radar imaging system using illuminators of opportunity is first proposed and investigated. Equipped with a SAR receiver, the UAV platform passively reuses the backscattered signal of the target scene from an external illuminator, such as SAR satellite, GNSS or ground-based stationary commercial illuminators, and achie…
SAR/ISAR Imaging in 6G Network
本文提出两种高分辨率无线电成像方案，利用多普勒信息实现6G网络下的成像，无需范围估计，解决了带宽限制问题。
DIFNet: SAR RFI suppression based on domain invariant features
针对SAR成像中的RFI抑制与跨传感器泛化问题，本文提出DIFNet，通过重构损失函数提取干扰的域不变特征，并将抑制过程嵌入成像流程。
A Vision Transformer Approach for Efficient Near-Field Irregular SAR Super-Resolution
针对近场不规则SAR成像在位置估计误差下散焦且保真度低的问题，提出首个采用移动友好ViT架构的Mobile-SRViT算法，有效解决误差并实现SAR图像超分辨率增强。
A Robust Super-resolution Gridless Imaging Framework for UAV-borne SAR Tomography
针对无人机载SAR层析成像，提出一种利用慢速平台PRF冗余构建多测量矢量模型，并采用原子范数软阈值算法实现无网格超分辨重建的鲁棒成像框架，经仿真与飞行实验验证有效。
ATASI-Net: An Efficient Sparse Reconstruction Network for Tomographic SAR Imaging with Adaptive Threshold
针对传统压缩感知类层析SAR成像方法抗噪弱、复杂度高、调参复杂的问题，提出带自适应阈值的ATASI-Net稀疏展开网络，预计算权重仅需学习两个参数，逐像素自适应阈值可结合语义，经模拟与真实数据验证兼具有效性与高效性。
UAV-Borne Digital Radar System for Coherent Multistatic SAR Imaging
本文提出一种搭载于无人机、采用OFDM波形的L波段数字雷达系统，通过主发射节点与无源接收节点保持快慢时间相干，并经静态测量和双基地SAR实验验证其高分辨率多基地成像能力。
Target Detection in Sea Clutter with Application to Spaceborne SAR Imaging
本文提出利用Weibull分布和CFAR算法改进海杂波中目标检测的方法，通过实验验证其有效性。
Inevitable interferences exist for the SAR system, adversely affecting the imaging quality. However, current analysis and suppression methods mainly focus on the far-field situation. Due to different sources and characteristics of interferences, they are not applicable in the near field. To bridge this gap, in the first time, analysis and the suppression method of interferences in near-field SAR are presented in this work. We find that echoes from both the nadir points and the antenna coupling are the main causes, which have the constant-time-delay feature. To characterize this, we further est…
RIS-Aided Radar Imaging Utilizing the Virtual Source Principle
本文提出将RIS辅助雷达成像视为移动虚拟源SAR成像，在波数域建模并制定近远场成像算法，为适配成熟SAR方法开辟新途径。
Originally developed in fields such as robotics and autonomous driving with image-based navigation in mind, deep learning-based single-image depth estimation (SIDE) has found great interest in the wider image analysis community. Remote sensing is no exception, as the possibility to estimate height maps from single aerial or satellite imagery bears great potential in the context of topographic reconstruction. A few pioneering investigations have demonstrated the general feasibility of single image height prediction from optical remote sensing images and motivate further studies in that directio…
Imaging-Communication Trade-off in VLEO ISAC-SAR Using CP-OFDM
本文针对VLEO ISAC-SAR，建立统一分析框架，推导图像域统计特性并提出ENESZ指标，揭示CP持续时间作为设计参数在成像质量与通信吞吐量之间的可扩展权衡。
As an emerging approach to space situational awareness and space imaging, the practical use of an event-based camera in space imaging for precise source analysis is still in its infancy. The nature of event-based space imaging and data collection needs to be further explored to develop more effective event-based space image systems and advance the capabilities of event-based tracking systems with improved target measurement models. Moreover, for event measurements to be meaningful, a framework must be investigated for event-based camera calibration to project events from pixel array coordinate…
UAV SAR Imaging via Diffusion Posterior Sampling under Non-Ideal Motion in ISAC Systems
