Wave direction measured by four different systems

During a March 1977 experiment, four systems were used to provide wave-direction information offshore of Mission Beach, CA: a synthetic aperature radar (SAR) carried aboard a NASA CV990 aircraft, a coastal imaging radar, a pressure-gauge array offshore, and aerial photography aboard two aircraft. The coastal radar, aerial photographs, and SAR provided wave images. From the coastal radar images and the aerial photographs, the direction and length of the principal wavetrains were measured by a manual analysis. The SAR images were also processed using an FFT to give two-dimensional wave spectra. The array at the Naval Ocean Systems Center (NOSC) tower was used to provide directional wave spectra. Scatter diagrams are presented, which intercompare the measurements from these four systems. In addition, radar image spectral information is compared with the array spectra. The intercomparison of the data from these four systems shows good agreement among the imaging systems. Between the imaging systems and the pressure array there is agreement for the most prominent wavetrains and disagreement for several cases where multiple wavetrains from different directions but with similar periods are present.     

A semiempirical algorithm for SAR wave height retrieval and its validation using Envisat ASAR wave mode data

Many synthetic aperture radar(SAR) wave height retrieval algorithms have been developed.However,the wave height retrievals from most existing methods either depend on other input as the first guess or are restricted to the long wave regime.A semiempirical algorithm is presented,which has the objective to estimate the wave height from SAR imagery without any prior knowledge.The proposed novel algorithm was developed based on the theoretical SAR ocean wave imaging mechanism and the empirical relation between two types of wave period.The dependency of the proposed model on radar incident and wave direction was analyzed.For Envisat advanced synthetic aperture radar(ASAR) wave mode data,the model can be reduced to the simple form with two input parameters,i.e.,the cutoff wavelength and peak wavelength of ocean wave,which can be retrieved from SAR imagery without any prior knowledge of wind or wave.Using Envisat ASAR wave mode data and the collocated buoy measurements from NDBC,the semiempirical algorithm is validated and compared with the Envisat ASAR level 2 products.The root-mean-square-error(RMSE) and scatter index(SI) in respect to the in situ measurements are 0.52 m and 19% respectively.Validation results indicate that,for Envisat ASAR wave mode data,the proposed method works well.     

对ENVISAT ASAR level2算法固有误差的分析

欧洲空间局的ENVISAT ASAR level 2算法是从合成孔径雷达(SAR)单视复图像反演涌浪方向谱的算法.该算法假设双峰海浪谱的SAR图像交叉谱是涌浪的图像交叉谱和风浪的图像交叉谱之和.实际上双峰海浪谱的SAR图像交叉谱中还有一个混合项,正是该混合项导致ENVI-SAT ASAR level 2算法有固有误差.利用遥感仿真的方法分析了不同海况条件下该算法的这一固有误差,结果表明,只有在有效波高较小、或风浪的成分较少、或双峰海浪的传播方向较靠近SAR距离向、或波长较长时固有误差才较小,ENVISAT ASAR level 2算法对海浪谱的反演才较为适用.     

Ocean wave parameters retrieved directly from compact polarimetric SAR data

We aim to directly invert wave parameters by using the data of a compact polarimetric synthetic aperture radar(CP SAR) and validate the effectiveness of ocean wave parameter retrieval from the circular transmit/linear receive mode and π/4 compact polarimetric mode. Relevant data from the RADARSAT-2 fully polarimetric SAR on the C-band were used to obtain the compact polarimetric SAR images, and a polarimetric SAR wave retrieval algorithm was used to verify the sea surface wave measurements. Usin...     

