High-resolution Spaceborne Synthetic Aperture Radar Research Articles

Accurate Range Modeling for High-Resolution Spaceborne Synthetic Aperture Radar.

Spaceborne synthetic aperture radar (SAR) is an advanced microwave imaging technology that provides all-weather and all-day target information. However, as spaceborne SAR resolution improves, traditional echo signal models based on airborne SAR design become inadequate due to the curved orbit, Earth rotation, and increased propagation distance. In this study, we propose an accurate range model for high-resolution spaceborne SAR by analyzing motion trajectory and Doppler parameters from the perspective of the space geometry of spaceborne SAR. We evaluate the accuracy of existing range models and propose an advanced equivalent squint range model (AESRM) that accurately fits the actual range history and compensates for high-order term errors by introducing third-order and fourth-order error terms while maintaining the simplicity of the traditional model. The proposed AESRM's concise two-dimensional frequency spectrum form facilitates the design of imaging algorithms. Point target simulations confirm the effectiveness of the proposed AESRM, demonstrating significant improvements in fitting accuracy for range histories characterized by nonlinear trajectories. The developed AESRM provides a robust foundation for designing imaging algorithms and enables higher resolution and more accurate radar imaging.

Analysis and compensation of stop-and-go approximation in high-resolution spaceborne synthetic aperture radar

ABSTRACT With the advancement of spaceborne synthetic aperture radar (SAR) resolution, the conventional stop-and-go approximation-based motion model is no longer suitable for high-resolution imaging algorithms. This paper conducts a comprehensive analysis of the approximation errors resulting from the stop-and-go approximation and proposes corresponding compensation methods. Firstly, an accurate echo model based on continuous platform motion is derived from the SAR geometry configuration. The impact of these errors on range and azimuth imaging is analysed from a spectral perspective, and the applicable boundary conditions are examined. Subsequently, compensation methods are proposed to eliminate the introduced approximation errors, addressing both”fast time” and”slow time” effects, thus enabling high-resolution imaging through improvements in traditional imaging algorithms. Experimental simulations validate the effectiveness of the error analysis and compensation methods, using X-band low Earth orbit SAR as an illustrative example. The proposed methods are not only compatible with existing mature imaging algorithms, but the analytical approach and compensation methods are also applicable to SAR systems operating on different carrier frequencies, orbits, and platforms.

Generation of internal solitary waves by the Mackenzie River plume in the coastal Arctic Ocean

High-resolution spaceborne synthetic aperture radar (SAR) images have verified the wide existence of internal solitary waves (ISWs) over the Chukchi and Beaufort Seas. A major ISW generation hotspot has been observed at the mouth of the Mackenzie River. Considering the weak tidal currents and relatively flat topography of the Mackenzie Shelf, such ISWs are unlikely to be generated by tide–topography interactions. However, this is more likely caused by the intrusion of river plumes. Therefore, the generation of ISWs by the Mackenzie River plume is investigated numerically. A series of numerical simulations are conducted to explore the influence of stratification, river plume strength, and Earth's rotation on the generation and evolution of ISWs. The results indicate that the Mackenzie River plume is an essential ISW source for the coastal Arctic Ocean. The amplitude of the ISWs is affected by the intrusion strength of the Mackenzie River plume. In addition to the direct observational evidence from summer, the numerical results show that the environmental conditions in winter are suitable for the generation of ISWs. Rotation affects the amplitude of the generated ISWs and the number of ISWs in an ISW packet by modulating the plume intrusion strength and dispersing the ISWs. This study highlights the crucial role of the river plume mechanism in exciting ISWs and emphasizes the importance of ISWs for vertical mixing in the Arctic Ocean.

