Synthetic Aperture Radar Mode Research Articles

Maritime Moving Target Reconstruction via MBLCFD in Staggered SAR System

Imaging maritime targets requires a high resolution and wide swath (HWRS) in a synthetic aperture radar (SAR). When operated with a variable pulse repetition interval (PRI), a staggered SAR can realize HRWS imaging, which needs to be reconstructed due to echo pulse loss and a nonuniformly sampled signal along the azimuth. The existing reconstruction algorithms are designed for stationary scenes in a staggered SAR mode, and thus, produce evident image defocusing caused by complex target motion for moving targets. Typically, the nonuniform sampling and complex motion of maritime targets aggravate the spectrum aliasing in a staggered SAR mode, causing inevitable ambiguity and degradation in its reconstruction performance. To this end, this study analyzed the spectrum of maritime targets in a staggered SAR system through theoretical derivation. After this, a reconstruction method named MBLCFD (Modified Best Linear Unbaised and Complex-Lag Time-Frequency Distribution) is proposed to refocus the blurred maritime target. First, the signal model of the maritime target with 3D rotation accompanying roll–pitch–yaw movement was established under the curved orbit of the satellite. The best linear unbiased (BLU) method was modified to alleviate the coupling of nonuniform sampling and target motion. A precise SAR algorithm was performed based on the method of inverse reversion to counteract the effect of a curved orbit and wide swath. Based on the hybrid SAR/ISAR technique, the complex-lag time-frequency distribution was exploited to refocus the maritime target images. Simulations and experiments were carried out to verify the effectiveness of the proposed method, providing precise refocusing performance in staggered mode.

Analysis of wave breaking on synthetic aperture radar at C-band during tropical cyclones

ABSTRACT The purpose of our work is to analyze the effect of wave breaking on dual-polarized (vertical-vertical (VV) and vertical-horizontal (VH)) synthetic aperture radar (SAR) image in the C-band during tropical cyclones (TCs) based on the machine learning method. In this study, more than 1300 Sentinel-1 (S-1) interferometric-wide (IW) and extra wide (EW) mode SAR images are collocated with wave simulations from the WAVEWATCH-III (WW3) model during 400 TCs. The validation of the significant wave height (SWH) simulated using the WW3 model against Jason-2 altimeter data. The winds for S-1 SAR images are reconstructed using wind retrievals in VV and VH polarization. The non-polarized (NP) contribution σ wb caused by wave breaking is assumed to be the result of the SAR-measured normalized radar cross-section (NRCS) σ 0 minus the Bragg resonant roughness σ br without the distortion of rain cells during TCs. The σ br is simulated by imputing wave spectra from the WW3 model into the theoretical backscattering model. It is found that the ratio (σ wb /σ 0) in VV polarization is related to the wind speed, the wind direction relative with the flight orientation, and radar incidence angle. Following this rationale, the Adaptive Boosting (AdaBoost) model was used for the estimation of NP contribution σ wb during TCs and are implemented for more than 300 dual-polarized S-1 images to validate the model. It is found that for the comparison between the sum of simulation NRCS and SAR observations, the root mean squared error (RMSE) is 1.95 dB and the coefficient (COR) is 0.86, which is better than a 2.83 dB RMSE and a 0.67 COR by empirical model. It is concluded that the AdaBoost model has a good performance on NP component simulation during TCs.

