Airborne Synthetic Aperture Radar System Research Articles

Impact Analysis and Compensation Methods of Frequency Synchronization Errors in Distributed Geosynchronous Synthetic Aperture Radar

Frequency synchronization error, as one of the inevitable technical challenges in distributed synthetic aperture radar (SAR), has different impacts on different SAR systems. Multi-monostatic SAR is a typical distributed configuration where frequency synchronization errors are tiny in distributed airborne and low earth orbit (LEO) SAR systems. However, due to the long time delay and long synthetic aperture time, the imaging performance of a multi-monostatic geosynchronous (GEO) SAR system is affected by frequency oscillator errors. In this paper, to investigate the frequency synchronization problem in this configuration, we firstly model the echo signals with the frequency synchronization errors, which can be divided into fixed frequency errors and random phase noise. Secondly, we talk about the impacts of the two kinds of errors on imaging performance. To solve the problem, we thirdly propose an autofocus back-projection (ABP) algorithm, which adopts the coordinate descent method and iteratively adjusts the phase error estimation until the image reaches its maximum sharpness. Based on the characteristics of the frequency synchronization errors, we further propose the Node ABP (NABP) algorithm, which greatly reduces the amount of storage and computation compared to the ABP algorithm. Finally, simulations are carried out to validate the effectiveness of the ABP and NABP algorithms.

Recognition for SAR deformation military target from a new MiniSAR dataset using multi-view joint transformer approach

Accurately detecting ground armored weapons is crucial for achieving initiative advantages in military operations. Generally, satellite or airborne synthetic aperture radar (SAR) systems face limitations due to their revisit cycles and fixed flight trajectories, resulting in single-view imaging of targets, thereby hampering the recognition of small SAR ground targets. In contrast, MiniSAR possesses the capability to capture the multi-view of a target by acquiring images from different azimuth angles. In this research, our team utilizes a self-developed MiniSAR system to generate multi-view SAR images of real ground armored targets and recognize targets. However, the recognition of small targets in SAR images encounters two significant difficulties. First, small targets in SAR images are prone to interference from background noise. Second, SAR target deformation arises from variations in depression angles and imaging processes. To tackle these difficulties, this paper proposes a novel SAR ground deformation target recognition approach based on a joint multi-view transformer model. The method first preprocesses SAR images based on a low-frequency priori SAR image denoising method. Next, it obtains multi-view joint information through a self-attentive mechanism, inputs joint features to the transformer structure. The outputs are jointly updated by a multi-way averaging adaptive loss function to improve the recognition accuracy of deformed targets. The experimental results demonstrate the superiority of the proposed method in SAR ground deformation target recognition, outperforming other representative approaches such as information fusion of target and shadow (IFTS) and Vision Transformer (ViT). It is concluded that the proposed method has high recognition accuracies of 98.37% and 93.86 % on the moving and stationary target acquisition and recognition (Mstar) and our SAR images dataset, respectively, in the field of SAR ground deformation target recognition. We have included links to the code and data in the abstract of this paper for ease of access. The source code and sample dataset are available at https://github.com/Lvjiming/MJT.

A Novel Point Target Attitude Compensation Method Using Electromagnetic Reflectance Theory

During the process of the airborne synthetic aperture radar (SAR) system platform in space, platform attitude deflection is inevitable. However, large attitude deflection angles are unacceptable for polarimetric calibration using point targets, especially the dihedral, which is very sensitive to the pointing angle of the radar. To mitigate the impact of attitude angles on calibration accuracy, attitude compensation of the corner reflector is necessary during the calibration process. The conventional approach to attitude compensation typically maps the three-dimensional attitude angle information to the one-dimensional polarimetric orientation angle (POA) information. However, the reduction of dimension inevitably results in information loss, leading to errors that affect calibration performance when the attitude angle is large. In order to ensure the accuracy of point target calibration, this paper proposes a novel point target compensation method based on the reflection theory of electromagnetic waves. This method is based on three-dimensional attitude angle information and has higher reliability than the POA method. Finally, this paper calculates the distance between the scattering matrices obtained after compensation based on the proposed method and the POA method to obtain the difference in the performance of the two methods. Through a simulation, this paper finds that when the attitude angle is small, the results of the two schemes are approximately the same, but as the attitude angle increases, the error between the two gradually increases. This suggests that the proposed method has greater advantages in the case of attitude deflection. Furthermore, the proposed method does not require additional information supplementation compared with the equivalent POA method, making it highly practical.

