Future Synthetic Aperture Radar Research Articles

Improving the Estimation of Lake Ice Thickness with High-Resolution Radar Altimetry Data

Lake ice thickness (LIT) is a sensitive indicator of climate change, identified as a thematic variable of Lakes as an Essential Climate Variable (ECV) by the Global Climate Observing System (GCOS). Here, we present a novel and efficient analytically based retracking approach for estimating LIT from high-resolution Ku-band (13.6 GHz) synthetic-aperture radar (SAR) altimetry data. The retracker method is based on the analytical modeling of the SAR radar echoes over ice-covered lakes that show a characteristic double-peak feature attributed to the reflection of the Ku-band radar waves at the snow–ice and ice–water interfaces. The method is applied to Sentinel-6 Unfocused SAR (UFSAR) and Fully Focused SAR (FFSAR) data, with their corresponding tailored waveform model, referred to as the SAR_LIT and FFSAR_LIT retracker, respectively. We found that LIT retrievals from Sentinel-6 high-resolution SAR data at different posting rates are fully consistent with the LIT estimations obtained from thermodynamic lake ice model simulations and from low-resolution mode (LRM) Sentinel-6 and Jason-3 data over two ice seasons during the tandem phase of the two satellites, demonstrating the continuity between LRM and SAR LIT retrievals. By comparing the Sentinel-6 SAR LIT estimates to optical/radar images, we found that the Sentinel-6 LIT measurements are fully consistent with the evolution of the lake surface conditions, accurately capturing the seasonal transitions of ice formation and melt. The uncertainty in the LIT estimates obtained with Sentinel-6 UFSAR data at 20 Hz is in the order of 5 cm, meeting the GCOS requirements for LIT measurements. This uncertainty is significantly smaller, by a factor of 2 to 3 times, than the uncertainty obtained with LRM data. The FFSAR processing at 140 Hz provides even better LIT estimates, with 20% smaller uncertainties. The LIT retracker analysis performed on data at the higher posting rate (140 Hz) shows increased performance in comparison to the 20 Hz data, especially during the melt transition period, due to the increased statistics. The LIT analysis has been performed over two representative lakes, Great Slave Lake and Baker Lake (Canada), demonstrating that the results are robust and hold for lake targets that differ in terms of size, bathymetry, snow/ice properties, and seasonal evolution of LIT. The SAR LIT retrackers presented are promising tools for monitoring the inter-annual variability and trends in LIT from current and future SAR altimetry missions.

Application of Gated Recurrent Unit Neural Network for Flood Extraction from Synthetic Aperture Radar Time Series

Floods are a sudden and influential natural disaster, and synthetic aperture radar (SAR) can image the Earth’s surface almost independently of time and weather conditions, making it particularly suitable for extracting flood ranges in time. Platforms such as Google Earth Engine (GEE) can provide a large amount of SAR data and preprocess it, providing powerful assistance for real-time flood monitoring and time series analysis. However, the application of long-term series data combined with recurrent neural networks (RNNs) to monitor floods has been lacking in current research, and the accuracy of flood extraction in open water surfaces remains unsatisfactory. In this study, we proposed a new method of near real-time flood monitoring with a higher accuracy. The method utilizes SAR image time series to establish a gated recurrent unit (GRU) neural network model. This model was used to predict normal flood-free surface conditions. Flood extraction was achieved by comparing and analyzing the actual flood surface conditions with the predicted conditions, using a parameter called Scores. Our method demonstrated significant improvements in accuracy compared to existing algorithms like the OTSU algorithm, Sentinel-1 Dual Polarized Water Index (SDWI) algorithm, and Z-score algorithm. The overall accuracy of our method was 99.20%, which outperformed the Copernicus Emergency Management Service (EMS) map. Importantly, our method exhibited high stability as it allowed for fluctuation within the normal range, enabling the extraction of the complete flood range, especially in open water surfaces. The stability of our method makes it suitable for the flood monitoring of future open-access SAR data, including data from future Sentinel-1 missions.