Machine learning based classification of lake ice and open water from Sentinel-3 SAR altimetry waveforms

The aim of the study was to evaluate, for the first time, the capability of different machine learning (ML) algorithms in classifying along-track lake surface conditions (open water and ice types) across ice seasons (freeze-up, ice growth and break-up periods) from Sentinel-3 A/B synthetic aperture radar altimeter (SRAL) data. To achieve this goal, over 107,500 radar waveforms extracted from 11 large lakes across the Northern Hemisphere and three ice seasons (2018–2021) were manually labelled using complementary satellite data (Sentinel-1 imaging Synthetic Aperture Radar (SAR), Sentinel-2 Multispectral Instrument (MSI) Level 1C, and MODIS Aqua/Terra data) for the training and testing of the ML algorithms in discriminating between open water, young (thin) ice, growing ice and melting ice. The four ML algorithms tested include Random Forest (RF), Gradient Boosting Trees (GBT), K Nearest Neighbor (KNN) and Support Vector Machine (SVM). To characterize the waveforms, seven waveform parameters were derived: Leading Edge Width (LEW), Offset Center of Gravity (OCOG) Width, Pulse Peakiness (PP), backscatter coefficient (Sigma0), late tail to peak power (LTPP), early tail to peak power (ETPP) and the maximum value of the echo power (Max). Accuracies >95% were achieved across all classifiers using a 4-parameter combination (Sigma0, PP, OCOG Width, and LEW). Among all waveform parameters, Sigma0, OCOG width and PP were found to be the most important parameters for discriminating between lake ice types and open water. Despite showing comparable classification performances in the overall classification, RF and KNN are found to be a better fit for global lake ice mapping as both are less sensitive to their internal hyperparameters. Additionally, consistent results (>93.7% accuracy in all classifiers) achieved on the accuracy assessment carried out for each lake (out-of-sample testing) revealed the strength of the classifiers for spatial transferability. Implementation of RF and KNN could be valuable in a pre-or post-processing step for identifying lake surface conditions under which the retrieval of water level and ice thickness may be limited or not possible and, therefore, inform algorithms currently used for the generation of operational or research products. While the research focused on 11 of the largest lakes of the Northern Hemisphere, the classification approach presented herein has potential for application on smaller lakes too since data in SAR mode (∼300 m along-track resolution) are used.

Towards the Mitigation of Discrepancies in Sea Surface Parameters Estimated from Low- and High-Resolution Satellite Altimetry

In this study, we present an extension to existing numerical retrackers of synthetic-aperture radar (SAR) altimetry signals. To our knowledge at the time of writing this manuscript, it offers the most consistent retrieval of geophysical parameters compared to low-resolution mode (LRM) retracking results. We achieve this by additionally estimating the standard deviation of vertical wave-particle velocities σv and a new parameter ux, linked to a residual Doppler in the returned radar echoes, which can be related to wind speed and direction. Including this new parameter into the SAR stack retracker mitigates sea surface height estimation errors by up to two centimeters for Sentinel-6MF SAR mode results. Additionally, we found a closed-form equation to describe ux as a function of eastward and northward wind variables, which allows mitigating the effects of this parameter on a SAR stack within level 1B processing and generating a lookup table to correct sea surface height estimates in SAR mode. This additionally opens up the door to estimating the wind speed and direction from SAR altimetry stacks. Additionally, we discuss how this new retracker performs with respect to different planned future baseline processor changes of Sentinel-6MF, namely F09 and F10, by attempting to imitate their level 2 processing. This is achieved by processing cycles 017 to 051 (nearly a full year) of Sentinel-6MF level 1A data on a global scale. We observe that the new retracking method is, on average, more accurate with respect to LRM. However, there is a slight increase in measurement noise due to the introduction of an additional parameter. To ensure that the results of the new retracker are not biased, we retrack using both the new method and the SINCS-OV ZSK retracker on Sentinel-6MF stack data produced in a Monte Carlo simulation. We analyze the simulation results with respect to accuracy, precision, and correlations between estimated parameters. We show that the accuracy of the new retracker is better than SINCS-OV ZSK but less precise, which could be related to higher correlation coefficients—especially with respect to the new parameter ux—between estimated parameters.