Analysis of Geometric Characteristics and Coverage for Moon-Based/Spaceborne Bistatic SAR Earth Observation

With the rapid development of Earth system science, a new understanding of the complete Earth system has highlighted the crucial importance of integrated observations, especially in research involving large-scale geoscience phenomena. As an active sensor with all-time and all-weather capabilities, synthetic aperture radar (SAR) has been widely used in recent decades for Earth observation. However, the existing spaceborne, airborne, and ground-based SAR systems have difficulty providing temporally consistent and spatially continuous Earth observation data on a global scale. As Earth’s only natural satellite, the Moon is a very promising Earth observation platform. By deploying a transmitter on the Moon and a receiver on the high-orbit satellite, a Moon-based/spaceborne bistatic synthetic aperture radar (MS-BiSAR) can be formed. In this paper, the MS-BiSAR geometric model of Earth observation was established using ephemeris and orbit propagators with reference system transformations, and three different MS-BiSAR configurations were used to calculate and analyze their geometric characteristics and Earth observation coverage. The results show that with the advantage of wide swaths, continuous observation capabilities, and large coverage, such an MS-BiSAR could significantly contribute to monitoring and understanding large-scale geoscience phenomena.

A novel linear frequency modulation signal generator in real‐time processing of airborne synthetic aperture radar

Generally, synthetic aperture radar(SAR)generates linear frequency modulation (LFM) signals by method of look-up table (LUT), which requires calculating different LFM signals and storing these waveforms in advance. With the demand for multi-mode, high-resolution and wide swath of airborne SAR systems, the method of LUT is not available, because that requires huge storage resources. In order to solve these drawbacks in limited hardware resources, this letter proposes a novel LFM signal generator in real-time processing. By taking advantage of high level synthesis (HLS) on FPGA, the proposed generator calculates the LFM signal simply using parameters of pulse width, bandwidth, and sampling frequency. Meanwhile, in order to compensate for the SAR system phase error, the proposed generator calculates phase error using a linear polynomial algorithm, which can compensate for the phase error in real time. The simulation results prove that this approximation can achieve a good effect. The performance of this method is implemented by experiments with an X-band airborne SAR system.

Statistical Theory of Optimal Stochastic Signals Processing in Multichannel Aerospace Imaging Radar Systems

The work is devoted to solving current scientific and applied problems of the development of radar imaging methods. These developments are based on statistical theory of optimal signal processing. These developments allow researchers to create coherent high-resolution information-enriched images as well as incoherent images. These methods can be practically applied in multichannel aerospace radars through the proposed programs and algorithms. Firstly, the following models of stochastic signals at the output of multichannel registration regions of scattered electro-magnetic fields, internal noise, and observation equations are developed and their statistical characteristics investigated. For the considered models of observation equations, the likelihood functional is defined. This definition is an important stage in optimizing spatial and temporal signal processing. These signals are distorted by internal receiver noises in radar systems. Secondly, by synthesising and analysing methods of measuring a radar cross section, the problem of incoherent imaging by aerospace radars with planar antenna array is solved. Thirdly, the obtained optimal mathematical operations are physically interpreted. The proposed interpretation helps to implement a quasi-optimal algorithm of radar cross section estimation in aerospace radar systems. Finally, to verify the proposed theory, a semi-natural experiment of real radio holograms processing was performed. These radio holograms are digital recordings of spatial and temporal signals by an airborne synthetic aperture radar (SAR) system. The results of the semi-natural experiment are presented and analysed in the paper. All the calculations, developments and results in this paper can be applied to new developments in areas such as remote sensing or non-destructive testing.

An Integrated Raw Data Simulator for Airborne Spotlight ECCM SAR

Airborne synthetic aperture radar (SAR) systems often encounter the threats of interceptors or electronic countermeasures (ECM) and suffer from motion measurement errors. In order to design and analyze SAR systems while considering such threats and errors, an integrated raw data simulator is proposed for airborne spotlight electronic counter-countermeasure (ECCM) SAR. The raw data for reflected echo signals and jamming signals are generated in arbitrary waveform to achieve pulse diversity. The echo signals are simulated based on the scene model computed through the inverse polar reformatting of the reflectivity map. The reflectivity map is generated by applying a noise-like speckle to an arbitrary grayscale optical image. The received jamming signals are generated by the jamming model, and their powers are determined by the jamming equivalent sigma zero (JESZ), a newly proposed quantitative measure for designing ECCM SAR systems. The phase errors due to the inaccuracy of the navigation system are also considered in the design of the proposed simulator, as navigation sensor errors were added in the motion measurement process, with the results used for the motion compensation. The validity and usefulness of the proposed simulator is verified through the simulation of autofocus algorithms, SAR jamming, and SAR ECCM with pulse diversity. Various types of autofocus algorithms were performed through the proposed simulator and, as a result, the performance trends were identified to be similar to those of the real data from actual flight tests. The simulation results of the SAR jamming and SAR ECCM indicate that the proposed JESZ is well-defined measure for quantifying the power requirements of ECCM SAR and SAR jammers.