Reexamining the Estimation of Tropical Cyclone Radius of Maximum Wind from Outer Size with an Extensive Synthetic Aperture Radar Dataset

Abstract The radius of maximum wind Rmax, an important parameter in tropical cyclone (TC) ocean surface wind structure, is currently resolved by only a few sensors so that, in most cases, it is estimated subjectively or via crude statistical models. Recently, a semiempirical model relying on an outer wind radius, intensity, and latitude was fit to best-track data. In this study we revise this semiempirical model and discuss its physical basis. While intensity and latitude are taken from best-track data, Rmax observations from high-resolution (3 km) spaceborne synthetic aperture radar (SAR) and wind radii from an intercalibrated dataset of medium-resolution radiometers and scatterometers are considered to revise the model coefficients. The new version of the model is then applied to the period 2010–20 and yields Rmax reanalyses and trends that are more accurate than best-track data. SAR measurements corroborate that fundamental conservation principles constrain the radial wind structure on average, endorsing the physical basis of the model. Observations highlight that departures from the average conservation situation are mainly explained by wind profile shape variations, confirming the model’s physical basis, which further shows that radial inflow, boundary layer depth, and drag coefficient also play roles. Physical understanding will benefit from improved observations of the near-core region from accumulated SAR observations and future missions. In the meantime, the revised model offers an efficient tool to provide guidance on Rmax when a radiometer or scatterometer observation is available, for either operations or reanalysis purposes.

Segmented continuously varying pulse interval sequence design for extremely high-resolution spaceborne sliding spotlight SAR

ABSTRACT Synthetic aperture radar (SAR) is an active microwave remote sensing device used to obtain high-resolution SAR images.With the development of SAR, extremely high-resolution SAR (i.e. resolution reaching 0.1 m) plays an increasingly important role in applications such as target recognition. In extremely high-resolution spaceborne SAR, the variation of slant range history becomes extremely severe, resulting in echoes of interest overlapping with transmitted pulses and nadir echoes when transmitting the pulses at constant pulse intervals (PIs), further causing the loss of echo data. Although a continuously varying pulse interval (CVPI) system can expand the tolerance of slant range variation to some extent, overlap still occurs when the variation in slant range exceeds a certain threshold. Thus, this paper proposes segmented CVPI sequence design methods to solve the data acquisition problem in the situation of severe variation in slant range history. The timing diagram- and strip layering diagram-based segmented CVPI sequence design methods, which are suitable for the acquisition of spaceborne SAR data with any variation of slant range, are given. The characteristics of the two methods are analysed. Finally, several computer simulations indicate that the echoes generated by the proposed methods are not overlapped, which verifies the validity of the proposed methods.

A High-Resolution, Wide-Swath SAR Imaging System Based on Tandem SAR Satellites.

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 swath by the scanning mode, and the other obtains the undersampled echo from the same swath. The high resolution is achieved by associating the tandem SARs’ echo and using the minimum-energy-based algorithm. Finally, a high-resolution wide-swath SAR system is designed, and its imaging performance is verified by simulated data and real airborne SAR data.

Real-Time Imaging Processing of Squint Spaceborne SAR with High-Resolution Based on Nonuniform PRI Design

The real-time imaging research of squint spaceborne synthetic aperture radar (SAR) with high resolution has significant value in both military and civil fields, which makes it a hot issue in SAR research. It is necessary to solve the contradictory problems of nonlinear trajectory and efficient imaging at the same time in order to achieve the two goals, high-resolution and real-time imaging. A large number of complex operations are required in the accurate correction algorithms for nonlinear trajectory, which will reduce the imaging efficiency, and this problem becomes more prominent with the improvement of resolution. To solve the above problems, this paper proposes a new real-time imaging processing of squint high-resolution SAR, which eliminates the velocity–azimuth variation caused by nonlinear trajectory in the data acquisition stage through nonuniform pulse repetition interval (PRI) design. The imaging efficiency has been greatly improved because the new method avoids the complex azimuth resampling operation. Simulation experiments verify the effectiveness of the method.

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 Efficient Full-Aperture Approach for Airborne Spotlight SAR Data Processing Based on Time-Domain Dealiasing

The two-step approach (TSA) is an efficient full-aperture method to solve the Doppler spectrum aliasing when processing data acquired by a synthetic aperture radar (SAR) system operating in beam steering mode. This simple approach solves the spectral aliasing by implementing an azimuth convolution between the raw data and a chirp signal, thus avoiding complex subaperture division and recombination of subaperture approaches. However, as aliasing reoccurs in the slow time-domain after the convolution, the estimation and compensation for residual motion error by autofocus cannot be performed immediately, which is crucial for airborne and high-resolution spaceborne SAR processing. The extended TSA solves this problem by implementing full-aperture azimuth scaling, but it is inefficient when the scaling factor deviates from unity severely, which is common in the data acquisition geometry of an airborne SAR. Aiming at addressing the existing shortcomings, this article combines the TSA with autofocus by the time-domain dealiasing and provides an efficient full-aperture processing framework of airborne spotlight SAR data. Simulated and experimental airborne spotlight SAR data with the transmission signal bandwidth of 1.2 GHz and a coherent integration angle of 15<inline-formula><tex-math notation="LaTeX">$^\circ$</tex-math></inline-formula> are processed by the proposed algorithm and the clarity of the processed results shows its effectiveness.

