Spaceborne Synthetic Aperture Radar Satellite Research Articles

Interferometric Calibration Model for the LuTan-1 Mission: Enhancing Digital Elevation Model Accuracy

The LuTan-1 (LT-1) mission, China’s first civilian bistatic spaceborne Synthetic Aperture Radar (SAR) mission, comprises two L-band SAR satellites. These satellites operate in bistatic InSAR strip map mode, maintaining a formation flight with an adjustable baseline to generate global digital elevation models (DEMs) with high accuracy and spatial resolution. This research introduces a dedicated interferometric calibration model for LT-1, tackling the unique challenges of the bistatic system, such as interferometric parameter coupling and the π-ambiguity problem caused by synchronization phase errors. This study validates the model using SAR images from LT-1 and Xinjiang corner reflector data, achieving interferometric phase accuracy better than 0.1 rad and baseline accuracy better than 2 mm, thereby producing high-precision DEMs with a height accuracy meeting the 5 m requirement.

Development of China’s spaceborne SAR satellite, processing strategy, and application: take Gaofen-3 series as an example

ABSTRACT After mastering the key technologies of manufacturing spaceborne Synthetic Aperture Radar (SAR), China’s SAR satellites have been successfully launched into space. As the only civil microwave satellite listed in the “National High-resolution Earth Observation System Major Project,” the Gaofen-3 (GF-3) 01 satellite is the first C-band multi-polarization SAR satellite with a resolution of 1 m. GF-3 series satellites stand out among civil SAR satellites worldwide because of their high resolution, wide swath, high geometric radiation quality, multiple imaging modes, and long operation time. Taking GF-3 series satellites as an example, this study introduces the development of China’s civil SAR satellites, as well as their processing strategies and applications. The success of the GF-3 series satellites shows that China’s SAR remote sensing technology has stepped into a new era of high-quality and high-precision Earth observations.

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.

Kalman filtering for SAR satellite yaw steering

The algorithm based on Kalman filtering was proposed to calculate yaw steering angles of spaceborne Synthetic Aperture Radar (SAR) systems. We establish the process equation and the observation equation by proper design. Performance analysis and computer simulations demonstrate that Kalman filtering may take advantages in both numerical precision and computational efficiency. It therefore can be applied to SAR satellites in a wide range of microwave bands (C, X, Ku) along noncircular orbits. In addition, an efficient algorithm based on simple interpolation may be employed in practice. Since the Kalman filter is linear in nature, the fast computation makes possible the implementation of accurate onboard processing.

Monitoring the Spring Flood in Lena Delta with Hydrodynamic Modeling Based on SAR Satellite Products

Due to the remote location and the extreme climate, monitoring stations in Arctic rivers such as Lena in Siberia have been decreasing through time. Every year, after a long harsh winter, the accumulated snow on the Lena watershed melts, leading to the major annual spring flood event causing heavy transport of sediments, organic carbon, and trace metals, both into as well as within the delta. This study aims to analyze the hydrodynamic processes of the spring flood taking place every year in the Lena Delta. Thus, a combination of remote sensing techniques and hydrodynamic modeling methodologies is used to overcome limitations caused by missing ground-truth data. As a test site for this feasibility study, the outlet of the Lena River to its delta was selected. Lena Delta is an extensive wetland spanning from northeast Siberia into the Arctic Ocean. Spaceborne Synthetic Aperture Radar (SAR) data of the TerraSAR-X/TanDEM-X satellite mission served as input for the hydrodynamic modeling software HEC-RAS. The model resulted in inundation areas, flood depths, and flow velocities. The model accuracy assessed by comparing the multi-temporal modeled inundation areas with the satellite-derived inundation areas ranged between 65 and 95%, with kappa coefficients ranging between 0.78 and 0.97, showing moderate to almost perfect levels of agreement between the two inundation boundaries. Modeling results of high flow discharges show a better agreement with the satellite-derived inundation areas compared to that of lower flow discharges. Overall, the remote-sensing-based hydrodynamic modeling succeeded in indicating the increase and decrease in the inundation areas, flood depths, and flow velocities during the annual flood events.