Enhanced compressed sensing autofocus for high-resolution airborne synthetic aperture radar

The limited accuracy of the navigation system leads to deviations between the real and measured trajectories in airborne synthetic aperture radar (SAR) which results in residual motion (phase) errors and seriously degrades the image quality. The residual errors are usually corrected by using autofocus methods. In this paper, we investigate the autofocus for a high-resolution airborne SAR system which employs stepped-frequency chirp (SFC) signal to achieve high range resolution. As a promising waveform to improve radar range resolution, the SFC signal is widely realized in practical systems. We characterize the backscattering from the scene, phase errors, and receiver noise with a linear matrix-based formulation. In addition, we propose a compressed sampling method that is directly applied to the scene and received signal to provide a sparse raw dataset. We describe the autofocus problem as a constrained optimization problem and propose a new compressed sensing (CS)-based autofocus method to solve it. This method iteratively estimates the phase error and reconstructs the high-resolution SAR image. The image reconstruction is based on the proximity algorithm which applies the shrinkage proximal operator to solve the problem in a computationally efficient manner. We validate the effectiveness of the proposed method using both simulated and real SAR images. Based on visual results and a variety of metrics, the proposed method outperforms the classical autofocus approaches. Also, it provides better or comparable results, with much lower computational complexity, in comparison to that of the recent CS-based autofocus methods.

Parallel Optimisation and Implementation of a Real-Time Back Projection (BP) Algorithm for SAR Based on FPGA.

This study conducts an in-depth evaluation of imaging algorithms and software and hardware architectures to meet the capability requirements of real-time image acquisition systems, such as spaceborne and airborne synthetic aperture radar (SAR) systems. By analysing the principles and models of SAR imaging, this research creatively puts forward the fully parallel processing architecture for the back projection (BP) algorithm based on Field-Programmable Gate Array (FPGA). The processing time consumption has significant advantages compared with existing methods. This article describes the BP imaging algorithm, which stands out with its high processing accuracy and two-dimensional decoupling of distance and azimuth, and analyses the algorithmic flow, operation, and storage requirements. The algorithm is divided into five core operations: range pulse compression, upsampling, oblique distance calculation, data reading, and phase accumulation. The architecture and optimisation of the algorithm are presented, and the optimisation methods are described in detail from the perspective of algorithm flow, fixed-point operation, parallel processing, and distributed storage. Next, the maximum resource utilisation rate of the hardware platform in this study is found to be more than 80%, the system power consumption is 21.073 W, and the processing time efficiency is better than designs with other FPGA, DSP, GPU, and CPU. Finally, the correctness of the processing results is verified using actual data. The experimental results showed that 1.1 s were required to generate an image with a size of 900 × 900 pixels at a 200 MHz clock rate. This technology can solve the multi-mode, multi-resolution, and multi-geometry signal processing problems in an integrated manner, thus laying a foundation for the development of a new, high-performance, SAR system for real-time imaging processing.

Three Dimension Airborne SAR Imaging of Rotational Target With Single Antenna and Performance Analysis

For the target with 3-D rotation, the 3-D synthetic aperture radar (SAR) imaging is very important for the feature extraction and classification. To solve this issue, a novel 3-D imaging algorithm through the airborne SAR system with a single antenna is proposed in this article, which has great advantages for the simplification of system structure compared with the traditional interferometric system. The proposed 3-D airborne SAR imaging algorithm can be implemented with three steps: 1) the azimuth signal is modeled as multicomponent linear frequency modulation (LFM) signal due to the relative movement between the target and radar. 2) The scatterer height position can be obtained by estimating the frequency modulation rate (FMR) for the LFM signal. 3) The 3-D airborne SAR image is obtained via the range-Doppler (RD) algorithm. Furthermore, the reconstruction performance under different rotation patterns, including roll, pitch, and yaw, is analyzed. The availability of the presented novel technique is demonstrated by the results of simulated and real experimental data.