An Advanced Non-Interrupted Internal Calibration Model Based on Azimuth Modulation and Waveform Diversity for SAR Systems

Internal calibration, designed for obtaining the gain and phase errors introduced by the fluctuations of the electronic instruments, is an essential operation to guarantee the imaging performance of modern synthetic aperture radar (SAR) systems. However, in most of the current internal calibration schemes, the internal calibration processes interrupt the normal SAR data acquisition, which results in a loss of azimuth samples and degradation of the SAR image quality. To this end, an advanced non-interrupted internal calibration model is proposed, performing the internal calibration during nominal data acquisitions. The calibration signals and echoes are orthogonal and are received simultaneously. Then, they can be separated by postprocessing via the waveform diversity concept. Two schemes based on the proposed model are demonstrated via theoretical analysis and simulation experiments. The proposed model can achieve a considerable signal-to-noise ratio (SNR) and reduce the influence of calibration signals on echoes, which have some potential applications for future SAR missions.

Wind Retrieval from Constellations of Small SAR Satellites: Potential for Offshore Wind Resource Assessment

The planning of offshore wind energy projects requires wind observations over long periods for the establishment of wind speed distributions. In the marine environment, high-quality in situ observations are sparse and restricted to point locations. Numerical modeling is typically used to determine the spatial variability of the wind resource. Synthetic Aperture Radar (SAR) observations from satellites can be used for retrieval of wind fields over the ocean at a high spatial resolution. The recent launch of constellations of small SAR satellites by private companies will improve the sampling of SAR scenes significantly over the coming years compared with the current sampling rates offered by multi-purpose SAR missions operated by public space agencies. For the first time, wind fields are retrieved from a series of StriX SAR scenes delivered by Synspective (Japan) and also from Sentinel-1 scenes delivered by the European Space Agency. The satellite winds are compared with wind speed observations from the FINO3 mast in the North Sea. This leads to root-mean-square errors of 1.4–1.8 m s−1 and negative biases of −0.4 m s−1 and −1.0 m s−1, respectively. Although the Geophysical Model Functions (GMF) applied for wind retrievals have not yet been tuned for StriX SAR observations, the wind speed accuracy is satisfactory. Through conditional sampling, we estimate the wind resource from current and future SAR sampling scenarios where the number of SAR satellites in orbit is increasing over time. We find that hourly samples are needed to fully capture the diurnal wind speed variability at the site investigated. A combination of SAR samples from current missions with samples from clusters of small SAR satellites can yield the necessary number of wind speed samples for accurate wind resource estimation. This is particularly important for sites with pronounced diurnal wind speed variability. An additional benefit of small SAR satellites is that wind speed variability can be mapped at the sub-km scale. The very high spatial resolution is valuable for characterizing the wind conditions in the vicinity of existing offshore wind farms.

A noise autocovariance model for SAR altimeter measurements with implications for optimal sampling