Evaluation of Sentinel-6 Altimetry Data over Ocean

The Sentinel-6 Michael Freilich (S6-MF) satellite was launched on 21st November 2020. Poseidon-4, the main payload onboard S6-MF, is the first synthetic aperture radar (SAR) altimeter operating in an interleaved open burst mode. In this study, the sea surface height (SSH), significant wave height (SWH) and wind speed observations from the Poseidon-4 Level 2 altimetry products from November 2021 to October 2022 are assessed. The assessment contains synthetic aperture radar mode (SARM) as well as low-resolution mode (LRM) data. The SSH assessment is conducted using range noise, sea level anomaly (SLA) spectral analysis and crossover analysis, whereas the SWH and wind speed assessments are performed against NDBC buoy data and other satellite altimetry missions. The performance of the Sentinel-6 altimetry data is compared to those of Sentinel-3A/B and Jason-3 altimetry data. The 20 Hz range noise is 3.07 cm for SARM and 6.40 cm for LRM when SWH is 2 m. The standard deviation (STD) of SSH differences at crossovers is 3.76 cm for SARM and 4.27 cm for LRM. Compared against the NDBC measurements, the Sentinel-6 SWH measurements have a root-mean-square error (RMSE) of 0.361 m for SARM and an RMSE of 0.225 m for LRM. The Sentinel-6 wind speed measurements show an RMSE of 1.216 m/s for SARM and an RMSE of 1.323 m/s for LRM. We also present the impacts of ocean waves on parameter retrievals from Sentinel-6 SARM data. The Sentinel-6 SARM data are sensitive to wave period and direction as well as vertical velocity. It should be paid attention to in the future.

High-Resolution Wide-Swath Ambiguous Synthetic Aperture Radar Modes for Ship Monitoring

This paper proposes two high-resolution, wide-swath synthetic aperture radar (SAR) acquisition modes for ship monitoring that tolerate ambiguities and do not require digital beamforming. Both modes, referred to as the low pulse repetition frequency (PRF) and the staggered (high PRF) ambiguous modes, make use of a wide elevation beam, which can be obtained by phase tapering. The first mode is a conventional stripmap mode with a PRF much lower than the nominal Doppler bandwidth, allowing for the imaging of a large swath, because the ships’ azimuth ambiguities can be recognized as they appear at known positions. The second mode exploits a continuous variation of the pulse repetition interval, with a mean PRF greater than the nominal Doppler bandwidth as the range ambiguities of the ships are smeared and are unlikely to determine false alarms. Both modes are thought to operate in open sea surveillance, monitoring Exclusive Economic Zones or international waters. Examples of implementation of both modes for TerraSAR-X show that ground swaths of 120 km or 240 km can be mapped with 2 m2 resolution, ensuring outstanding detection performance even for small ships. The importance of resolution over noise and ambiguity level was highlighted by a comparison with ScanSAR modes that image comparable swaths with better noise and ambiguity levels but coarser resolutions.

Comparison of Stacked Sentinel‐3 A&B and AltiKa Repeat Cycle Data

AbstractSentinel‐3 A&B radar altimeters yield sea surface height measurements in both a high‐precision Synthetic Aperture Radar Mode (SARM), and a Pseudo‐Low Resolution Mode (PLRM). We stacked repeat cycles from both missions and in both modes to compare their resolution of small seamounts. Stacking entailed removing non‐geoidal heights and height errors, testing for consecutive measurements over ocean, aligning to common locations at 1 km intervals along a synthetic track, and forming a median height profile. These profiles are available from the National Centers for Environmental Information (NCEI) data repository. Global maps show that, over the oceans, the median height is usually derived from more than 49 cycles, and the typical error in an individual PLRM measurement is approximately 1.9 times greater than an individual SARM measurement. We applied a seamount detection bandpass filter to the median profiles and compared their spectral resolution to that of the Satellite for ARgos and AltiKa (SARAL) AltiKa mission. Small seamounts are similarly resolved by Sentinel‐3 A&B SARM data and by the SARAL/AltiKa data.