The Effects of Dry Snow on the SAR Impulse Response and Feasibility for Single Channel Snow Water Equivalent Estimation

Snow water equivalent (SWE) is an important surface parameter for understanding a number of Earth system processes. Synthetic aperture radar (SAR) has considerable potential for measuring SWE of dry-snow because SAR can penetrate through the snow to the ground surface and is both amplitude- and phase-sensitive to refraction from the snow. Previous work on refraction-based SWE measurement by SAR has utilized the repeat-pass InSAR phase signal to estimate changes in SWE that occur between SAR acquisitions. These are subject to temporal decorrelation effects and consider only the refraction that occurs along the SAR beam center rather than the entire synthetic aperture. This study examines the refractive effect of dry-snow along the synthetic aperture and its impact on SAR image formation including defocusing and phase bias of the system impulse response. Snow phase compensation during time domain processing to recover the snow-free impulse response function (IRF) is described and demonstrated. The feasibility of using the mapdrift and image sharpness autofocus methods to estimate SWE is examined, and the effect of key system parameters on the estimation performance is derived. Experimental validation of the method was conducted by acquiring L-band data with the Simon Fraser University (SFU) Airborne SAR System over a pair of corner reflectors installed on the Kluane icefield in northwestern Canada. Results from both simulations and the icefield experiment are presented and compared including an analysis of errors affecting the estimation.

Multichannel SAR Moving Target Detection via RPCA-Net

Ground moving target indication (GMTI), as a challenging task for synthetic aperture radar (SAR) systems, keeps drawing considerable attention. Robust principal component analysis (RPCA) aiming at separating low-rank and sparse components has been successfully employed in SAR systems for GMTI recently. However, its practical application is limited by the heavy computational burden as well as the requirement of manual parameter modification. To cope with this problem, a fast and free of presetting parameters RPCA network (RPCA-Net) is proposed for SAR-GMTI under strong clutter background. In the proposed method, a novel RPCA model is first introduced, where not only the low-rank and sparse terms but also the errors in practical SAR systems are taken into account. Moreover, the low-rank factorization plus scaled gradient descent (ScaledGD) is also employed to acquire low-rank clutter background rather than singular value decomposition (SVD). Then, we parameterize our proposed RPCA model and unfold it as a feedforward neural network (FNN) to acquire the iterative parameters through backpropagation. Compared to the GMTI methods based on traditional RPCA models, our proposed RPCA-Net can provide a higher detection ability and faster convergence without presetting parameters empirically. Experiments on two groups of measured data collected by airborne SAR systems validate the superior performance of the proposed RPCA-Net.

Forest height retrieval using P-band airborne multi-baseline SAR data: A novel phase compensation method

Synthetic aperture radar (SAR) tomography (TomoSAR) has been well-established for three-dimensional (3-D) information extraction of forests using the multi-baseline SAR data stacks. The multi-baseline SAR data stacks can be acquired by spaceborne and airborne SAR systems, but for forest scenarios, the data stacks acquired by the airborne SAR system are mostly used. Such a data stack has the advantages of short revisiting time and weak temporal decorrelation. However, due to the baseline errors (caused by the residual platform motion and the measurement errors of the navigation instruments), phase errors (PEs) will occur. PEs are independent of one track to the other, resulting in spreading and defocusing in tomographic imaging. In this paper, we proposed a novel phase compensation method named NC-PGA, which combines the methods of network construction (NC) and phase gradient autofocus (PGA) to estimate and compensate the PEs. The NC method uses the Delaunay triangulation network and beamforming to obtain an accurate elevation estimate of the selected permanent scatterers, which can be used as the prior information for subsequent processing to overcome the shortcomings of the PGA method in PEs estimation. The PGA method uses the spatial invariance of PEs in a limited area to compensate for the PE of each track. The applicability of the NC-PGA method is demonstrated using simulated data and real data. The real data contains two data stacks. The one is acquired by a full-polarization P-band airborne SAR system (developed independently by our project research team) over the study area in Saihanba Forest Farm in Hebei, China. The other one is acquired by ONERA SETHI airborne system over Paracou, French Guiana, in the frame of the European Space Agency’s campaign TropiSAR. We select a test area in the study area and successfully retrieve the height of the forest, and use LiDAR data for results validation and evaluation.

