Spaceborne Spaceborne Synthetic Aperture Radar Images Research Articles

Application of Quasi-Continuous Waveform Coding in Spaceborne Synthetic Aperture Radar

Quasi-continuous wave radar is an attempt to give consideration to the performance of pulse and continuous wave radar signals. However, it also has the shortcomings of both. This paper aims to add a new quasi-continuous-wave coding method to the spaceborne synthetic aperture radar (SAR) system. The technology of improving spaceborne SAR imaging performance by coding quasi-continuous-wave pulses is studied, and some shortcomings of this algorithm are improved. Firstly, the application of quasi-continuous-wave radar in the SAR system is studied, and the coding and reconstruction scheme is provided so that this technology can be successfully applied in spaceborne SAR. Secondly, the effects of different quasi-continuous-wave coding methods on SAR imaging performance are evaluated, including signal-to-noise ratio, resolution, and integration time. Then, several coding schemes are given, and the characteristic changes of the signal after quasi-continuous-wave coding are analyzed. The transmit–receive conversion loss function and azimuth Doppler ambiguity function of the design scheme are analyzed, which proves the advantages of the scheme. Finally, we design the hardware implementation scheme and carry out the practical test.

MCSNet: A Radio Frequency Interference Suppression Network for Spaceborne SAR Images via Multi-Dimensional Feature Transform

Spaceborne synthetic aperture radar (SAR) is a promising remote sensing technique, as it can produce high-resolution imagery over a wide area of surveillance with all-weather and all-day capabilities. However, the spaceborne SAR sensor may suffer from severe radio frequency interference (RFI) from some similar frequency band signals, resulting in image quality degradation, blind spot, and target loss. To remove these RFI features presented on spaceborne SAR images, we propose a multi-dimensional calibration and suppression network (MCSNet) to exploit the features learning of spaceborne SAR images and RFI. In the scheme, a joint model consisting of the spaceborne SAR image and RFI is established based on the relationship between SAR echo and the scattering matrix. Then, to suppress the RFI presented in images, the main structure of MCSNet is constructed by a multi-dimensional and multi-channel strategy, wherein the feature calibration module (FCM) is designed for global depth feature extraction. In addition, MCSNet performs planned mapping on the feature maps repeatedly under the supervision of the SAR interference image, compensating for the discrepancies caused during the RFI suppression. Finally, a detailed restoration module based on the residual network is conceived to maintain the scattering characteristics of the underlying scene in interfered SAR images. The simulation data and Sentinel-1 data experiments, including different landscapes and different forms of RFI, validate the effectiveness of the proposed method. Both the results demonstrate that MCSNet outperforms the state-of-the-art methods and can greatly suppress the RFI in spaceborne SAR.

Ship Detection in Spaceborne SAR Images under Radio Interference Environment Based on CFAR

Spaceborne synthetic aperture radar (SAR) can be easily interfered with by narrowband radio frequency interference (RFI) from ground radiation sources, causing significant degradation of image quality. In the application of SAR ship detection, the radio interference will raise the detection threshold of a constant false alarm rate (CFAR) detector, and consequently results in the degradation of detection performance. In order to solve this problem, we propose a ship-detection method for SAR under a narrowband RFI environment. The proposed method is mainly divided into five steps: (1) transform the input SAR image with narrowband RFI into 2-D frequency domain by fast Fourier transform (FFT); (2) use CFAR detector to detect RFI in 2-D frequency domain; (3) suppress RFI data points using adaptively weighting in the 2-D frequency domain; (4) transform the RFI suppressed 2-D spectrum into the image domain via inverse FFT; (5) apply CFAR detector for ship detection. Simulation and real data experiments show that the proposed method can effectively detect ships from SAR images with ocean background even if there exists serious RFI.