Development of a New Tropical Cyclone Strip Segment Retrieval Model for C-Band Cross-Polarized SAR Data

Compared with co-polarized (HH/VV) normalized radar cross-section (NRCS) backscattered from the sea surface, there is no saturation phenomenon in cross-polarized (HV/VH) NRCS when wind speed is greater than about 20 m/s, so cross-polarized synthetic aperture radar (SAR) images can be used for high wind speed monitoring. In this work, a new geophysical model function (GMF) is proposed to describe the relation of the C-band cross-polarized NRCS with wind speed and radar incidence angle. Here, sixteen ScanSAR wide mode SAR images acquired by RADARSAT-2 (RS-2) under tropical cyclone (TC) conditions and the matching wind speed data from the European Centre for Medium-Range Weather Forecasts (ECMWF) and the Stepped-Frequency Microwave Radiometer (SFMR) are collected and divided into datasets A and B. Dataset A is used for analyzing the effects of the wind field and radar incidence angle on the reference noise-removed cross-polarized NRCS, and for proposing the new GMF for each sub-swath of the SAR images, while dataset B is used to retrieve wind speed and evaluate the validity of the new GMF. The comparisons between the wind speeds retrieved by the new GMF and the collocated ECMWF and SFMR data demonstrate the excellent performance of the new GMF for wind speed retrieval. To analyze the universality of the new GMF, wind speed retrievals based on 32 Sentinel-1A/B (S-1A/B) extra-wide-swath (EW) mode images acquired under TC conditions are also compared with the collocated wind speeds measured by the Soil Moisture Active Passive (SMAP) radiometer, and the retrieved wind speeds have RMSE of 3.667 m/s and a bias of 2.767 m/s. The successful applications in high wind speed retrieval of different tropical cyclones again supports the availability of the new GMF.

Variable-Resolution SAR Imaging Mode With the Principle of Maximum Mutual Information

A generalized synthetic aperture radar (SAR) modality of operation named variable-resolution (VR) SAR is proposed, which explores the diversity of antenna patterns and inhomogeneity of pulse repetition frequencies (PRFs) for adaptive imaging. Based on the relationship between the azimuth resolution and the corresponding integration angle, it uses dynamic beam patterns along the trajectory to illuminate different regions. We formulate the optimization problem of VR SAR based on the principle of maximum mutual information. First, the information content of a specific scene is defined by modeling its distributed scattering as a stochastic process, and the mutual information between scenes and the observed SAR image can be derived. Then, we construct an optimization problem to maximize the mutual information by solving for the optimal beam manipulation scheme of the VR SAR mode. Further optimization of PRF is conducted to obtain a relatively larger swath width and smaller data volume by compromising the resolution of some regions with less information while ensuring there are no azimuth ambiguities. The potential advantages of VR mode are: 1) it simultaneously provides higher resolution for the high-information regions and a larger imaging area than would otherwise be possible in strip map and spotlight SAR modes and 2) it optimizes the efficiency of data acquisition while extracts as much information from scenes as possible. A mathematical model of VR SAR mode with the principle of maximum mutual information is established, and the feasibility and merits of the method are demonstrated through a series of simulations and an equivalent experiment using RADARSAT-1 raw data.

Study on Airborne Near-Nadir TOPS SAR Imaging With Attitude Angle Error

Combined with terrain observation by progressive scans (TOPS) synthetic aperture radar (SAR), near-nadir SAR (N-SAR) system has great potential for the surface water and ocean topography (SWOT) observation. However, one practical problem of the airborne N-SAR is the non-ideal attitude angle caused by the environment. Normally, the influence of attitude angle error can be considered as a constant squint angle of the system. However, in fact, for the near-nadir SAR system with TOPS SAR mode, the attitude angle error will cause a non-ideal 2-dimensional space-variant Doppler centroid for the receiving data and cause the traditional imaging algorithm failure. To deal with such problems, an imaging algorithm with attitude angle estimation for the near-nadir TOPS SAR system is proposed in this paper. Firstly, the influence of attitude angle error and the signal properties are analyzed. Secondly, based on the analysis, an attitude angle estimate algorithm (AAE), utilizing the nonlinear least square method (NLSM) and minimum entropy criterion, is proposed. Then, based on the estimated altitude angle, without data blocking, a full data imaging algorithm (FDA) is proposed. Its main idea is to obtain an un-ambiguous azimuth spectrum and design an appropriate range-variant azimuth filter through frequency chirp scaling (FCS). The numerical simulations and real data processing demonstrate that the proposed algorithm has good performance on attitude angle error estimation and well-focused image obtaining.