Synthetic aperture radar imaging of ocean waves during the marineland experiment

X- andL-band simultaneously obtained synthetic aperture radar (SAR) data of ocean gravity waves collected during the Marineland Experiment were analyzed using wave contrast measurements. The Marineland data collected in 1975 represents a unique historical data set for testing still-evolving theoretical models of the SAR ocean wave imaging process. The wave contrast measurements referred to are direct measurements of the backscatter variation between wave crests and troughs. These modulation depth measurements, which are indicators of wave detectability, were made as a function of: a) the settings used in processing the SAR signal histories to partially account for wave motion; b) wave propagation direction with respect to radar look direction for bothX- andL-band SAR data; c) SAR resolution; and d) number of coherent looks. The contrast measurements indicated that ocean waves imaged by a SAR are most discernible whenX-band frequency is used (as compared toL-band), and when the ocean waves are traveling in the range direction. Ocean waves can be detected by bothX- andL-band SAR, provided that the radar surface resolution is small compared to the ocean wavelength (at least 1/4 of the ocean wavelength is indicated by this work). Finally, wave detection withL-band SAR can be improved by adjusting the focal distance and rotation of the cylindrical telescope in the SAR optical processor to account for wave motion. The latter adjustments are found to be proportional to a value that is near the wave phase velocity.     

基于SVM回归模型的SAR图像有效波高估测

A new method for estimating significant wave height(SWH) from advanced synthetic aperture radar(ASAR) wave mode data based on a support vector machine(SVM) regression model is presented. The model is established based on a nonlinear relationship between σ0, the variance of the normalized SAR image, SAR image spectrum spectral decomposition parameters and ocean wave SWH. The feature parameters of the SAR images are the input parameters of the SVM regression model, and the SWH provided by the European Centre for Medium-range Weather Forecasts(ECMWF) is the output parameter. On the basis of ASAR matching data set, a particle swarm optimization(PSO) algorithm is used to optimize the input kernel parameters of the SVM regression model and to establish the SVM model. The SWH estimation results yielded by this model are compared with the ECMWF reanalysis data and the buoy data. The RMSE values of the SWH are 0.34 and 0.48 m, and the correlation coefficient is 0.94 and 0.81, respectively. The results show that the SVM regression model is an effective method for estimating the SWH from the SAR data. The advantage of this model is that SAR data may serve as an independent data source for retrieving the SWH, which can avoid the complicated solution process associated with wave spectra.     

Modification of SAR spectra associated with surface wind fields in the sea off the Kii Peninsula: A case study

Using surface wave parameters and a high-resolution surface wind field derived from Synthetic Aperture Radar (SAR) image mode data, we have investigated the spatial modification of SAR spectra. We found a surface wind front, formed by sheltering effect of the Kii Mountains, separating high and low wind-speed regions in a sea area of an European Remote-Sensing Satellite (ERS) SAR image off the Kii Peninsula. A swell system propagating westward dominates in the whole sea area covered by the SAR image. The wavelength retrieved from the SAR spectra in the sheltered (non-sheltered) region is longer (shorter). Since the distributions of surface wave parameters and surface wind speed are so well correlated, it can be considered that the SAR spectra are modified differently by the sheltered/non-sheltered surface winds. In order to examine the phenomena observed on the SAR image we have estimated the wind-wave SAR spectrum using the SAR surface winds, a wind-wave spectrum model and a SAR wave imaging model. We assume that the SAR spectrum related to the swell is homogeneous in the area imaged by SAR, and that the SAR spectrum of the wind-wave components causes the observed SAR spectra modification. Differences between the observed SAR spectra and the estimated SAR spectra in the sheltered and non-sheltered regions agree well with each other. In the present case, it can be concluded that the observed SAR spectra can be regarded as a linear combination of the wind-wave SAR spectra and the swell SAR spectra.     

Satellite-based RAR performance simulation for measuring directional ocean wave spectrum based on SAR inversion spectrum