A Lightweight Self-Supervised Representation Learning Algorithm for Scene Classification in Spaceborne SAR and Optical Images

Despite the increasing amount of spaceborne synthetic aperture radar (SAR) images and optical images, only a few annotated data can be used directly for scene classification tasks based on convolution neural networks (CNNs). For this situation, self-supervised learning methods can improve scene classification accuracy through learning representations from extensive unlabeled data. However, existing self-supervised scene classification algorithms are hard to deploy on satellites, due to the high computation consumption. To address this challenge, we propose a simple, yet effective, self-supervised representation learning (Lite-SRL) algorithm for the scene classification task. First, we design a lightweight contrastive learning structure for Lite-SRL, we apply a stochastic augmentation strategy to obtain augmented views from unlabeled spaceborne images, and Lite-SRL maximizes the similarity of augmented views to learn valuable representations. Then, we adopt the stop-gradient operation to make Lite-SRL’s training process not rely on large queues or negative samples, which can reduce the computation consumption. Furthermore, in order to deploy Lite-SRL on low-power on-board computing platforms, we propose a distributed hybrid parallelism (DHP) framework and a computation workload balancing (CWB) module for Lite-SRL. Experiments on representative datasets including OpenSARUrban, WHU-SAR6, NWPU-Resisc45, and AID dataset demonstrate that Lite-SRL can improve the scene classification accuracy under limited annotated data, and it is generalizable to both SAR and optical images. Meanwhile, compared with six state-of-the-art self-supervised algorithms, Lite-SRL has clear advantages in overall accuracy, number of parameters, memory consumption, and training latency. Eventually, to evaluate the proposed work’s on-board operational capability, we transplant Lite-SRL to the low-power computing platform NVIDIA Jetson TX2.

An Autofocus Approach With Applications to Ionospheric Scintillation Compensation for Spaceborne SAR Images

Spaceborne synthetic aperture radar (SAR) systems, operating at L-band or lower, are very susceptible to ionospheric scintillation. The scintillation phase error (SPE) can bring about serious azimuth decorrelation and resolution loss. Compared with the motion phase error, the SPE takes on a much stronger spatial-variation both in along-track and across-track orientations, and its anisotropic feature makes the compensation more intractable. In this article, the phase gradient autofocus (PGA) is used for the first time to compensate the spatial-varying and anisotropic SPE for spaceborne SAR images. It begins with achieving a reliable SPE estimate by applying PGA to a strong scatterer. According to the preknowledge of the phase screen altitude and the anisotropic elongation heading, the emphasis is then on estimating the SPEs for other pixels from the well-estimated SPE, based on the mutual correlation and overlapping of SPEs. The pixel-by-pixel strategy is adopted for the final compensation. The proposed methodology is very appropriate for SAR images with few corner reflectors, which is validated on a simulated L-band stripmap data and a PALSAR-2 spotlight real data. It shows more powerful utility than the classical PGA. The performance analysis is implemented with regard to two necessary factors, which further confirms the effectiveness of the proposed methodology.

Multi-Scale Ship Detection Algorithm Based on a Lightweight Neural Network for Spaceborne SAR Images

The current limited spaceborne hardware resources and the diversity of ship target scales in SAR images have led to the requirement of on-orbit real-time detection of ship targets in spaceborne synthetic aperture radar (SAR) images. In this paper, we propose a lightweight ship detection network based on the YOLOv4-LITE model. In order to facilitate the network migration to the satellite, the method uses MobileNetv2 as the backbone feature extraction network of the model. To solve the problem of ship target scale diversity in SAR images, an improved receptive field block (RFB) structure is introduced, enhancing the feature extraction ability of the network, and improving the accuracy of multi-scale ship target detection. A sliding window block method is designed to detect the whole SAR image, which can solve the problem of image input. Experiments on the SAR ship dataset SSDD show that the detection speed of the improved lightweight network could reach up to 47.16 FPS, with the mean average precision (mAP) of 95.03%, and the model size is only 49.34 M, which demonstrates that the proposed network can accurately and quickly detect ship targets. The proposed network model can provide a reference for constructing a spaceborne real-time lightweight ship detection network, which can balance the detection accuracy and speed of the network.