Earlier work has empirically demonstrated some advantages of an increased posting rate of Synthetic Aperture Radar (SAR) altimeters beyond the expected ground resolution of about 320 m in Delay-Doppler (unfocused SAR, UFSAR) processing, corresponding to ∼20 Hz sampling. Higher posting rates of 40–80 Hz were shown to prevent spectral aliasing of the signal, enable to measure swell wave related signal distortions and may lead to a reduced root mean square error of 1 Hz estimates of Sea Surface Heights (SSH), radar cross section (sigma0) and Significant Wave Heights (SWH) from current SAR altimeters. These improvements were explained by the narrow noise autocovariance function of the waveform signal’s power speckle noise in along-track direction on one hand, and frequency doubling by power detection (squaring of the signal) on the other. It has not been explained, however, why the power speckle noise decorrelates faster than anticipated by the predicted Doppler resolution, and whether this decorrelation depends on the altimeter and processing configuration. Also, it has not been shown explicitly that the estimates of SSH, SWH and sigma0 decorrelate in the same way. Describing the noise autocovariance function – or equivalently the noise power spectral density via the Wiener-Kintchin theorem – is necessary on two counts: Knowing the noise autocovariance allows to apply optimal filtering strategies that maximize precision on one hand, while the noise power spectral density predicts the frequencies contained in the noise (and signals), which in turn determines the required sampling frequency according to the Nyquist theorem. Using a newly derived analytic noise autocovariance model for UFSAR-processed altimeter data, we show that the swift signal decorrelation is mainly due to the observation geometry. Furthermore, our results demonstrate that the noise autocovariance functions of power speckle, SSH, SWH and sigma0 estimates in along-track direction are different and depend on the sea state. On top of that, the noise autocovariance functions are strongly dependent on the number of Doppler beams used for multilooking, the used retracker, and the processing choices such as antenna gain pattern compensation and windowing within the UFSAR processing (Level-1b). We validated our noise autocovariance model with segments of 42 Sentinel-3B overpasses. Our findings are in accordance to all earlier work, but indicate that the reported precision improvements with respect to 20 Hz may have been too optimistic and that the SSH, SWH and sigma0 generally decorrelate slower than the power speckle noise. We found that the required posting rate is always higher or equal to 40 Hz. Our results will potentially enable improved spectral analysis and optimal filtering of any UFSAR altimetry data. More importantly, our results can be used to trade off different aspects for determining an optimal posting rate in UFSAR altimeter processing in different sea states and with changing processing parameters, which is necessary in view of strict precision requirements of existing and future SAR altimetry missions.

Investigating the dielectric properties of lunar surface regolith fines using Mini-RF SAR data

Polarimetric synthetic aperture radar (SAR) is an effective technique to retrieve physical properties of planetary surfaces, such as the dielectric constant and surface roughness. Dielectric properties of lunar regolith are quite attractive for future lunar SAR missions. In this paper, we investigate the dielectric properties of lunar regolith by the Mini-RF SAR data. First, a new model of dielectric constant inversion for hybrid polarimetric SAR is proposed, in which the hybrid polarimetric scattering similarity parameter is first introduced. Second, the dielectric constants of Apollo 14, 16, 17 and Chang’E-5 landing sites are estimated through the proposed model. The inversion results fit well with the laboratory measurements of lunar samples, with an estimated root mean square error (RMSE) of 0.53. In addition, we analyze the dielectric properties of regolith on crater floors in different geologic settings, including the lunar maria, highlands, and permanently shadowed regions (PSRs) near the lunar poles. The results indicate that for craters with diameters of 5–25 km, the real part of the dielectric constant of regolith fines increases with crater depth-to-diameter (d/D) ratio, while no apparent correlation is found with crater diameter. Furthermore, the average dielectric constant of regolith fines is 3.01 in PSRs, which is less than that in the lunar maria and highlands (3.43 and 4.13, respectively). This implies that craters in PSRs may possess a looser regolith material compared to the mid-latitude craters. In a word, the proposed method is useful for estimating the dielectric properties of lunar regolith, and it is promising for future lunar SAR applications.

Unified Classification Framework for Multipolarization and Dual-Frequency SAR

For synthetic aperture radar (SAR), multi-polarization and multi-frequency modes greatly enrich the acquired earth resource information and have been widely applied in remote sensing fields. In this paper, we compare the classification capabilities of multi-polarization and dual-frequency SAR. To meet the objective of selecting consistent and complete polarimetric information, a unified classification framework is proposed. In the framework, covariance matrices are used directly as inputs instead of polarimetric indicators. Additionally, the Wishart mixture model (WMM) is utilized to characterize the statistical distribution of polarimetric SAR data. Besides, the data log-likelihood function is utilized to mitigate the influence of the initial values on the expectation-maximization (EM) algorithm. Then, among the combinations of four sample-to-subclass distances and two schemes for obtaining sample-to-class distances, the one with the best classification performance is selected as the default for this framework. In the experiments, the classification capabilities of full polarization (FP), compact polarization (CP), and dual polarization (DP) modes are first compared through the proposed classification framework. Then, we compare the classification capabilities of dual-frequency SAR in FP, CP, and DP modes. For PolSAR system design, it is necessary to strike a balance between demand indexes (classification performance, coverage width, and so on) and cost (such as budget, weight, and so on). The comparison results provide a reference for the optimization of polarization modes and frequency bands of the existing multi-polarization and dual-frequency SAR payloads and the design of future SAR systems.