Design and Performance Analysis of Sparse TOPS SAR Mode

Terrain observation by progressive scans (TOPS) is a novel and promising wide-swath synthetic aperture radar (SAR) imaging mode, which overcomes the scalloping effect existing in ScanSAR. Traditional imaging algorithms are computationally efficient in raw data processing of TOPS, but the problems from clutter and sidelobes suppression have not been effectively solved. Sparse SAR imaging not only effectively solves these problems, but also has great potential in improving system performance, <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">e.g.</i> , lower requirement of pulse repetition frequency (PRF), higher swath coverage, less data amount, and lower system complexity. Therefore, this paper proposes a novel sparse TOPS SAR imaging mode. The proposed mode combines advantages of sparse imaging system and TOPS mode to achieve high-quality and wide-swath SAR imaging. In this mode, we first design the beam position by timing diagram. Then the basic parameters of the mode are calculated according to the radar equation, and the properties such as grating lobes are analyzed. Finally, an <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$L_{2,1}$</tex-math></inline-formula> -norm regularization based sparse TOPS SAR imaging algorithm is introduced to achieve the high-quality sparse scene recovery. Experimental results show that compared with conventional TOPS imaging mode, the proposed mode can obtain wide swath with lower PRF and effectively solve the effect on distributed target ambiguity ratio (DTAR). Compared with matched filtering (MF) based TOPS imaging algorithm, the sparse method can achieve unambiguous reconstruction of the considered scene from down-sampled data, and obtain the image with less artifacts.

A Sparse Imaging Method for Frequency Agile SAR

Frequency agility increases the difficulty of jammers to predict and estimate the carrier frequency and, thus, improves the radar electronic counter-countermeasures (ECCM) performance. In this article, frequency agility is introduced into synthetic aperture radar (SAR). The characteristic of the Doppler history of frequency-agile SAR (FASAR) is analyzed, which shows that the azimuth compression could not be achieved by the classic imaging algorithms. In order to reconstruct the images of interested targets, a three-channel sparse imaging method is proposed based on approximated observation model by using the echo data of different carrier frequencies. By deriving the equivalent observation model, it is concluded that the reconstruction performance can be enhanced by improving the coherence of match filter imaging results in different channels. The image characteristic of different channels in FASAR is analyzed based on the chirp scaling imaging operator. A phase compensation method is then proposed to improve the coherence of images of interested targets in different channels. Specifically, the SAR mode of random frequency agility is proposed to improve the reconstruction performance. Finally, simulations are carried out to demonstrate the effectiveness of imaging methods and ECCM performance. Theoretical analysis and simulation results demonstrate that images generated in random FASAR have better performance than those in stepped FASAR. By performing the phase compensation, the reconstruction performance of small targets can be significantly improved.