A Novel Imaging Algorithm for High-Resolution Wide-Swath Space-Borne SAR Based on a Spatial-Variant Equivalent Squint Range Model

High-Resolution Wide-Swath (HRWS) is an important development direction of space-borne Synthetic Aperture Radar (SAR). The two-dimensional spatial variation of the Doppler parameters is the most significant characteristic of the sliding spotlight space-borne SAR system under the requirements of HRWS. Therefore, the compensation of the two-dimensional spatial variation is the most challenging problem faced in the imaging of HRWS situations. The compensatory approach is then proposed to address this problem in this paper. The spatial distribution of the Doppler parameters for the HRWS space-borne SAR data in the sliding spotlight working mode is firstly analyzed, based on which a Spatial-Variant Equivalent Slant Range Model (SV-ESRM) is put forward to accurately formulate the range history for the distributed target. By introducing an azimuth-varying term, the SV-ESRM can precisely describe the range history for not only central targets but also marginal targets, which is more adaptive to the HRWS space-borne SAR requirements. Based on the SV-ESRM, a Modified Hybrid Correlation Algorithm (MHCA) for HRWS space-borne SAR imaging is derived to focus the full-scene data on one single imaging processing. A Doppler phase perturbation incorporated with the sub-aperture method is firstly performed to eliminate the azimuth variation of the Doppler parameters and remove the Doppler spectrum aliasing. Then, an advanced hybrid correlation is employed to achieve the precise differential Range Cell Migration (RCM) correction and Doppler phase compensation. A range phase perturbation method is also utilized to eliminate the range profile defocusing caused by range-azimuth coupling for marginal targets. Finally, a de-rotation processing is performed to remove the azimuth aliasing and the residual azimuth-variance and obtain the precisely focused SAR image. Simulation shows that the SAR echoes for a 20 km × 20 km scene with a 0.25 m resolution in both the range and azimuth directions could be focused precisely via one single imaging processing, which validates the feasibility of the proposed algorithm.

An FPGA-Based Four-Channel 128k-Point FFT Processor Suitable for Spaceborne SAR

Spaceborne synthetic aperture radar (SAR) plays an important role in many fields of national defense and the national economy, and the Fast Fourier Transform (FFT) processor is an important part of the spaceborne real-time SAR imaging system. How to meet the increasing demand for ultra-large-scale data processing and to reduce the scale of the hardware platform while ensuring real-time processing is a major problem for real-time processing of on-orbit SAR. To solve this problem, in this study, we propose a 128k-point fixed-point FFT processor based on Field-Programmable Gate Array (FPGA) with a four-channel Single-path Delay Feedback (SDF) structure. First, we combine the radix-23 and mixed-radix algorithms to propose a four-channel processor structure, to achieve high efficiency hardware resources and high real-time performance. Secondly, we adopt the SDF structure combined with the radix-23 algorithm to achieve efficient use of storage resources. Third, we propose a word length adjustment strategy to ensure the accuracy of calculations. The experimental results show that the relative error between the processor and the MATLAB calculation result is maintained at about 10−4, which has good calculation accuracy.

A Robust Stereo Positioning Solution for Multiview Spaceborne SAR Images Based on the Range–Doppler Model

In recent years, the stereo positioning technology based on multiview spaceborne synthetic aperture radar (SAR) images has been widely applied in digital surface model extraction. In this letter, problems of the existing methods based on the range–Doppler (RD) model in a multiview stereo solution are pointed out. A robust stereo positioning solution for multiview spaceborne SAR images based on the RD model is proposed. In the proposed method, the traditional RD model is normalized to reduce the model errors caused by the different scales of the range equation and Doppler equation. A weighting strategy is also proposed to improve the positioning accuracy. This strategy is useful for multiview stereo positioning when using images of different satellites with orbital data of different accuracies. The experiments based on GaoFen-3 and TerraSAR-X satellite data sets validate the effectiveness of the proposed method.