针对ISAC系统无人机SAR非理想运动导致的图像散焦问题，本文提出基于DPS的超分辨率SAR框架及联合DPS与MoCo算法，仿真验证其在多样轨迹与未知运动误差下的优异成像性能。
A Novel Gradient Descent Least Squares (GDLS) Algorithm for Efficient SMV Gridless Line Spectrum Estimation with Applications in Tomographic SAR Imaging
本文提出GDLS算法，将SMV无网格线谱估计转化为最小二乘问题并用梯度下降迭代求解，以低于ANM的复杂度避免离网问题，并在TomoSAR成像中验证了性能。
Integrated Communication and Remote Sensing in LEO Satellite Systems: Protocol, Architecture and Prototype
本文提出LEO卫星中基于ODDM波形的一体化通信与SAR遥感架构，兼容5G NR协议，并设计统一信号处理框架，通过仿真和SDR原型验证了实时成像与传输性能。
3D Radar Imaging from the UAV Nadir
针对无人机天底视角的三维雷达成像问题，本文提出基于低成本MIMO毫米波雷达的InSAR框架及PGA相位误差补偿方法，经仿真与实验验证了算法的有效性。
Emerging Approaches for THz Array Imaging: A Tutorial Review and Software Tool
本文综述了近场太赫兹SAR成像的系统与算法，重点介绍结合信号处理与机器学习的新兴方法，涵盖安全检测与图像超分辨率，并探讨基准标准化与未来研究方向。
Deep Denoising Prior-Based Spectral Estimation for Phaseless Synthetic Aperture Radar
提出一种基于深度去噪先验的无相位SAR成像方法，通过在频谱估计的幂迭代中引入深度去噪器并在即插即用框架下构建深度成像网络，扩展了无相位成像的适用性。
A problem with synthetic aperture radar (SAR) is that due to the poor penetrating action of electromagnetic waves within solid bodies, the ability to observe through distributed targets is precluded. In this context, indeed, imaging is only possible on targets distribute on the scene surface. This work describes an imaging method based on the analysis of micro-motions present on volcanoes and generated by the underground Earth's heat. Processing the coherent vibrational information embedded on the single SAR image, in the single-look-complex configuration, the sound information is exploited, p…
Diffusion-Prior Split Gibbs Sampling for Synthetic Aperture Radar Imaging under Incomplete Measurements
本文提出一种基于扩散的分割吉布斯采样框架，通过整合测量保真度与学习的扩散先验，提升SAR成像在不完整测量下的重建性能。
Spherical Geometry Algorithm for Space-borne Synthetic Aperture Radar Imaging
本文针对星载SAR高分辨率宽幅成像中弯曲轨道、地球自转和球面地表等挑战，利用球面几何特性推导精确傅里叶变换关系，提出基于傅里叶反演的成像算法，兼具高聚焦精度和高计算效率。
We consider a bistatic configuration with a stationary transmitter transmitting unknown waveforms of opportunity and a moving receiver, and present a Deep Learning (DL) framework for passive synthetic aperture radar (SAR) imaging. Existing passive radar methods require two or more antennas which are either spatially separated or colocated with sufficient directivity to estimate the underlying waveform prior to imaging. Our approach to passive radar only requires a single receiver, hence reduces cost and increases versatility. We approach DL from an optimization perspective and formulate image …
The classification of large-scale high-resolution SAR land cover images acquired by satellites is a challenging task, facing several difficulties such as semantic annotation with expertise, changing data characteristics due to varying imaging parameters or regional target area differences, and complex scattering mechanisms being different from optical imaging. Given a large-scale SAR land cover dataset collected from TerraSAR-X images with a hierarchical three-level annotation of 150 categories and comprising more than 100,000 patches, three main challenges in automatically interpreting SAR im…
Deep Learning-Based Multiband Signal Fusion for 3-D SAR Super-Resolution
针对高带宽3-D SAR成像成本高、现有多波段融合方法不适用于复杂真实场景的问题，提出基于双域复值CNN的kR-Net融合多波段信号填补频率间隙，实现复杂目标高分辨率成像，并搭建了集成毫米波雷达系统。
A Reconfigurable Pipelined-SAR ADC with Embedded Compression for Temporal Compressed-Sensing Ultrasound Imaging
该研究提出嵌入式压缩的可重构流水线SAR ADC，用于超声成像的RF数据时间压缩，在保留点目标几何的同时降低数据速率，且可通过压缩比权衡性能。
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