On the Use of Multipolarization Satellite SAR Data for Coastline Extraction in Harsh Coastal Environments: The Case of Solway Firth

This study deals with coastline extraction using multipolarization spaceborne synthetic aperture radar (SAR) imagery acquired over coastal intertidal areas. The latter are very challenging environments where mud flats lead to a large variability of normalized radar cross section, which may trigger a significant number of false edges during the extraction process. The performance of SAR-based coastline extraction methods that rely on a joint combination of multipolarization information (either single- or dual-polarization metrics) and speckle filtering (either local and nonlocal approaches) are analyzed using global positioning system (GPS) samples and colocated SAR imagery collected under different incidence angles. Our test site is an intertidal zone with a wetland (i.e., salt marsh) in the Solway Firth, south-west along the Scottish-English border. Experimental results, obtained processing a pair of RadarSAT-2 full-polarimetric and a pair of Sentinel-1 dual-polarimetric SAR imagery augmented by colocated GPS samples, show that: first, the multipolarization information outperforms the single-polarization counterpart in terms of extraction accuracy; second, among the single-polarization channels, the cross-polarized one performs best; third, both single- and dual-polarization methods perform better when nonlocal speckle filtering is applied; fourth, the joint combination of nonlocal speckle filter and dual-polarization information provides the best accuracy; and finally, the incidence angle plays a role in the extraction accuracy with larger incidence angles resulting in the best performance when dual-polarization metric is used.

The feasibility of assessing swell-based bathymetry using SAR imagery from orbiting satellites

Remote sensing instruments, especially synthetic aperture radar (SAR), have become valuable tools for monitoring coastal bathymetry in both space and time. In this study, we investigate the viability of using data from spaceborne SAR satellites to detect shallow water depths from swell patterns. Using data from four Sentinel-1A SAR images, we employed numerical simulations to quantify the sensitivity of the bathymetry results to different initial input parameters such as wavelength, swell period, and initial water depth. Our sensitivity experiments indicate that the swell period is most sensitive to the water depth, while the initial water depth has the lowest impact on the shallow water depth estimation. Once we quantified the sensitivity of the estimated water depth to these parameters, we calculated the minimum and maximum detectable shallow water depth ranges of six SAR orbiting satellites (L-band: ALOS-2, C-band: GF-3, RADARSAT-2 and Sentinel-1, X-band: TerraSAR-X and COSMO-SkyMed). Because of its single-polarization SAR data, the TerraSAR-X satellite is ultimately the best source of SAR data for swell-based bathymetry analyses. With an incidence angle of 20° and significant wave height of 0.6 m, the TerraSAR-X satellite has the largest theoretical depth detection range (with a minimum detectable depth of less than 2 m, and a maximum detectable depth of more than 200 m) for swell waves with a period of 15 s. The results of this study demonstrate that for low to moderate wave height, satellites with lower slant range to platform velocity ratios (RRV) can be successfully applied to the task of large-scale bathymetric mapping at shallow depths where there are weak tidal currents or where no recent or accurate ground truth data is available. Based on these results, we can make recommendations that will enable future users to get reliable, robust bathymetry information from their SAR data sets.

Retrieval of historical surface displacements of the Baige landslide from time-series SAR observations for retrospective analysis of the collapse event

Landslides and resultant barrier lakes are significant threats to human lives and infrastructures. Three-dimensional (3D) surface displacements can give vital clues to the exploration of internal structure of landslides, but they are difficult to be retrieved from spaceborne Synthetic Aperture Radar (SAR) observations due to the intrinsic limitation of SAR imaging geometry. Meanwhile, studies on predicting slope failure based on SAR-measured displacements are rarely seen. Here, we used SAR pixel offset tracking to investigate the Baige landslide before the collapse on 10 October 2018. 3D surface displacements retrieved by combining satellite SAR and optical observations revealed heterogeneous spatial patterns within the landslide complex. We observed linear secondary creep and accelerating tertiary creep prior to the failure from multi-sensor SAR data. The possibility of forecasting the failure was demonstrated by applying an inverse velocity method to the time-series displacements measured by Sentinel-1 during the tertiary creep, which is valuable for risk evaluation and disaster early warning.