A Modified Capon Method for SAR Tomography Over Forest

The 3-D structure of forests is an important indicator for evaluating forest health and can provide data support for ecological monitoring and protection. Synthetic aperture radar (SAR) tomography (TomoSAR) is an important technology for forest structure estimation using the multibaseline (MB) SAR data stacks. The spectral estimators, such as the Capon method, are usually used to estimate the 3-D reflectivity along elevation direction. In this letter, a modified Capon (M-Capon) method is proposed to improve the estimated profiles of ground and canopy scatterers in the elevation direction, including the estimation accuracy and resolution. This method combines the ideas of the CLEAN algorithm with the Capon method and uses iteration to improve the resolution and accuracy of the estimation. The effectiveness of the M-Capon method is demonstrated using the simulated data and the MB SAR data acquired by the P-band airborne SAR system over the Saihanba Forest Farm in Hebei, China.

Ship Target Imaging in Airborne SAR System Based on Automatic Image Segmentation and ISAR Technique

The airborne synthetic aperture radar (SAR) image of ship target will be blurred for the complex motion of the target, which will influence the performance of feature extraction and target classification. In this article, a refocusing method of ship target in airborne SAR image though the inverse synthetic aperture radar (ISAR) technique is presented. The novel contributions of this article can be summarized as follows: 1) the residual phase of processed signal is analyzed in detail to illustrate the necessity of adopting ISAR technique; 2) a valid, labor-saving, and automatic image segmentation approach via clustering algorithm is put forward for automatic data extraction and inverse mapping. The clustering algorithm we choose is the agglomerative hierarchical cluster algorithm, which does not require the number of categories in advance; 3) the refocused individual ISAR image of individual ship target is yielded though the range-instantaneous Doppler algorithm. Finally, the simulated and real measured data are processed, and imaging results verify the effectiveness of the novel algorithm presented in this article.

Hybrid‐fed shared aperture antenna array for X/K‐band airborne synthetic aperture radar applications

The design of X/K-band shared aperture antenna (SAA) single-linear polarized K-band, dual-polarized (linear/circular) X-band 36-elements (6×6) planar array antenna with high gain, and low cost for airborne synthetic aperture radar systems is presented. To reduce the complexity and size of the feed networks, the concept of series-feed centre-fed open stub array with Chebyshev amplitude distribution of −25 dB side-lobe levels (SLL) are employed for K-band design. Two typical frequencies, X-band and K-band of 9.65 and 21 GHz, are chosen (frequency ratio of 1:2.176) in this proposed SAA design on a single-layer printed circuit board. For K-band design, SLL can be controlled by Chebyshev distribution. The amplitude is controlled by the width of the individual patch in the linear array with left and right symmetries. A 50-Ω microstrip line with 0.7λ spacing is used in between the patches for the ±25° scan angle requirement. The measured results are consistent with the simulations and provide a matching impedance bandwidth of 10.36/1.45% at X/K-bands, respectively. The array also has a high aperture efficiency of more than 85%, SLL of (X/K-bands: −18.9/−25 dB), and gain of (X/K-bands: 24.2/17.4 dBi).

Internal kinematics of the Slumgullion landslide (USA) from high-resolution UAVSAR InSAR data

Landslides represent one of the most damaging natural hazards and often lead to unexpected casualties and property damage. They also continually modify our natural environment and landscapes. Knowledge of landslide systems is largely restricted by the stochastic nature, subjective interpretation and infrequent or spatially sparse surveying of landslides. Characterized by persistent daily movements of a couple of centimeters over multi-centennial timescales and a long narrow shape as long as ~4 km, the Slumgullion landslide in Colorado, USA represents an ideal natural laboratory to study slow-moving landslides. Here we demonstrate the capability of the highly accurate, spatially continuous airborne Synthetic Aperture Radar (SAR) system of the NASA Uninhabited Aerial Vehicle SAR (UAVSAR) to characterize the kinematic details of internal deformation of the Slumgullion landslide using SAR interferometry (InSAR). We develop a phase-based approach to automatically extract the boundaries of the mobile geological structures without unwrapping. Comparison with historic field observations from 1991 reveals the 40-m advance of the frontal toe and shift of an internal fault. The UAVSAR data also resolve an internal minislide (100 by 70 m), which moves more southerly than the main body at 5 mm/day in the lower part of the landslide. A Light Detection and Ranging (LiDAR) Digital Elevation Model (DEM) shows that the minislide is associated with the opening of a 30 by 10 m pull-apart basin and bounding strike-slip faults. These extensional structures, nearby incised streams, and steepened local slopes helped establish the kinematic environment for the formation of the secondary minislide. The disparity between the UAVSAR InSAR-derived horizontal moving directions and the LiDAR DEM-derived slope aspects suggest that while the surface topography governs the first-order orientation, the local kinematics is also subject to the variable nature of heterogeneous landslide materials and the irregular basal bedrock surface. The landslide velocity and precipitation show similar multi-annual variations. Our study demonstrates that the freely available, high-resolution UAVSAR data, have great potential for characterizing landslide kinematics and other small-scale geological and geomorphological processes.