Influence of Radar Parameters and Sea State on Wind Wave-Induced Velocity in C-Band ATI SAR Ocean Surface Currents

Wind wave-induced artifact surface velocity (WASV) is an important component of the sea surface motions detected by synthetic aperture radar (SAR) systems. Understanding the characteristics of the interference of WASV on SAR current velocity estimates is necessary to improve the accuracy of retrievals. In this study, we assessed and analyzed the sensitivity of WASV in C-band along-track interferometric (ATI) SAR to radar configuration, wind field, swell field, and a wave spectrum model. Results showed that the influence of wind speed on WASV increased with the current velocity. The swell also affected WASV, especially at higher wind speeds; WASV was more strongly influenced by swell amplitude than by swell wavelength. In terms of radar configurations, results showed that VV polarization was more suitable than HH polarization in the estimation of WASV. The interference of WASV was minimal at moderate incidence angles (around 40°), and an appropriate ATI baseline selection was also given. The WASV was more strongly influenced by sea states than by the wave spectrum model or by a spreading function. The findings of this study improve our understanding of WASV and provide a reference for the design of future ATI SAR current measurement instruments and projects.

Performance Analysis of Ku/Ka Dual-Band SAR Altimeter from an Airborne Experiment over South China Sea

Satellite radar altimeters have been successfully used for sea surface height (SSH) measurement for decades, gaining great insight in oceanography, meteorology, marine geology, etc. To further improve the observation precision and spatial resolution, radar altimeters have evolved from real aperture to synthetic aperture, from the Ku-band to Ka-band. Future synthetic aperture radar (SAR) altimeter of the Ka-band is expected to achieve better performance than its predecessors. To verify the SAR altimeter data processing method and explore the system advantage of the Ka-band, a Ku/Ka dual-band SAR altimeter airborne experiment was carried out over South China Sea on 6 November 2021. Through dedicated hardware design, this campaign has acquired the Ku and Ka dual-band echo data simultaneously. The airborne data are processed to estimate the SSH retrieval precision after a series of procedures (including height compensation, range migration correction, multi-look processing, waveform re-tracking). To accustom to the airborne experiment design, a SAR echo model that fully considers both the attitude variation of the aircraft and the elliptical footprint of radar beam is established. The retrieved SSH data are compared with the public SSH data along the flight path at the experiment day, showing good consistence for both bands. By calculating the theoretical precision of waveform re-tracking and re-processing the dual-band airborne data into different bandwidths, it is demonstrated that the Ku/Ka precision ratio is possible to achieve 1.4 within the 27 km offshore area, which indicates that Ka-band has better performance.

A Novel Aperture Extension Loss Compensation Scheme and Azimuth Ambiguity Suppression Method for Airborne Elevation DBF-SAR

Digital beamforming (DBF) is a state-of-the-art technique for high-resolution and wide-swath (HRWS) observation in synthetic aperture radar (SAR) imaging. Since azimuth high-resolution imaging will be a popular tendency in future SARs, DBF-SAR needs to become practical. A new problem arising in airborne DBF-SAR application is the aperture extension loss (AEL). Similar to the pulse extension loss, it is confirmed in our study that AEL will widen the point target responses and degrade the signal-to-noise ratio (SNR) improvement in airborne DBF-SAR. However, little work has been devoted to the compensation of the AEL effect. In this article, the effects of AEL are demonstrated and two compensation methods are proposed, discussed, and implemented for the processing of raw data. The above are demonstrated through simulations and an airborne experimental C-band azimuth high-resolution DBF-SAR. The results show that the AEL compensation removes the AEL effects and increases the SNR with the cost of higher impulse response sidelobes. Moreover, with this novel design scheme, it is demonstrated that azimuth ambiguity suppression can be implemented by elevation DBF.