Refocusing of Moving Targets Based on Low-Bit Quantized SAR Data via Parametric Quantized Iterative Hard Thresholding

Low-bit quantization of echo improves storage and leads to more efficient downlink transmission of spaceborne synthetic aperture radar (SAR) systems. In this paper, a new parametric quantized iterative hard thresholding (PQIHT) algorithm is proposed to refocus the images of moving targets with low-bit quantized SAR data, based on the combination of quantized iterative hard thresholding (QIHT) and the parametric sparse representation. The blurred and quantization-error-involved subimage of the region of interest (ROI) containing the moving target is represented in a sparse fashion through an adaptive parametric dictionary. The QIHT with a pruned searching method is performed for efficiently estimating the motion-adaptive parameter inside the dictionary, refocusing the ROI image and suppressing the quantization-induced error in an iterative way. Different from the conventional QIHT algorithm with a fixed dictionary that can only represent stationary targets, the proposed method exploits a parametric dictionary with a parameter related to target motion status, which is capable of adaptively representing the radar echo from a moving target with unknown motion status and, therefore, is suitable for moving target refocusing. Simulations and experiments on real GF-3 satellite SAR data demonstrate that, compared with the conventional parametric sparse representation framework for moving target refocusing based on purely precise data, the proposed algorithm can provide satisfactory quality of moving target refocusing with remarkably reduced data volume.

Detecting the slope movement after the 2018 Baige Landslides based on ground-based and space-borne radar observations

On Oct. 11 and Nov. 3, 2018, two large-scale landslides occurred in the same location in Baige Village, Tibet, and massive rocks fell and encroached into the Jingsha River. These landslides posed a severe risk to the upstream and downstream areas. The occurrence, development and evolution of landslides are accompanied by a large number of changes in measurable variables. The deformation data are one of most important parameters for characterizing change and development trends of a landslide. This paper is centered on the results derived from ground-based radar and space-borne Synthetic Aperture Radar (SAR) images in the post-event phase to monitor the Baige landslides and to assess their residual risk. Two technologies play important roles in identifying and characterizing impending catastrophic slope failures: ground-based radar reveals the horizontal deformation, and satellite SAR images reveal the azimuth and range offset deformation. By combining satellite and ground-based SAR observations, we obtained high-precision three-dimensional (3D) deformation results and found that the vast majority of the instability regions mainly occur in the source area of the slope failures and that the direction of collapse converges from all sides to the middle. Additional information from UAV orthophoto maps and GNSS measurements also reveal that several cracks are distributed on the trailing edge of the landslide and are still moving. The comprehensive results revealed that the moving rock mass has still been remarkably active after the two landslide events. This study combined ground-based and space-borne SAR data to develop a long-term monitoring and stability evaluation process for implementation after a large landslide disaster. Based on the distribution characteristics of the 3D deformation fields, the present and future stability of the Baige Landslide was analyzed.

Database of Crustal Deformation Observed by SAR: Improving Atmospheric Delay Mitigation for Satellite SAR Interferometry and Developing L-Band Multi-Type Portable SAR

Spaceborne synthetic aperture radar (SAR) and ground-based radar interferometers (GBRIs) can be used to detect spatially detailed crustal deformations that are difficult to detect by on-site observations, the Global Navigation Satellite System, tiltmeters, and so on. To make such crustal deformation information readily available to those engaged in evaluating volcanic activities and researching the mechanisms, we are preparing a database within the Japan Volcanological Data Network data sharing system to store crustal deformation detected by spaceborne SAR and GBRIs (Subtheme 2-1, Project B, the Integrated Program for Next Generation Volcano Research and Human Resource Development). In this study, we examined methods to reduce atmospheric delay noise in SAR interferometry using the numerical weather model and determined the methods for resampling the analytical values of the numerical weather model and estimating atmospheric delay to efficiently determine atmospheric delay. We show that the atmospheric delay can be estimated with higher accuracy by properly combining the isobaric surface and ground surface data of the mesoscale model (MSM) provided by the Japan Meteorological Agency. We are developing a multi-type portable SAR system as a GBRI system such that it would allow campaign observations whenever increased volcanic activities are observed and acquire crustal deformation with a higher temporal resolution than spaceborne SAR for storage in the database. This system employs L-band radar, which has a higher penetrability against vegetation. Two modes of observations are possible: ground-based SAR and car-borne SAR. The prototype was fabricated to conduct experiments necessary to develop a working model. The experimental observations was carried out around Asama volcano, and we confirmed that clear fringe was obtained.

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.