Spaceborne High-Squint High-Resolution SAR Imaging Based on Two-Dimensional Spatial-Variant Range Cell Migration Correction

High-squint imaging is an effective means to enhance the flexibility and coverage ability of spaceborne synthetic aperture radar (SAR). Although existing imaging algorithms based on linear range cell migration correction (LRCMC) and nonlinear chirp scaling (NCS) can reduce the range-azimuth coupling of the spectrum and the spatial-variant of the Doppler parameter to some extent, they become invalid as the resolution increases. On one hand, the beam rotation of sliding spotlight SAR results in nonlinear azimuth-variant of the Doppler centre, and the traditional deramping operation, which removes the linear variation, will cause spectrum aliasing. On the other hand, these algorithms assume the azimuth-variants of range cell migration (RCM) are consistent in the total swath. However, the azimuth-variants of RCM are different in different range cells, which cannot be neglected in high-resolution imaging. To solve these problems, a novel imaging algorithm based on two-dimensional spatial-variant range cell migration correction is proposed in this paper. First, LRCMC is utilized, and the nonlinear azimuth deramping operation is conducted to obtain aliasing-free spectrum. Then, the azimuth-variant of RCM is corrected by azimuth interpolation and polynomial compensation. Noting that the interpolation coefficient varies linearly with slant range, this can weaken the azimuth-variant differences of RCM in different range cells. Meanwhile, azimuth polynomial compensation can correct the consistent azimuth-variant of RCM, and hence the azimuth-variant of RCM can be totally corrected. Finally, the compression is performed via the range chirp scaling and azimuth NCS. The effectiveness of the proposed algorithm is verified by computer simulations.

Onboard Digital Beamformer with Multi-Frequency and Multi-Group Time Delays for High-Resolution Wide-Swath SAR

Scan-on-receive (SCORE) digital beamforming (DBF) in elevation can significantly improve the signal-to-noise ratio (SNR) and suppress range ambiguities in spaceborne synthetic aperture radar (SAR). It has been identified as one of the important methods to obtain high-resolution wide-swath (HRWS) SAR images. However, with the improvement of geometric resolution and swath width, the residual pulse extension loss (PEL) due to the long pulse duration in the conventional spaceborne onboard DBF processor must be considered and reduced. In this paper, according to the imaging geometry of the spaceborne DBF SAR system, the reason for the large attenuation of the receiving gain at the edge of the wide swath is analyzed, and two improved onboard DBF methods to mitigate the receive gain loss are given and analyzed. Taking account of both the advantages and drawbacks of the two improved DBF methods presented, a novel onboard DBF processor with multi-frequency and multi-group time delays in HRWS SAR is proposed. Compared with the DBF processor only with multi-group time delays, the downlink data rate was clearly reduced, while focusing performance degradation due to phase and amplitude errors between different frequency bands could be mitigated compared with the DBF processor only with multi-frequency time delays. The simulation results of both point and distributed targets validate the proposed DBF processor.

Spatial Shift Phenomenon Compensation for TomoSAR Imaging Using High-Resolution TerraSAR-X Data

Massive high-resolution spaceborne synthetic aperture radar (SAR) data are available nowadays, effecting rapid development in the urban remote sensing technology. In this study, we use a set of 27 scenes from TerraSAR-X to reconstruct the three-dimensional (3D) point clouds of a skyscraper-North Star Times Tower in Beijing, China. We study in detail the derivation process of a 3D model of tomographic SAR (TomoSAR) from the two-dimensional (2D) imaging mathematical model of SAR. We observe the presence of a spatial shift in the elevation direction of TomoSAR, which yields poor and even incorrect results when greedy algorithms such as orthogonal matching pursuit (OMP) or regularized orthogonal matching pursuit (ROMP) algorithms are applied. Then, we propose a phase compensation method to eliminate the spatial shift. Both OMP and ROMP algorithms are used for TomoSAR imaging on high-resolution TerraSAR-X data. The experimental results with North Star Times Tower demonstrate the accuracy of the theoretical analysis and the effectiveness of the algorithms. Finally, we compare the ROMP and OMP algorithms and conclude that both algorithms can yield similar reconstruction results in TomoSAR imaging. The ROMP algorithm does not depend on sparsity and can suppress noise through regularization selection at the cost of time. The OMP algorithm introduces noise when the sparsity is inaccurate.