Measuring Ocean Surface Current in the Kuroshio Region Using Gaofen-3 SAR Data

The Kuroshio is the strongest warm current in the western North Pacific, which plays a crucial role in climate and human activities. In terms of this, the accurate acquisition of ocean surface current velocity and direction in the Kuroshio region is of great research value. Gaofen-3 synthetic aperture radar (SAR) provides data support for the study of ocean surface current measurements in the Kuroshio region, but no relevant experimental result has been published yet. In this paper, four available stripmap mode SARs’ data acquired by Gaofen-3 in the Kuroshio region are used for measuring the ocean surface current field. In general, the Doppler centroid anomaly (DCA) estimation is a common method to infer ocean surface currents from single-antenna stripmap data, but only the radial velocity component can be retrieved. In order to measure current vectors, a novel method combining the sub-aperture processing and the least squares (LS) technology is suggested and demonstrated by applying to the Gaofen-3 SAR data processing. The experiment’s results agree well with model-derived ocean current data, indicating that the Gaofen-3 SAR has the capability to accurately retrieve the ocean surface current field in the Kuroshio region and motivate further research by providing more data.

Precise inland surface altimetry (PISA) with nadir specular echoes from Sentinel-3: Algorithm and performance assessment

In the recent years satellite radar altimetry has evolved from pulse-limited low resolution mode (LRM) to a synthetic aperture radar (SAR) high resolution mode. The SAR mode focusses and coherently sums all radar return echoes within the 2-s time window the target surface area is in the antenna beam. In principle the SAR processing improves along-track resolution. Land contamination has been a major concern for inland waters altimetry and SAR can reduce land interference. This paper shows that the physics of specular echoes from smooth inland waters leads to a very different approach which we call precise inland surface altimetry (PISA). PISA uses only echoes within the specular “flash” period, which is approximately the time the satellite nadir crosses over the water body. The processing is four orders of magnitude less than SAR. Land interference is negligible because specular water echoes are usually >50 dB greater than land. Sentinel-3 SRAL dataset on the salar de Uyuni (Bolivia) is used to evaluate PISA ranging precision. During inundation (wet months), echoes are at the theoretical maximum radar cross section (RCS), σ = 129 dBsm, and ranging precision is ~1 mm. In dry months the echoes are quasi-specular, with σ = 70–100 dBsm, and ranging precision is ~1 cm. The precision assessment is made with variate-differences, with pass-to-pass repeatability, and by comparison with GPS measurements. In addition to the salar de Uyuni analysis we gathered σ statistics on five millions Sentinel-3 SRAL Ku-band altimeter bursts (one burst = 64 contiguous echoes) from 52 passes of Sentinel-3A track 167 over South America. We illustrate specular and quasi-specular waters on lakes, a river, and a fjord. Ranging precision is similar to Uyuni, in the 1 mm-1 cm range. Water surface slopes of 1–3 cm/km are detected. We propose a simple rule-set to distinguish specular waveforms (σ >100 dBsm, sidelobes (with Hamming window) of −37 dB or lower) and quasi-specular (σ >70 dBsm, sidelobes lower than −20 dB), and non-specular (sidelobes> − 20 dB). PISA is appropriate to specular and quasi-specular echoes.

On Autonomous Reconfiguration of SAR Satellite Formation Flight With Continuous Control

Satellites clusters for Earth observation purposes entail precise orbit monitoring and control to satisfy application needs efficiently. Fast technological progress in GNSS receivers, intersatellite communications/vision links, and propulsion technologies have inspired and fostered autonomous orbit determination and control techniques, allowing more efficient ground segment operations. Moreover, new distributed satellite missions have been enabled by autonomous formation flying, with unprecedented Earth observation potential. These missions may adopt varying observational modes associated with different relative orbital configurations and also transit among these modes as required by mission control. In this article, we consider a hypothetic distributed synthetic aperture radar (SAR) mission with a main SAR illuminator, as CONAE's SAOCOM 1 satellites, and one or more companions able to adopt different bistatic SAR geometries, enabling interferometry, tomography, or specular acquisition. To approach this problem, we formulate a basic task for any actively controlled companion satellite (deputy satellite) consisting of following a reference maneuver relative to the chief satellite orbit. This task is performed by means of a feedback control law based on newly introduced relative orbital elements (ROEs) and suitable to continuous actuators (e.g., electric propulsion) with bounded thrust. As a main result, we prove the asymptotic stability of the maneuver orbit tracking task for low Earth, nonequatorial, and near-circular chief orbits. This required a reformulation of the relative orbit tracking problem and the associated ROEs. A control allocation along the orbit is also proposed to reduce the propellant consumption and the transient time between SAR modes. The theoretical results are validated with simulated controlled transitions between different acquisition modes.