Decorrelating Ambiguities in SAR Interferometry Through Slight PRI Variation

Synthetic aperture radar (SAR) interferometry is a well-established technique for producing high-resolution digital elevation models (DEMs) of the Earth’s surface and measuring displacements on different time scales. Observations of SAR interferograms, however, show that azimuth ambiguities can be coherently imaged and may lead to phase biases and coherence losses that significantly degrade the interferometric performance. Whereas imposing very low ambiguity levels may represent a severe design constraint for a spaceborne SAR system, a slight variation of the pulse repetition interval (PRI) is a new, simple, yet effective technique to decorrelate ambiguities, which in turn reduces the phase biases and coherence losses without substantially affecting the imaged swath width. An additional benefit of the PRI variation is that range ambiguities also become decorrelated. This paper addresses two cases: For the repeat-pass case, slightly different pulse repetition frequencies (PRFs) can be used for the two acquisitions and the minimum required PRF difference can be analytically derived resorting to the power spectral density of the ambiguous signals; For the single-pass case, a slight variation of the PRI during the common acquisition is an effective solution, in case an along-track baseline is present. In particular, a square wave PRI variation scheme outperforms sinusoidal or random ones. Finally, simulations using TanDEM-X data are presented to show the improvement in interferogram and DEM quality resulting from ambiguity decorrelation. This work is relevant for the design of future spaceborne interferometric SAR systems and for the enhanced exploitation of current ones.

An Advanced Scheme for Range Ambiguity Suppression of Spaceborne SAR Based on Blind Source Separation

Due to the minimum antenna area constrain of synthetic aperture radar (SAR), high-resolution and wide-swath (HRWS) imaging is difficult to be achieved using classical modes, such as scan, spotlight, and so on. Range ambiguity is one of the main technical challenges limiting HRWS imaging in spaceborne SAR. Insipred by the cocktail party effect, an advanced scheme based on blind source separation is put forward to suppress the range ambiguity of spaceborne SAR in this paper. In the scheme, multiple subantennas are used to collect multiple echo data sets, which are given different patterns. In this way, the echo signal of the desired region and that of the ambiguous region are weighted using different coefficients. During postprocessing, a detailed flow with the blind source separation algorithm is proposed to separate the desired echoes from those data sets. To verify the scheme, point target and scene simulations based on GF3 are carried out. The results indicate that the range ambiguity can be reduced by more than 15 dB using the proposed scheme, the processing flow is effective, and the scheme has a good performance without increasing the complexity of the system design under the current SAR system conditions. The scheme has the potential to be adopted in future spaceborne SAR missions.

The dark side of the remote sensing: current SAR remote sensing missions and applications

The present paper provides an overview of Synthetic Aperture Radar (SAR) remote sensing concepts. SAR remote sensing is a coherent active imaging technique, where the spaceborne sensor emits an electromagnetic wave and captures its backscattered signal. Each pixel contains amplitude information, witness of the ground properties to reflect the signal back to the sensor, and a phase component, which is related to the distance from the sensor to the ground target. Firstly, we will focus on SAR and SAR interferometry concepts. The acquisition geometry, the different wavelengths, the issue of spatial resolution, the polarization; SAR has a number of differences compared to optical remote sensing. In addition, the coherent imaging technique allows the exploitation of the phase information, with applications such as DEM generation or surface displacements retrieval. In a second part, we will discuss the current and future SAR constellations as well as recent advances in applications coming from the deep learning field. The domain of SAR remote sensing is a rapidly evolving field, where more and more satellites are being set up and where the private sector is investing massively. Service-oriented market using small X-Band SAR satellites is getting more and more present. In parallel, public institutions already have several important SAR satellites and are currently preparing the next generation, with improved technical specifications.