Calibration of the Copolarized Backscattering Measurements From Gaofen-3 Synthetic Aperture Radar Wave Mode Imagery

Accurate absolute radiometric calibration of spaceborne synthetic aperture radar (SAR) sensor is of great importance in quantitative oceanic monitoring. Traditionally, the calibration constant is determined by analyzing measurements of man-made calibrators deployed on land at a high expense. In this paper, a technique called numerical weather prediction (NWP)-based ocean calibration method for estimating the calibration constant on the basis of SAR observations over ocean is applied to the first Chinese C-band SAR satellite Gaofen-3 (GF-3). The ocean calibration is performed on GF-3 wave mode SAR images at VV and HH polarizations over a period of one year from September 2017 to August 2018. Verification against the independent scatterometer-derived winds shows that after NWP-based ocean recalibration, the accuracy of wind speed retrieval from GF-3 wave mode imagery could reach the wind speed estimation performance using the state-of-the-art of SAR data. These results indicate that GF-3 wind retrievals are promising for operational oceanic products and applications if the SAR data are appropriately calibrated by the proposed NWP-based ocean calibration approach.

SPACEBORNE SAR SIGNAL DETECTION AND PARAMETER ESTIMATION IN SPACE TRACKING AND SURVEILLANCE SYSTEM MODELING

The development of information support of the space tracking and surveillance system is a highly topical task, the solution of which will help to increase the effectiveness of monitoring space objects. Development and practical application of the software for Spaceborne synthetic aperture radar (SAR) signal detection and parameter estimation described and analyzed. Architecture of the software is described, processing results in the simulation mode (comparison of different processing methods) and real SAR satellite signals processing mode analyzed. In simulation mode detection and parameter estimation methods compared statistically as averaged estimation error as a function of the signal‑to‑noise ratio. Estimator statistical characteristics – bias, variation, error histogram – derived and analyzed.

Passive SAR satellite constellation for near-persistent earth observation: Prospects and issues

Over the last decades spaceborne synthetic aperture radar (SAR) has proved its capability as a remote sensing technique of great power and value. A number of precise SAR instruments (e.g., [1]–[4]) have been developed by space and defense agencies around the world and are being used today for a wide range of applications in wide-area land (e.g., [5]–[8]) and sea monitoring (such as [9]–[11]).

An Accurate Measurement Method for Azimuth Pointing of Spaceborne Synthetic Aperture Radar Antenna Beams Based on Ground Receiver.

The paper proposes a new method for measuring the azimuth pointing of spaceborne synthetic aperture radar (SAR) antenna beams based on the ground receiver, which can receive and record complex sampling data of the pulse signals transmitted from the spaceborne SAR. The center of the antenna pattern is extracted from the complex sampling data amplitude envelope to obtain the time when the beam main lobe center irradiates the ground receiver, and the range migration information is extracted from the complex sampling data to obtain the time when the satellite is over the top of the ground receiver. The results of Chinese civilian remote sensing GaoFen-3 SAR satellite experiment data processing show that the measurement accuracy of this method is better than 0.002°, which can be applied to the accurate measurement of azimuth pointing of various low Earth orbit (LEO) SAR antenna beams.

Simultaneous range ambiguity mitigation and sidelobe reduction using orthogonal non-linear frequency modulated (ONLFM) signals for satellite SAR Imaging

ABSTRACTThis letter first attempts to simultaneously reduce range ambiguities and sidelobes in spaceborne synthetic aperture radar (SAR). Two of the limitations of SAR are the range ambiguity phenomenon and the sidelobes effect. The range ambiguity appears with long delayed echoes. The current transmitted signal does not contribute to the reflected echo that is received after the transmission of one or more new pulses. Moreover, the conventional radar commonly uses linear frequency modulated (LFM) waveforms, producing a peak sidelobe ratio (PSLR) of −13.25 dB. Unfortunately, the sidelobes in SAR imagery contribute to speckle and interfere with nearby scatterers. This letter investigates the opportunity of designing the transmitted signals using orthogonal non-linear frequency modulated (ONLFM) waveform. The results demonstrate that ONLFM signals outperform conventional LFM signal. Using the proposed ONLFM waveforms, the PSLR is reduced to −50.25 dB, meanwhile the range ambiguities can be greatly suppressed, despite broadening the mainlobe.