Motion bias analysis of sea surface height measurement by near-nadir interferometric Synthetic Aperture Radar (SAR) and its compensation method research

ABSTRACT High-precision observation of ocean surface topography is of great significance in studying the ocean mesoscale and sub-mesoscale processes. Spaceborne near-nadir interferometric synthetic aperture radar (InSAR) is capable of measuring sea surface height with centimetre-level accuracy and over a wide swath. It differs from terrestrial height measurement because the constant movement of the dynamic ocean surface creates biases in synthetic aperture radar imaging and leads to height measurement inaccuracy. This study investigates the bias due to the motion of ocean surface waves and establishes a theoretical model of the height measurement motion bias related to the ocean wave spectrums and InSAR system parameters. The motion bias model was simulated in different SAR modes, including Stripmap and Terrain Observation by Progressive Scans (TOPS) modes in various oceanic states. The results showed that the motion biases are smaller in Stripmap mode than TOPS mode under the same oceanic conditions. By adopting the total zero steering technology in Stripmap mode, the motion bias can be significantly decreased. In the same oceanic state, the motion bias increases with increasing angle of incidence. In the TOPS mode, the Doppler centroid frequency of the antenna’s signal changes linearly with the azimuth time, and thus, the biases change significantly in the azimuth direction. The motion bias model is validated by the interferometric full-link experimental simulation and the results are consistent with the theoretical values. This study provides a compensation method with millimetre level accuracy to compensate for the height measurement bias caused by sea surface motion. The theoretical derivation of motion bias models and simulation results provide feasible suggestions for the design of InSAR systems and bias compensation for sea surface height measurement.

Extreme Waves in the Agulhas Current Region Inferred from SAR Wave Spectra and the SWAN Model

The influence of the Agulhas Current on the wave field is investigated. The study is conducted by performing high resolution spectral wave model simulations with and without ocean currents. The validation of the numerical simulations is performed for the Significant Wave Height (Hs) using all possible satellite altimetry data available in the study region for a winter period of 2018. Wave spectra and extreme waves parameters are examined in places where waves and current are aligned in the Agulhas Current. Sentinel-1 (S1) wave mode Synthetic Aperture Radar (SAR) spectra are used to estimate the composites of the Hs and BFI (Benjamin–Feir Index). SAR computed BFI and Hs were compared with the respective composites obtained from the Simulating Waves Nearshore (SWAN) model. From the Hs composites using SAR data and modeled data, it can be concluded that the Hs maxima values are distributed in the Agulhas Current Retroflection (ACR) and also in the southern limit of the domain that is affected by the strong circumpolar winds around Antarctic. In addition, the BFI composites exhibit the highest values in the ACR and some few values are observed in the southern border as occurred with the Hs. The results of this study indicate that there is direct correlation between the Agulhas Current strength, the Hs and the BFI. It was found that the modeled directional wave spectra are broadened when the ocean current is considered in the simulation. The analysis of the modeled wave spectra is performed over eddies, rings and meanders in the Agulhas Current region. The transformation of the wave spectra due to current refraction is discussed based on the numerical simulations. The effect of the Agulhas Current on the spectral shape is explored. The spectral wave energy grows when the wave and the current are aligned, resulting in peaked, elongated and widened spectra. A decrease of the peak period was observed before the occurrence of maximum values of BFI, which characterize abnormal sea states.