Some missions have been carried out to measure wave directional spectrum by synthetic aperture radar (SAR) and airborne real aperture radar (RAR) at a low incidence. Both them have their own advantages and limitations. Scientists hope that SAR and satellite-based RAR can complement each other for the research on wave properties in the future. For this study, the authors aim to simulate the satellite-based RAR system to validate performance for measuring the directional wave spectrum. The principal measurements are introduced and the simulation methods based on the one developed by Hauser are adopted and slightly modified. To enhance the authenticity of input spectrum and the wave spectrum measuring consistency for SAR and satellite-based RAR, the wave height spectrum inversed from Envisat ASAR data by cross spectrum technology is used as the input spectrum of the simulation system. In the process of simulation, the sea surface, backscattering signal, modulation spectrum and the estimated wave height spectrum are simulated in each look direction. Directional wave spectrum are measured based on the simulated observations from 0° to 360°. From the estimated wave spectrum, it has an 180° ambiguity like SAR, but it has no special high wave number cut off in all the direction. Finally, the estimated spectrum is compared with the input one in terms of the dominant wave wavelength, direction and SWH and the results are promising. The simulation shows that satellite-based RAR should be capable of measuring the directional wave properties. Moreover, it indicates satellite-based RAR basically can measure waves that SAR can measure.     

台风中降雨对中国高分3号合成孔径雷达观测信号的影响

Gaofen-3(GF-3), a Chinese civil synthetic aperture radar(SAR) at C-band, has operated since August 2016.Remarkably, several typhoons have been captured by GF-3 around the China Seas over its last two-year mission.In this study, six images acquired in Global Observation(GLO) and Wide ScanSAR(WSC) modes at verticalvertical(VV) polarization channel are discussed. This work focuses on investigating the observation of rainfall using GF-3 SAR. These images were collocated with winds from the European Centre for Medium-Range Weather Forecasts(ECMWF), significant wave height simulated from the WAVEWATCH-III(WW3) model, sea surface currents from climate forecast system version 2(CFSv2) of the National Centers for Environmental Prediction(NCEP) and rain rate data from the Tropical Rainfall Measuring Mission(TRMM) satellite. Sea surface roughness,was compared with the normalized radar cross section(NRCS) from SAR observations, and indicated a 0.8 correlation(COR). We analyzed the dependences of the difference between model-simulated NRCS and SARmeasured NRCS on the TRMM rain rate and WW3-simulated significant wave height. It was found that the effects of rain on SAR damps the radar signal at incidence angles ranging from 15° to 30°, while it enhances the radar signal at incidence angles ranging from 30° to 45° and incidence angles smaller than 10°. This behavior is consistent with previous studies and an algorithm for rain rate retrieval is anticipated for GF-3 SAR.     

Retrieval of surface wave parameters from sar images and their validation in the coastal seas around Japan

We have developed a scheme to retrieve surface wave parameters (wave height and wave propagation direction) from European Remote-Sensing Satellite (ERS) Synthetic Aperture Radar (SAR) image mode data in coastal seas around Japanese coastlines. SAR spectra are converted to surface wave spectra of swell-dominated or wind-wave dominated cases. The SAR spectrum and SAR-derived wind speed are used to derive the surface wave spectrum. The wind-wave dominated case and swell-dominated case are differentiated by a wind speed of 6 m/s, and processed in different ways because of their different degree of nonlinearity. It is indicated that the cutoff wavelength for retrieval of the wind-wave dominated spectrum is proportional to the root of significant wave height, which is consistent with the results of previous studies. We generated 66 match-ups using the SAR sub-images and the in-situ surface wave parameters, which were measured by wave gauges installed in near-shore seas. Among them, there are 57 swell-dominated cases, and 9 wind-wave dominated cases. The significant wave heights derived from SAR and from in-situ observation agree with the bias of 0.09 m, the standard deviation of 0.61 m and the correlation coefficient of 0.78. The averaged absolute deviation of wave propagation directions is 18.4°, and the trend of the agreement does not depend on the wave height. These results demonstrate that the SAR surface wave spectrum retrieved by the present system can be used to observe the surface wave field in the coastal seas around Japan.     