Feasibility of Replacing the Range Doppler Equation of Spaceborne Synthetic Aperture Radar Considering Atmospheric Propagation Delay with a Rational Polynomial Coefficient Model.

Usually, the rational polynomial coefficient (RPC) model of spaceborne synthetic aperture radar (SAR) is fitted by the original range Doppler (RD) model. However, the radar signal is affected by two-way atmospheric delay, which causes measurement error in the slant range term of the RD model. In this paper, two atmospheric delay correction methods are proposed for use in terrain-independent RPC fitting: single-scene SAR imaging with a unique atmospheric delay correction parameter (plan 1) and single-scene SAR imaging with spatially varying atmospheric delay correction parameters (plan 2). The feasibility of the two methods was verified by conducting fitting experiments and geometric positioning accuracy verification of the RPC model. The experiments for the GF-3 satellite were performed by using global meteorological data, a global digital elevation model, and ground control data from several regions in China. The experimental results show that it is feasible to use plan 1 or plan 2 to correct the atmospheric delay error, no matter whether in plain, mountainous, or plateau areas. Moreover, the geometric positioning accuracy of the RPC model after correcting the atmospheric delay was improved to better than 3 m. This is of great significance for the efficient and high-precision geometric processing of spaceborne SAR images.

A Fast, Three-Dimensional, Indirect Geolocation Method Using IAGM and DSM Data without GCPs for Spaceborne SAR Images.

To determine the geolocation of a pixel for spaceborne synthetic aperture radar (SAR) images, traditional indirect geolocation methods can cause great computational complexity. In this paper, a fast, three-dimensional, indirect geolocation method without ground control points (GCPs) is presented. First, the Range-Doppler (RD) geolocation model with all the equations in the Earth-centered rotating (ECR) coordinate system is introduced. By using an iterative analytical geolocation method (IAGM), the corner point locations of a quadrangle SAR image on the Earth’s surface are obtained. Then, a three-dimensional (3D) grid can be built by utilizing the digital surface model (DSM) data in this quadrangle. Through the proportional relationship for every pixel in the 3D grid, the azimuth time can be estimated, which is the key to decreasing the calculation time of the Doppler centroid. The results show that the proposed method is about 12 times faster than the traditional method, and that it maintains geolocation accuracy. After acquiring the precise azimuth time, it is easy to obtain the range location. Therefore, the spaceborne SAR image can be geolocated to the Earth surface precisely based on the high-resolution DSM data.

Maritime targets classification based on CNN using Gaofen‐3 SAR images

The classification and detection of maritime targets are widely used in shipping navigation and military fields. With the development of spaceborne synthetic aperture radar (SAR) technology, more and more very high-resolution SAR images can be acquired for maritime targets recognition. However, due to the different imaging mechanisms between SAR images and optical images, it is difficult and laborious to interpret SAR images manually. This study uses a modified Alexnet structure to realise maritime targets classification on the Gaofen-3 spaceborne SAR images. The maritime targets dataset (MTD), including boats, cargo ships, container ships, windmills, oil tankers, and iron towers, is conducted. Moreover, the proposed convolution neural networks (CNNs) structure is trained and tested on the MTD. Experimental results show that the model can get an accuracy of 92.10% in classifying the six kinds of targets, and the performance is superior compared with other CNNs and traditional supportive vector machine algorithms.

Moving ships refocusing for spaceborne SAR based on Doppler parameters estimation

Moving ships imaging is an important issue in marine remote-sensing by spaceborne synthetic aperture radar (SAR). As the moving ships defocus generally in high-resolution spaceborne SAR images, the refocusing step is demanded for the following processing in classification and identification. A new refocusing method based on Doppler parameters search is proposed to enhance the performance of ship images. This method is applied directly on the single-look complex image data. Furthermore, the space-variant characteristic of Doppler parameters is taken into account within this method. Finally, the GF-3 satellite SAR data refocusing results of moving ships verify the effectiveness of the proposed method.