Study on Precise Satellite Attitude Maneuvering Strategy for Ultrahigh Resolution Spaceborne SAR Imaging

For future ultrahigh resolution spaceborne synthetic aperture radar (SAR), it requires the antenna beam capable of large angle scanning in azimuth to increase the azimuth bandwidth and to improve the resolution consequently. To achieve this goal, this paper proposes for the first time a complete implementation scheme based on three-axis attitude maneuvering of satellite platform. Starting from the determination of rotation center, we will deduce the variation of Euler angles during the whole imaging period. Compared with two-dimensional electronical beam-sweeping approach used in phased-array antenna, the most notable advantage of our approach is that it can guarantee azimuth Doppler frequency barely vary along the range line at any azimuth squint angle, which enables the effective decoupling of the signal in azimuth from that in range. Taking advantage of this characteristic, the processing efficiency of high resolution SAR imaging could then be improved to a great extent. Simulation results are presented to verify its effectiveness as well as superiority compared to electronical beam-sweeping.

Slow Pulse Repetition Interval Variation for High-Resolution Wide-Swath SAR Imaging

In the context of spaceborne synthetic aperture radar (SAR) imaging, high resolution and wide swath are inherently conflicting requirements. These may, however, be simultaneously satisfied by advanced imaging modes with multichannel architectures in elevation and/or azimuth. This article elaborates on a new mode based on multiple elevation beams and a simple pulse repetition interval (PRI) variation scheme which allows high-resolution wide-swath imaging. It is shown to use the illumination time more efficiently than ScanSAR and yet to be simpler than staggered SAR. Good SAR imaging performance is achieved with a rather compact antenna design. The proposed imaging mode is suitable for spaceborne SAR systems with planar and reflector antennas. In order to improve the imaging performance, a reflector antenna architecture with a multichannel feed in both elevation and azimuth is considered.

Advanced high-order nonlinear chirp scaling algorithm for high-resolution wide-swath spaceborne SAR

Spaceborne Synthetic Aperture Radar (SAR) is a well-established and powerful imaging technology that can provide high-resolution images of the Earth’s surface on a global scale. For future SAR systems, one of the key capabilities is to acquire images with both high-resolution and wide-swath. In parallel to the evolution of SAR sensors, more precise range models, and effective imaging algorithms are required. Due to the significant azimuth-variance of the echo signal in High-Resolution Wide-Swath (HRWS) SAR, two challenges have been faced in conventional imaging algorithms. The first challenge is constructing a precise range model of the whole scene and the second one is to develop an effective imaging algorithm since existing ones fail to process high-resolution and wide azimuth swath SAR data effectively. In this paper, an Advanced High-order Nonlinear Chirp Scaling (A-HNLCS) algorithm for HRWS SAR is proposed. First, a novel Second-Order Equivalent Squint Range Model (SOESRM) is developed to describe the range history of the whole scene, by introducing a quadratic curve to fit the deviation of the azimuth FM rate. Second, a corresponding algorithm is derived, where the azimuth-variance of the echo signal is solved by azimuth equalizing processing and accurate focusing is achieved through a high-order nonlinear chirp scaling algorithm. As a result, the whole scene can be accurately focused through one single imaging processing. Simulations are provided to validate the proposed range model and imaging algorithm.

Automatic Urban Area Extraction From SAR Image Based on Morphological Operator

With the development of high-resolution spaceborne synthetic aperture radar (SAR) systems, it has been possible to use SAR data for identifying man-made structures in urban areas. In this letter, a new approach to extract urban areas in the SAR image is presented by using the morphological characteristics of the radar scattering mechanism. In order to detect the shape and location of a building, the radar shadow index and the double-bounce index are proposed. In addition, an automatic urban area extraction method is proposed using the fuzzy-based fusion of the morphological indices. The detection performance is evaluated by two ${X}$ -band SAR data acquired from different systems. Despite the differences in observation and environmental conditions in the two data, the proposed method can provide consistent detection performance with the overall accuracy of about 88% and the Kappa coefficient of about 68%.