浅海水下地形的SAR遥感仿真研究

结合连续性方程和布拉格后向散射模型,在准一维简化浅海水下地形情况下,建立了浅海水下地形SAR海面相对后向散射强度仿真模型,将浅海水下地形区域的SAR海面后向散射强度的相对变化与大尺度背景流场、海面风场和雷达系统参数等联系起来.海上实验和研究结果表明,浅海水下地形的SAR成像主要由通过受水下地形影响的海表层流场对海表面风引起的微尺度波的水动力调制而获取浅海水下地形信息,其中潮流与水下地形的相互作用过程改变海表层流场,变化的海表层流与海表面微尺度波之间的相互作用改变海表面波的空间分布,雷达波与海表面波之间的相互作用决定雷达海面后向散射强度.因此SAR图像中浅海水下地形或水深信息量的多少不仅与海表层流场和海面风速有关,而且与雷达工作波段、雷达波束入射角和极化方式也密切相关.认为由水下地形变化引起的缓慢变化的表层流场中海表面定常微尺度波谱能量密度的变化满足波作用量谱平衡方程;而在波数空间中,海表面微尺度波谱的成长过程也可以用波数谱平衡方程描述,在此基础上,得出了海表面波高频谱(毛细-重力波)形式的解析表达式.众所周知,浅海水下地形信息是由于水下地形影响下SAR海面后向散射强度与背景海面后向散射强度的相对差异而在SAR图像上的呈现,从而在建立浅海水下地形SAR海面相对后向散射强度仿真模型的基础上,仿真计算了浅海水下地形SAR海面相对后向散射强度相对于海表层流场、海面风场等海况参数和SAR工作波段、SAR波束入射角、极化方式等雷达系统参数的数值仿真结果,分析得到了有关浅海水下地形SAR海面相对后向散射强度的特征和SAR浅海水下地形遥感的最佳海况参数与最佳雷达系统参数,为研究和开展SAR浅海水下地形遥感研究提供了有价值的参考.     

基于理论的气旋条件下双极化C波段合成孔径雷达波参数检测

Theoretical-based ocean wave retrieval algorithms are applied by inverting a synthetic aperture radar(SAR)intensity spectrum into a wave spectrum, that has been developed based on a SAR wave mapping mechanism. In our previous studies, it was shown that the wave retrieval algorithm, named the parameterized first-guess spectrum method(PFSM), works for C-band and X-band SAR at low to moderate sea states. In this work, we investigate the performance of the PFSM algorithm when it is applied for dual-polarization c-band sentinel-1(S-1) SAR acquired in extra wide-swath(EW) and interferometric wide-swath(IW) mode under cyclonic conditions.Strong winds are retrieved from six vertical-horizontal(VH) polarization S-1 SAR images using the c-band crosspolarization coupled-parameters ocean(C-3 PO) model and then wave parameters are obtained from the image at the vertical-vertical(VV) polarization channel. significant wave height(SWH) and mean wave period(MWP) are compared with simulations from the WAVEWATCH-III(WW3) model. The validation shows a 0.69 m root mean square error(RMSE) of SWH with a –0.01 m bias and a 0.62 s RMSE of MWP with a –0.17 s bias. Although the PFSM algorithm relies on a good quality SAR spectrum, this study confirms the applicability for wave retrieval from an S-1 SAR image. Moreover, it is found that the retrieved results have less accuracy on the right sector of cyclone eyes where swell directly affects strong wind-sea, while the PFSM algorithm works well on the left and rear sectors of cyclone eyes where the interaction of wind-sea and swell is relatively poor.     

Signature extraction from mesoscale surface patterns observed onsynthetic aperture radar imagery

Two techniques for extracting internal wave signature from airborne synthetic aperture radar (SAR) imagery are presented. The first technique involves the extraction of a single-scan signature and appropriate for the validation of theoretical models which utilize sea truth from a limited area as input. The second technique involves creating a signature by averaging the results from a number of single scans within the same scene and is appropriate for trend analyses. The utility of both techniques is illustrated using internal wave signatures present in a multifrequency, airborne SAR data set     

Atmospheric frontal gravity waves observed in satellite SAR images of the Bohai Sea and Huanghai Sea