Analytical Approximation Model for Quadratic Phase Error Introduced by Orbit Determination Errors in Real-Time Spaceborne SAR Imaging

Research on real-time spaceborne synthetic aperture radar (SAR) imaging has emerged as satellite computation capability has increased and applications of SAR imaging products have expanded. The orbit determination data of a spaceborne SAR platform are essential for the SAR imaging procedure. In real-time SAR imaging, onboard orbit determination data cannot achieve a level of accuracy that is equivalent to the orbit ephemeris in ground-based SAR processing, which requires a long processing time using common ground-based SAR imaging procedures. It is important to study the influence of errors in onboard real-time orbit determination data on SAR image quality. Instead of the widely used numerical simulation method, an analytical approximation model of the quadratic phase error (QPE) introduced by orbit determination errors is proposed. The proposed model can provide approximation results at two granularities: approximations with a satellite’s true anomaly as the independent variable and approximations for all positions in the satellite’s entire orbit. The proposed analytical approximation model reduces simulation complexity, extent of calculations, and the processing time. In addition, the model reveals the core of the process by which errors are transferred to QPE calculations. A detailed comparison between the proposed method and a numerical simulation method proves the correctness and reliability of the analytical approximation model. With the help of this analytical approximation model, the technical parameter iteration procedure during the early-stage development of an onboard real-time SAR imaging mission will likely be accelerated.

Implementation of CS coefficient calculation based on dual‐operator engines in multimode spaceborne SAR imaging systems

To provide an optimised implementation aimed at calculating the chirp scaling (CS) coefficients used in state-of-the-art spaceborne synthetic aperture radar (SAR) imaging systems. Built on the core concept of breaking down the CS coefficient calculation into basic operations, we propose a new architecture that adopts a dual-operator engine as the basic processing unit and seeks to optimise the switching network of operator engines through an appropriately interconnected grouping of various calculations. A wide variety of SAR imaging architectures based on fast Fourier transformation-CS operations may benefit from this work. The proposed architecture is implemented in a Xilinx Virtex-7 FPGA process; a comparison between test results and results obtained from an off-the-shelf counterpart confirms the efficacy of the proposed architecture.

ARCHAEOLOGICAL SURVEYS ON THE GERMAN NORTH SEA COAST USING HIGH-RESOLUTION SYNTHETIC APERTURE RADAR DATA

Abstract. We show that high-resolution space-borne Synthetic Aperture Radar (SAR) imagery with pixel sizes well below 1 m2 can be used to complement archaeological surveys in areas that are difficult to access. After major storm surges in the 14th and 17th centuries, vast areas on the German North Sea coast were lost to the sea. Areas of former settlements and historical land use were buried under sediments for centuries, but when the surface layer is driven away under the permanent action of wind, currents, and waves, they appear again on the Wadden Sea surface. However, the frequent flooding and erosion of the intertidal flats make any archaeological monitoring a difficult task, so that remote sensing techniques appear to be an efficient and cost-effective instrument for any archaeological surveillance of that area. Space-borne SAR images clearly show remnants of farmhouse foundations and of former systems of ditches, dating back to the 14th and to the 16th/17th centuries. In particular, the very high-resolution acquisition (staring spotlight) mode of the German TerraSAR/ TanDEM-X satellites allows for the detection of various kinds of residuals of historical land use with high precision. In addition, we also investigate the capability of SARs working at lower microwave frequencies (on Radarsat-2) to complement our archaeological survey of historical cultural traces, some of which have been unknown so far.