Location of Synthetic Aperture Radar Imagery via Range History

Geolocation is one of the key synthetic aperture radar (SAR) image processing procedures in SAR-based remote sensing applications. The conventional SAR imagery geolocation model is based on the range-Doppler (RD) equation, which is derived from the Fresnel approximation of SAR. Currently, there is no other rigorous geolocation model for modern high-resolution SAR; however, this approximation may not be fully applicable for various modern SAR imaging modes and algorithms. This study aims to develop a novel SAR image geolocation model based on the SAR range history (RH) equation, which is derived from the basic SAR backscattered signal property. Moreover, a new geometric calibration model is presented for RH-based location. Experiments based on real spaceborne SAR data are presented as examples, and the location accuracy of RH and RD location models are compared. The results show that the location accuracies of the RH and RD models are consistent under the existing SAR processing framework, but those for the RH model demonstrate better performance in the azimuth direction. In theory, the proposed RH model can be used for SAR image products generated from complex modes and non-Fresnel-approximation-based imaging algorithms, making it suitable for future SAR systems.

Characterization of Nadir Echoes in Multiple-Elevation-Beam SAR With Constant and Variable Pulse Repetition Interval

Multiple-elevation-beam synthetic aperture radar (SAR) is a concept based on digital beamforming (DBF) in elevation and simultaneous recording of the echoes of multiple transmitted pulses. It enables high-resolution imaging of wide areas and is therefore ideal for the systematic observation of dynamic processes on the Earth’s surface. Furthermore, if the pulse repetition interval (PRI) is continuously varied (staggered SAR), it is possible to map a wide continuous swath rather than multiple subswaths separated by “blind” ranges. Within the design of multiple-elevation-beam SAR, however, it is fundamental to consider how nadir echoes affect the mapping capabilities of systems with constant PRI and the image quality of staggered SAR systems, where nadir echoes are intrinsically smeared due to the PRI variation. This article addresses the characterization of nadir echoes in multiple-elevation-beam SAR with constant and variable PRI by presenting a parametric model for the nadir echo profile based on real radar measurements, a formulation of the nadir echo location and smearing in staggered SAR, and realistic simulations based on TerraSAR-X data, which show that nadir echo are likely to be barely visible in staggered SAR images. The results of this work are relevant to both the design of future SAR systems and the interpretation of the acquired data.

On the Value of LES Models for Evaluating Spatio-Temporal Tropospheric Variability in Multitemporal SAR Interferograms

Atmospheric delay has a profound impact on synthetic aperture radar (SAR) interferometry, inducing a spatial signal that significantly devaluates interferometric products. While the wide-scale variability of the atmosphere can be adequately modeled with global or regional weather models, it is especially the turbulent and convective part of the atmosphere at smaller spatial and temporal scales that is typically poorly captured. Due to the high resolution and precision of InSAR, there is a need for a realistic modelling of the 3D distribution of turbulent refractivity in the boundary layer. This would enable assessment of the impact of a temporal or spatial model misalignment on the interferometric products, and contribute to studying the impact for future SAR missions. Here we test the feasibility of an advanced Large Eddy Simulation (LES) model to simulate a time-series refractivity distribution with a high spatio-temporal resolution to show the spatio-temporal variability of the troposphere on short time scales. We found for a fair-weather situation that the LES model produces realistic atmospheric simulations that match stochastically with results found in interferometric studies and that tropospheric delay variation leads to significant phase gradients within several minutes. This implies that even when using an (unrealistic) perfect weather model with resolutions similar to the SAR image, realizations that are several minutes apart from the time of the SAR acquisition will lead to significant phase errors. We propose the use of LES models as a realistic instrument to perform InSAR quality-assessments and for the development and simulation for future missions.