In the satellite synthetic aperture radar (SAR) images of the Bohai Sea and Huanghai Sea, the authors observe sea surface imprints of wave-like patterns with an average wavelength of 3.8 km. Comparing SAR observations with sea surface wind fields and surface weather maps, the authors find that the occurrence of the wave-like phenomena is associated with the passing of atmospheric front. The authors define the waves as atmospheric frontal gravity waves. The dynamical parameters of the wave packets are derived from statistics of 9 satellite SAR images obtained from 2002 to 2008. A two-dimensional linear physical wave model is used to analyze the generation mechanism of the waves. The atmospheric frontal wave induced wind variation across the frontal wave packet is compared with wind retrievals from the SAR images. The CMOD-5 (C-band scatterometer ocean geophysical model function) is used for SAR wind retrievals VV (transmitted vertical and received vertical) for ENVISAT and HH (transmitted horizontally and received horizontally) for RADARSAT-1. A reasonable agreement between the analytical solution and the SAR observation is reached. This new SAR frontal wave observation adds to the school of SAR observations of sea surface imprints of AGWs including island lee waves, coastal lee waves, and upstream Atmospheric Gravity Waves (AGW).     

A fundamental model and efficient inference for SAR ocean imagery

Employing a synthetic aperature radar (SAR) imaging model based on fundamental models of nonlinear hydrodynamics, electromagnetic scattering from a two-scale surface, and SAR imaging of a time-variant scene, the optimal (minimum mean-square error) estimates of the parameters of a sinusoidal, long gravity wave, and the short gravity wave ensemble are found in an efficient recursive form and their performance evaluated, generally by numerical simulation, in a one-dimensional stationary version. An application is made to Seasat-SAR complex imagery.     

Directional spectrum analysis and statistics obtained from ERS-1 SAR wave images

This work examines ERS-1 (the first European Remote Sensing Satellite) SAR (Synthetic Aperture Radar) water surface wave images over Hualien of Taiwan, indicating that the variation of SAR signals in space domain is similar to in situ wave data's in time domain. Some statistical properties of SAR data are investigated. The Rayleigh distribution function closely corresponds with the histogram of wave heights, but the Gaussian one cannot for water surface displacements. Evidence reveals that SAR wave signals do not respond well to actual ocean waves effectively. As wave spectral analysis of available SAR data reveals, the appropriate sample size of SAR wave image, sampling average, and moving average should be taken carefully to accurately confirm directional power spectra. Moreover, SAR spectra are compared with in situ ones, confirming that peak frequencies correlate well and wave directions approximately agree with each other. Some differences between both spectral shapes remain somewhat unclear and require further study. Nevertheless, in this study, ERS-1 SAR power spectra verified the feasibility of deriving an appropriate dominant wave direction and peak frequency.     

一种基于Curvelet变换的合成孔径雷达海洋内波图像的斑点噪声抑制方法

合成孔径雷达是海洋内波研究中最重要的工具之一。雷达图像中的斑点噪声会严重降低图像的质量,这一问题在处理和分析信号较弱的二模态内波信号和上升型内波信号时极为明显。合成孔径雷达图像中的海洋内孤立波的信号具有明显的尺度性和方向性。同时,curvelet变换作为一种同时具备尺度分辨率和方向分辨率的数学变换,能够对一幅雷达图像在不同尺度、不同方向和不同位置上进行分析。本文给出了一个基于curvelet变换的合成孔径雷达海洋内孤立波图像的斑点噪声抑制方法。该方法可简述为：(1)对一幅合成孔径雷达海洋内孤立波图像进行curvelet变换,获得curvelet系数;(2)分别仅仅保留一个尺度的系数,将其它尺度的系数置为零,利用处理之后的系数分别重建图像,得到仅仅用一个尺度的系数重建的图像;(3)分别计算上一步中得到的图像的均方差,根据波浪理论,图像的方差代表能量,方差越大则能量越大,以此可以确定内波信息集中的尺度;(4)在每个尺度下,分别计算每个方向的curvelet系数矩阵的平均值,以此确定内孤立波信号集中的方向;(5)在上两步工作的基础上,仅仅保留内波信号集中的尺度和方向的系数,而将其它尺度和方向的系数置为0,得到一幅提取主波信息的图像;(6)将上一步得到的提取主波信息的图像加回到原始图像中,从而达到增强波浪信息并抑制斑点噪声的目的。大量的实验验证表明,该方法不仅能有效地压制斑点噪声,而且能有效地增强波浪信号。     