The High-Resolution Digital-Beamforming Airborne SAR System DBFSAR

Synthetic Aperture Radar (SAR) is an established remote sensing technique that can robustly provide high-resolution imagery of the Earth’s surface. However, current space-borne SAR systems are limited, as a matter of principle, in achieving high azimuth resolution and a large swath width at the same time. Digital beamforming (DBF) has been identified as a key technology for resolving this limitation and provides various other advantages, such as an improved signal-to-noise ratio (SNR) or the adaptive suppression of radio interference (RFI). Airborne SAR sensors with digital beamforming capabilities are essential tools to research and validate this important technology for later implementation on a satellite. Currently, the Microwaves and Radar Institute of the German Aerospace Center (DLR) is developing a new advanced high-resolution airborne SAR system with digital beamforming capabilities, the so-called DBFSAR, which is planned to supplement its operational F-SAR system in near future. It is operating at X-band and features 12 simultaneous receive and 4 sequential transmit channels with 1.8 GHz bandwidth each, flexible DBF antenna setups and is equipped with a high-precision navigation and positioning unit. This paper aims to present the DBFSAR sensor development, including its radar front-end, its digital back-end, the foreseen DBF antenna configuration and the intended calibration strategy. To analyse the status, performance, and calibration quality of the DBFSAR system, this paper also includes some first in-flight results in interferometric and multi-channel marine configurations. They demonstrate the excellent performance of the DBFSAR system during its first flight campaigns.

On the Capabilities of the Italian Airborne FMCW AXIS InSAR System

Airborne Synthetic Aperture Radar (SAR) systems are gaining increasing interest within the remote sensing community due to their operational flexibility and observation capabilities. Among these systems, those exploiting the Frequency-Modulated Continuous-Wave (FMCW) technology are compact, lightweight, and comparatively low cost. For these reasons, they are becoming very attractive, since they can be easily mounted onboard ever-smaller and highly flexible aerial platforms, like helicopters or unmanned aerial vehicles (UAVs). In this work, we present the imaging and topographic capabilities of a novel Italian airborne SAR system developed in the frame of cooperation between a public research institute (IREA-CNR) and a private company (Elettra Microwave S.r.l.). The system, which is named AXIS (standing for Airborne X-band Interferometric SAR), is based on FMCW technology and is equipped with a single-pass interferometric layout. In the work we first provide a description of the AXIS system. Then, we describe the acquisition campaign carried out in April 2018, just after the system completion. Finally, we perform an analysis of the radar data acquired during the campaign, by presenting a quantitative assessment of the quality of the SLC (Single Look Complex) SAR images and the interferometric products achievable through the system. The overall analysis aims at providing first reference values for future research and operational activities that will be conducted with this sensor.

Robust Line Detection of Synthetic Aperture Radar Images Based on Vector Radon Transformation

Line detection on synthetic aperture radar (SAR) images is still challenging due to the existence of strong speckles. This article proposes a novel line detection method for SAR images based on vector Radon transform (VRT). First, the ratio of exponentially weighted averages operator is determined to calculate the edge map. Then, the VRT is proposed to transform the edge map into the parameter map and decompose the parameter map along the angle of projection into two mutually perpendicular components, i.e., parallel component and vertical component, which strips off part of the random edge information and ensures the sharpness of the peaks (local extremum). Peaks are detected in the parallel component. Finally, the intersection analysis technique is adopted to remove the redundant lines. Experiments are carried out with six amplitude-format SAR images of various bands, resolutions, and polarizations from Chinese airborne SAR systems, GaoFen-3 (GF-3) satellite, and TerraSAR-X satellite. The results demonstrate the outperformance of the proposed method. Furthermore, a road edge detection scheme is designed based on the proposed line detection method. The experimental results of the road edge detection further confirm the effectiveness of the proposed method and show its potential for practical use.