Analyzing floating and bedfast lake ice regimes across Arctic Alaska using 25 years of space-borne SAR imagery

Late-winter lake ice regimes are controlled by water depth relative to maximum ice thickness (MIT). When MIT exceeds maximum water depth, lakes freeze to the bottom with bedfast ice (BI) and when MIT is less than maximum water depth lakes have floating ice (FI). Both airborne radar and space-borne synthetic aperture radar (SAR) imagery (Ku-, X-, C-, and L-band) have been used previously to determine whether lakes have a BI or FI regime in a given year, across a number of years, or across large regions. In this study, we use a combination of ERS-1/2, RADARSAT-2, Envisat, and Sentinel-1 SAR imagery for seven lake-rich regions in Arctic Alaska to analyze lake ice regime extents and dynamics over a 25-year period (1992–2016). Our interactive threshold classification method determines a unique statistic-based intensity threshold for each SAR scene, allowing for the comparison of classification results from C-band SAR data acquired with different polarizations and incidence angles. Additionally, our novel method accommodates declining signal strength in aging extended-mission satellite SAR instruments. Comparison of SAR ice regime classifications with extensive field measurements from six years yielded a 93% accuracy. Significant declines in BI regimes were only observed in the Fish Creek area with 3% of lakes exhibiting transitional ice regimes—lakes that switch from BI to FI during this 25-year period. This analysis suggests that the potential conversion from BI to FI regimes is primarily a function of lake depth distributions in addition to regional differences in climate variability. Remote sensing of lake ice regimes with C-band SAR is a useful tool to monitor the associated thermal impacts on permafrost, since lake ice regimes can be used as a proxy for of sub-lake permafrost thaw, considered by the Global Climate Observing System as an Essential Climate Variable (ECV). Continued winter warming and variable snow conditions in the Arctic are expected and our long-term analysis provides a valuable baseline for predicting where potential future lake ice regimes shifts will be most pronounced.

Geometric Accuracy Analysis for GaoFen3 Stereo Pair Orientation

Due to the all-weather and all-day advantage and the high geometric accuracy, the spaceborne synthetic aperture radar (SAR) stereo pair has a wide application in digital elevation model (DEM) production and ground control points (GCPs) extraction around the world. The GaoFen3 (GF3) remote sensing satellite is the first C-band multipolarization SAR satellite with a resolution of 1 m in China and plays an important role in commercial exploitation and scientific research. This letter performs a comprehensive analysis of the geometric accuracy for GF3 stereo pair orientation. By analyzing the orientation error sources, it is proven that the affine transformation model in image space can effectively compensate the unmodeled errors in GF3 imagery. Based on the rational polynomial coefficient model, the integrated orientation model for the GF3 stereo pair is presented here. Moreover, the model parameters and weight determination are further studied to analyze the influence of weight matrixes on geometric accuracy. Experimental results demonstrate that the proposed integrated orientation model can be effectively used for the GF3 stereo pair. The GCPs, convergent angle, and weight setting are the key factors influencing the geometric accuracy.

Multidimensional Small Baseline Subset (MSBAS) for volcano monitoring in two dimensions: Opportunities and challenges. Case study Piton de la Fournaise volcano

Space-borne Synthetic Aperture Radar (SAR) provides an opportunity for monitoring ground deformation at active volcanoes with high temporal and spatial resolutions. Modern SAR satellites acquire very large volumes of data that no longer can be effectively and efficiently processed and interpreted manually. The development of novel automatic processing methodologies is warranted in order to fully utilize big data. The Multidimensional Small Baseline Subset (MSBAS) methodology is an example of the semi-automatic processing system for computing temporally dense two-dimensional, horizontal east-west and vertical time series of ground deformation from ascending and descending SAR imagery acquired by various satellites. Here MSBAS is used for mapping ground deformation at the Piton de la Fournaise volcano (La Réunion Island, France) during the February 2012–April 2016 period from RADARSAT-2 data. Five volcanic eruptions occurred during the June 2014–October 2015 period, producing over 60cm of horizontal and over 30cm of vertical ground deformation, well-resolved in the MSBAS-derived time series. Validation of DInSAR results by comparison with GNSS observations and modeling of the two last and largest eruptions was performed. Validation showed good overall agreement between DInSAR and GNSS observations while revealing the benefits and limitations of both techniques. Modeling of fault and dike geometries attempted to explain the dis-proportionally large eastward motion of the eastern flank of the Piton de la Fournaise volcano that occurred during these eruptions. We demonstrated that the simple elastic model consisting of two dikes and a sliding surface can account for the observed ground deformation.