利用一种改进的算法对中国高分三号同极化SAR图像反演的有效波高的验证

Chinese Gaofen-3(GF-3) is the first civilian satellite to carry C-band(5.3 GHz) synthetic aperture radar(SAR).During the period of August 2016 to December 2017, 1 523 GF-3 SAR images acquired in quad-polarization(vertical-vertical(VV), horizontal-horizontal(HH), vertical-horizontal(VH), and horizontal-vertical(HV)) mode were recorded, mostly around China's seas. In our previous study, the root mean square error(RMSE) of significant wave height(SWH) was found to be around 0.58 m when compared with retrieval results from a few GF-3 SAR images in co-polarization(VV and HH) with moored measurements by using an empirical algorithm CSAR_WAVE. We collected a number of sub-scenes from these 1 523 images in the co-polarization channel,which were collocated with wind and SWH data from the European Centre for Medium-Range Weather Forecasts(ECMWF) reanalysis field at a 0.125° grid. Through the collected dataset, an improved empirical wave retrieval algorithm for GF-3 SAR in co-polarization was tuned, herein denoted as CSAR_WAVE2. An additional 92 GF-3 SAR images were implemented in order to validate CSAR_WAVE2 against SWH from altimeter Jason-2, showing an about 0.52 m RMSE of SWH for co-polarization GF-3 SAR. Therefore, we conclude that the proposed empirical algorithm has a good performance for wave retrieval from GF-3 SAR images in co-polarization.     

Accuracy improvement of the radar backscatter simulation from sea surface covered by oil slick using fetch-dependent waveheight spectrum: Comparison with the 2007 <Emphasis Type="Italic">Heibei Spirit</Emphasis> Case in the Yellow Sea

In this paper, results are presented on the comparison of X-band radar backscattering coefficient (RBC) from an oilcovered sea surface that features the Elfouhaily and Durden-Vesecky waveheight spectra. The Durden-Vesecky spectrum applies to a fully-developed sea, while the Elfouhaily spectrum accounts for the fetch of arbitrary length. Using these two waveheight spectra, a one-dimensional random rough surface is simulated by the Monte Carlo method, and the method of moments (MoM) is applied to yield the RBC. Comparison of the results with TerraSAR-X synthetic aperture radar (SAR) data acquired over the coastal waters polluted by the Hebei Spirit oil tanker shows that the Elfouhaily spectrum yields better agreement than the Durden-Vesecky spectrum for the fully-developed sea, and that the fetch-dependent Elfouhaily spectrum improves the agreement with SAR data in comparison with the fetch-independent spectrum for the fully developed sea. A possible application to estimate the amount of spilled oil is also suggested.     

Estimates of ocean wavelength and direction from X-and L-band synthetic aperture radar data collected during the Marineland experiment

Simultaneously obtainedX- andL-band synthetic aperture radar (SAR) data collected during the Marineland Experiment were spectrally analyzed by fast Fourier transform (FFT) techniques to estimate ocean wavelength and direction. An eight-sided flight pattern was flown over the same ocean area in order to study the sensitivity of the spectral estimate on radar look direction. These spectral estimates were compared with in situ wave measurements made by a pitch-and-roll buoy. The comparison revealed that theX-band SAR detected all gravity waves independent of radar look direction, while theL-band SAR detected all range-traveling gravity waves but failed to detect waves in three of four cases in which the waves were traveling within 25° of the azimuth direction. The analysis also indicates that azimuth-traveling waves appear longer and more range-traveling in the SAR imagery than observed by in situ instrumentation. It is postulated that degraded azimuth resolution due to scatterer motion is responsible for these observations.