On-Ground RFI Mitigation for Spaceborne Multichannel SAR Systems Using Auxiliary Beams

Radio frequency interference (RFI) is becoming a major concern for future synthetic aperture radar (SAR) missions due to the increased user demand for frequency occupation in a number of applications. Each occurrence of interference introduces artifacts in the radar imagery, biasing the measurements and leading to erroneous results. In addition to conventional techniques, the use of multichannel SAR for RFI mitigation has been proposed, because its digital beamforming (DBF) capability allows for a spatial filtering of the received signals. Thereby, it becomes possible to remove RFI that arrives from a different direction than the SAR signal. Past publications on the topic presented highly flexible spatial filtering techniques. Those methods require either additional on-board processing or a substantial increase in the downlink capacity. This article shows that by slightly reducing the flexibility of the spatial filtering, DBF can be utilized for RFI mitigation without either drawbacks: the processing is performed on-ground after downlinking the data and the data volume remains manageable. This is achieved with auxiliary beams. Their concept and limitations are discussed in detail in this article and are supported with simulated RFI mitigation results. Furthermore, it is shown that the information collected with an auxiliary beam can also be used to filter the RFI signal when it is spatially nonorthogonal to the SAR signal.

SAR(Synthetic Aperture Radar) 위성 개발현황 및 향후 HRWS(High Resolution Wide Swath) SAR 위성 개발전략

This paper is made to suggest a future strategy for the Korean High Resolution Wide Swath Synthetic Aperture Radar (HRWS SAR) satellite development by surveying the current trends for the SAR satellite technologies. From the survey, the latest SAR technology trends are revealed of using Digital Beam-Forming (DBF), SCan-On-Receive (SCORE), Displaced Phase Center Antenna (DPCA), interferometry, and polarimetry for exploiting the SAR imagery. Based on the latest SAR technology trends and the foreign HRWS SAR development cases, the strategy for the future HRWS Korean SAR satellite development is suggested to develop the DPCA and SCORE technologies by using the KOrea Multi-Purpose SATellite-6 (KOMPSAT-6) which is going to launch in a few years, and consequently to develop the HRWS SAR satellites which can monitor the whole Earth at weekly intervals.

A Waveform-Encoded SAR Implementation Using a Limited Number of Cyclically Shifted Chirps

Synthetic aperture radar (SAR) provides high-resolution images of the Earth’s surface irrespective of sunlight and weather conditions. In conventional spaceborne SAR, nadir echoes caused by the pulsed operation of SAR may significantly affect the SAR image quality. Therefore, the pulse repetition frequency (PRF) is constrained within the SAR system design to avoid the appearance of nadir echoes in the SAR image. As an alternative, the waveform-encoded SAR concept using a pulse-to-pulse variation of the transmitted waveform and dual-focus postprocessing can be exploited for nadir echo removal and to alleviate the PRF constraints. In particular, cyclically shifted chirps have been proposed as a possible waveform variation scheme. However, a large number of distinct waveforms is required to enable the simple implementation of the concept. This work proposes a technique based on the Eulerian circuit for generating a waveform sequence starting from a reduced number of distinct cyclically shifted chirps that can be effectively exploited for waveform-encoded SAR. The nadir echo suppression performance of the proposed scheme is analyzed through simulations using real TerraSAR-X data and a realistic nadir echo model that shows how the number of distinct waveforms and therefore the system complexity can be reduced without significant performance loss. These developments reduce the calibration burden and make the concept viable for implementation in future SAR systems.

A Benchmark High-Resolution GaoFen-3 SAR Dataset for Building Semantic Segmentation

Deep learning is increasingly popular in remote sensing communities and already successful in land cover classification and semantic segmentation. However, most studies are limited to the utilization of optical datasets. Despite few attempts applied to synthetic aperture radar (SAR) using deep learning, the huge potential, especially for the very high resolution (VHR) SAR, are still underexploited. Taking building segmentation as an example, the VHR SAR datasets are still missing to the best of our knowledge. A comparable baseline for SAR building segmentation does not exist, and which segmentation method is more suitable for SAR image is poorly understood. This article first provides a benchmark high-resolution (1 m) GaoFen-3 SAR datasets, which cover nine cities from seven countries, review the state-of-the-art semantic segmentation methods applied to SAR, and then summarize the potential operations to improve the performance. With these comprehensive assessments, we hope to provide the recommendation and roadmap for future SAR semantic segmentation.