SAR Imaging of Archaeological Sites on Intertidal Flats in the German Wadden Sea

We show that high-resolution space-borne synthetic aperture radar (SAR) imagery with pixel sizes smaller than 1 m2 can be used to complement archaeological surveys on intertidal flats. After major storm surges in the 14th and 17th centuries (“Grote Mandrenke”), vast areas on the German North Sea coast were lost to the sea. Areas of settlements and historical farmland were buried under sediments for centuries, but when the surface layer is driven away under the action of wind, currents, and waves, they appear again on the Wadden Sea surface. However, frequent flooding and erosion of the intertidal flats make any archaeological monitoring a difficult task, so that remote sensing techniques appear to be an efficient and cost-effective instrument for any archaeological surveillance of that area. Space-borne SAR images clearly show remains of farmhouse foundations and of former systems of ditches, dating back to the times before the “Grote Mandrenke”. In particular, the very high-resolution acquisition (“staring spotlight”) mode of the TerraSAR/TanDEM-X satellites allows detecting various kinds of remains of historical land use at high precision. Moreover, SARs working at lower microwave frequencies (e.g., that on Radarsat-2) may complement archaeological surveys of historical cultural traces, some of which have been unknown so far.

Archeological crop marks identified from Cosmo-SkyMed time series: the case of Han-Wei capital city, Luoyang, China

ABSTRACTThe development of spaceborne Synthetic Aperture Radar (SAR) technology declares that the golden era of SAR remote sensing in archeology is approaching; however, nowadays its methodology framework is still lacking due to the inadequate case studies validated by ground-truths. In this study, we investigated the crop marks using multi-temporal Cosmo-SkyMed data acquired in 2013 by applying a two-step decision-tree classifier in conjunction with a spatial analysis in an area of archeological interest nearby the archeological site of Han-Wei capital city (1900–1500 BP), in Luoyang, China. The time-series backscattering anomalies related to the wheat growth cycle were identified and then further validated in two zones by geophysical investigations (Ground Penetration Radar and electrical measurements) and in a third zone by archeological excavations made after the SAR data acquisition. This study provides a new approach for the relic detection, shallowly buried and covered by the crop vegetation, by temporal crop marks on spaceborne SAR images. We also emphasize the necessity to establish a satellite-to-ground methodology framework for the promotion of remote-sensing technology in archeology.

Micro-Doppler Reconstruction in Spaceborne SAR Images Using Azimuth Time–Frequency Tracking of the Phase History

This letter proposes a micro-Doppler (m-D) reconstruction method for spaceborne synthetic aperture radar (SAR) images using azimuth time–frequency tracking of the phase history. The algorithm involves an azimuth defocusing of the SAR image in order to gain access to the phase history, followed by a time–frequency tracking algorithm. The tracking in azimuth is based on local polynomial phase modeling using as estimator for the polynomial coefficients the high-order ambiguity function. The approach is presented in the context of vibration estimation for infrastructure monitoring applications, with an emphasis on the estimation of vibration parameters from the reconstructed m-D. The procedure is tested and compared with state-of-the-art methods by various simulation scenarios in keeping with typical high-resolution SAR imaging parameters. Finally, the developed algorithm is applied on real data acquired by the TerraSAR-X satellite over the Puylaurent water dam in France.

An Imaging Compensation Algorithm for Spaceborne High-Resolution SAR Based on a Continuous Tangent Motion Model

This paper develops a continuous tangent motion model by approximating the relative trajectories between spaceborne Synthetic Aperture Radar (SAR) and its targets during every transmitting period and every receiving period as tangential segments. Compared with existing motion models, including the stop-go model and the continuous rectilinear model, the continuous tangent model is much closer to the actual relative motion. Based on the new motion model, an imaging compensation algorithm is proposed that considers the space-variant property of SAR echoes more fully by introducing three space-variant factors: the time-scaling factor, the transmitting–receiving rate, and the transmitting–receiving constant. As a result, spaceborne SAR imaging with 0.21-meter resolution and wide-swath, up to 15 km × 15 km, is achieved. Simulation results indicate that the novel algorithm provides a superior and more consistent focusing quality across the whole swath compared with existing algorithms based on the stop-go or continuous rectilinear models.