FUSAR-Ship: building a high-resolution SAR-AIS matchup dataset of Gaofen-3 for ship detection and recognition

Gaofen-3 (GF-3) is Chinas first civil C-band fully polarimetric spaceborne synthetic aperture radar (SAR) primarily missioned for ocean remote sensing and marine monitoring. This paper proposes an automatic sea segmentation, ship detection, and SAR-AIS matchup procedure and an extensible marine target taxonomy of 15 primary ship categories, 98 sub-categories, and many non-ship targets. The FUSAR-Ship high-resolution GF-3 SAR dataset is constructed by running the procedure on a total of 126 GF-3 scenes covering a large variety of sea, land, coast, river and island scenarios. It includes more than 5000 ship chips with AIS messages as well as samples of strong scatterer, bridge, coastal land, islands, sea and land clutter. FUSAR-Ship is intended as an open benchmark dataset for ship and marine target detection and recognition. A preliminary 8-type ship classification experiment based on convolutional neural networks demonstrated that an average of 79% test accuracy can be achieved.

Extended D-TomoSAR Displacement Monitoring for Nanjing (China) City Built Structure Using High-Resolution TerraSAR/TanDEM-X and Cosmo SkyMed SAR Data

The availability of high-resolution spaceborne synthetic aperture radar (SAR) data coupled with the ongoing refinement of tomographic SAR (TomoSAR) technology has made use of radar data feasible for preventive monitoring and assessment of built structures. In this study, we first applied extended differential TomoSAR (D-TomoSAR) to a set of 26 scenes of TerraSAR/TanDEM-X (TSX/TDX) (2013–2015) and 32 scenes of Cosmo-SkyMed (CSK) (2015–2017) images to estimate motions of skyscrapers, bridges and historical monuments in Nanjing City, China. The calculation and isolation of unknown parameters in the D-TomoSAR model, including linear velocity, thermal dynamics and structural heights, helped to estimate millimetric statistics of motion time series. Then, aforementioned two SAR datasets were tentatively tested using amplitude dispersion and phase stability indicators, highlighting the performance and sensitivity of X-band SAR in structural displacement monitoring. Experimental results demonstrated that motion indexes, e.g., heterogeneities of thermal amplitudes and spatiotemporal displacements, were useful to evaluate the conditions of built structures being monitored, in particular when their structural topology were visible owing to the enhanced density of persistent scatterer (PS) measurements. This study implies the value of high-resolution D-TomoSAR tools in the preventive monitoring and health diagnosis of built structures elsewhere over the world.

Classification of the global Sentinel-1 SAR vignettes for ocean surface process studies

Spaceborne synthetic aperture radar (SAR) can provide finely-resolved (meters-scale) images of ocean surface roughness day-or-night in nearly all weather conditions. This makes it a unique asset for many geophysical applications. Initially designed for the measurement of directional ocean wave spectra, Sentinel-1 SAR wave mode (WV) vignettes are small 20 km scenes that have been collected globally since 2014. Recent WV data exploration reveals that many important oceanic and atmospheric phenomena are also well captured, but not yet employed by the scientific community. However, expanding applications of this whole massive dataset beyond ocean waves requires a strategy to automatically identify these geophysical phenomena. In this study, we propose to apply the emerging deep learning approach in ocean SAR scenes classification. The training is performed using a hand-curated dataset that describes ten commonly-occurring atmospheric or oceanic processes. Our model evaluation relies on an independent assessment dataset and shows satisfactory and robust classification results. To further illustrate the model performance, regional patterns of rain and sea ice are qualitatively analyzed and found to be very consistent with independent remote sensing datasets. In addition, these high-resolution WV SAR data can resolve fine, sub-km scale, spatial structure of rain events and sea ice that complement other satellite measurements. Overall, such automated SAR vignettes classification may open paths for broader geophysical application of maritime Sentinel-1 acquisitions.

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.