Intrapulse Azimuth Frequency Scanning-Based 2-D Scanning SAR for HRWS Imaging

In this article, a novel 2-D scanning synthetic aperture radar mode for high-resolution and wide-swath imaging is introduced. Instead of the interpulse progressive azimuth beam scanning used in Terrain Observation by Progressive Scans (TOPS) mode, the intrapulse continuous azimuth frequency scanning is employed in this mode. The same azimuth resolution as the multichannel TOPS mode can be obtained through this mode in the case of single channel transmitting and receiving. And the wide-swath imaging in range is still achieved through the cyclically elevation beam scanning from burst to burst. Moreover, the antenna aperture can be fully exploited for transmitting in this mode. Therefore, it will outperform the multichannel TOPS mode especially in the case of active array antenna. The signal model of this mode is derived. Based on the analysis of the characteristics of echo spectrum, the design criteria for this mode are developed, followed by a design example. Finally, an imaging algorithm for this mode is presented. Theoretical analysis and numerical simulations verify the effectiveness of the proposed design criteria and imaging algorithm.

High-performance altimeter Doppler processing for measuring sea level height under varying sea state conditions

This paper describes an innovative method for processing nadir altimeter data acquired in Synthetic Aperture Radar (SAR) mode, enhancing the system performances over open ocean. Similarly to the current SAR data processing scheme, the so-called LR-RMC (Low Resolution with Range Migration Correction) method, originally designed by Phalippou and Demeester (2011), includes Doppler beam forming, Doppler shift correction and range correction. In LR-RMC, however, an alternative and less complex averaging (stacking) operation is used so that all the Doppler beams produced in a radar cycle (4 bursts of 64 beams for the open-burst Sentinel-3-mode altimeter) are incoherently combined to form a multi-beam echo. In that manner, contrarily to the narrow-band SAR technique, the LR-RMC processing enlarges the effective footprint to average out the effects of surface waves and particularly those from small sub-mesoscale structures (<1 km) that are known to impact SAR-mode performances. On the other hand, the number of averaged beams is as high as in current SAR-mode processing, thus providing a noise reduction at least equally good. The LR-RMC method has the added benefit of reducing the incoherent integration time with respect to the SAR-mode processing (50 ms compared to 2.5 s) limiting possible surface movement effects. By processing one year of Sentinel-3A SRAL SAR-mode data using the LR-RMC method, it is shown that the swell impact on the SAR altimeter performances is totally removed and that an improvement of 10–50% is obtained in the measurement noise of the sea surface height and significant wave height with respect to SAR mode. Additionally, observational capabilities over the middle scales are enhanced potentially allowing the ocean mesoscale features to be retrieved and observations assimilated more usefully in ocean models.

Research on the Parameter Design Method and System Simulation of Multimode Microwave Remote Sensors Operating in Scatterometer Modes

Multimode microwave remote sensors are a new type of radar system that operates in SAR (synthetic aperture radar), scatterometer, altimeter, and spectrometer modes in a time-sharing manner according to the current task scheduled on small satellites. High flexibility through mode switching is the outstanding advantage of this new microwave remote sensor. Two or more small satellites operating in different operation modes can be networked to perform observations synchronously to provide excellent remote sensing performance. This paper focuses on a method to determine the radar parameters of the scatterometer mode since the frequency band and the platform height of this new of kind sensor are determined according to the requirement of the SAR mode, and their values are evidently different from the values of current scatterometers in orbit. The proposed method systematically presents the complete steps and related formulae of the radar parameter design of scatterometers and determines the signal bandwidth by optimization. A system simulation method of the scatterometer mode is further studied to determine the wind field inversion error and thus evaluate the rationality of the parameter design results. In contrast to the existing methods, which directly add noise to the backscatter coefficients, our method simulates the noisy echo of the scatterometer and then retrieves the wind field by estimated backscatter coefficients from the noisy echo. The performed simulation shows that, by using the designed system parameters, the multimode microwave remote sensor obtains wind field inversion accuracy, resolution and swath width comparable to those of the HY-2 satellite and the QuikSCAT satellite.