The impact of rain to observed signal from Chinese Gaofen-3 synthetic aperture radar in typhoons

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.

Evaluation of wave retrieval for Chinese Gaofen-3 synthetic aperture radar

The goal of this study was to investigate the performance of a spectral-transformation wave retrieval algorithm and confirm the accuracy of wave retrieval from C-band Chinese Gaofen-3(GF-3)Synthetic Aperture Radar(SAR)images.More than 200 GF-3 SAR images of the coastal China Sea and the Japan Sea for dates from January to July 2020 were acquired in the Quad-Polarization Strip(QPS)mode.The images had a swath of 30 km and a spatial resolution of 8 m pixel size.They were processed to retrieve Significant Wave Height(SWH),which is simulated from a numerical wave model called Simulating WAves Nearshore(SWAN).The first-guess spectrum is essential to the accuracy of Synthetic Aperture Radar(SAR)wave spectrum retrieval.Therefore,we proposed a wave retrieval scheme combining the theocratic-based Max Planck Institute Algorithm(MPI),a Semi-Parametric Retrieval Algorithm(SPRA),and the Parameterized First-guess Spectrum Method(PFSM),in which a full wave-number spectrum and a non-empirical ocean spectrum proposed by Elfouhaily are applied.The PFSM can be driven using the wind speed without calculating the dominant wave phase speed.Wind speeds were retrieved using a Vertical-Vertical(VV)polarized geophysical model function C-SARMOD2.The proposed algorithm was implemented for all collected SAR images.A comparison of SAR-derived wind speeds with European Center for Medium-Range Weather Forecasts(ECMWF)ERA-5 data showed a 1.95 m/s Root-Mean-Squared Error(RMSE).The comparison of retrieved SWH with SWAN-simulated results demonstrated a 0.47 m RMSE,which is less than the 0.68 m RMSE of SWH when using the PFSM algorithm.

Semi-Empirical Algorithm for Wind Speed Retrieval from Gaofen-3 Quad-Polarization Strip Mode SAR Data

Synthetic aperture radar(SAR)is a suitable tool to obtain reliable wind retrievals with high spatial resolution.The geophysical model function(GMF),which is widely employed for wind speed retrieval from SAR data,describes the relationship between the SAR normalized radar cross-section(NRCS)at the copolarization channel(vertical-vertical and horizontal-horizontal)and a wind vector.SAR-measured NRCS at cross-polarization channels(horizontal-vertical and vertical-horizontal)correlates with wind speed.In this study,a semi-empirical algorithm is presented to retrieve wind speed from the noisy Chinese Gaofen-3(GF-3)SAR data with noise-equivalent sigma zero correction using an empirical function.GF-3 SAR can acquire data in a quad-polarization strip mode,which includes cross-polarization channels.The semi-empirical algorithm is tuned using acquisitions collocated with winds from the European Center for Medium-Range Weather Forecasts.In particular,the proposed algorithm includes the dependences of wind speed and incidence angle on cross-polarized NRCS.The accuracy of SAR-derived wind speed is around 2.10ms−1 root mean square error,which is validated against measurements from the Advanced Scatterometer onboard the Metop-A/B and the buoys from the National Data Buoy Center of the National Oceanic and Atmospheric Administration.The results obtained by the proposed algorithm considering the incidence angle in a GMF are relatively more accurate than those achieved by other algorithms.This work provides an alternative method to generate operational wind products for GF-3 SAR without relying on ancillary data for wind direction.

Evaluation of Wind Retrieval from Co-Polarization Gaofen-3 SAR Imagery Around China Seas

Gaofen-3(GF-3) is the first Chinese space-borne satellite to carry the C-band multi-polarization synthetic aperture radar(SAR). Marine applications, i.e., winds and waves retrieved from GF-3 SAR images, have been operational since January 2017. In this study, we have collected more than 1000 quad-polarization(vertical-vertical(VV); horizontal-horizontal(HH); vertical-horizontal(VH); horizontal-vertical(HV)) GF-3 SAR images, which were acquired around the China Seas from September 2016 to September 2017. Wind streaks were visible in these images in co-polarization(VV and HH) channel. Geophysical model functions(GMFs), including the CMOD5N together with polarization ratio(PR) model and C-SARMOD, were used to retrieve winds from the collected co-polarization GF-3 SAR images. Wind directions were directly obtained from GF-3 SAR images. Then, the SAR-derived wind speeds were compared with the measurements at a 0.25? grid from the Advanced Scatterometer on board the Metop-A/B and microwave radiometer WindSAT. Based on the analysis, empirical corrections are proposed to improve the performance of the two GMFs. Results of this study show that the standard deviation of wind speed is 1.63 m s^(-1) with a 0.19 m s^(-1) bias and 1.71 m s^(-1) with a 0.26 m s^(-1) bias for VV-and HH-polarization GF-3 SAR, respectively. Our work not only systematically evaluates wind retrieval by using the two advanced GMFs and PR models but also proposes empirical corrections to improve the accuracy of wind retrievals from GF-3 SAR images around the China Seas and thus enhance the accuracy of near real-time operational SAR-derived wind products.

Validation of significant wave height retrieval from co-polarization Chinese Gaofen-3 SAR imagery using an improved algorithm

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 CSARWAVE. 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 CSARWAVE2. An additional 92 GF-3 SAR images were implemented in order to validate CSARWAVE2 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.

Precise Three-Dimensional Deformation Retrieval in Large and Complex Deformation Areas via Integration of Offset-Based Unwrapping and Improved Multiple-Aperture SAR Interferometry:Application to the 2016 Kumamoto Earthquake

Conventional synthetic aperture radar(SAR)interferometry(InSAR)has been successfully used to precisely measure surface deformation in the line-of-sight(LOS)direction,while multiple-aperture SAR interferometry(MAI)has provided precise surface deformation in the along-track(AT)direction.Integration of the InSAR and MAI methods enables precise measurement of the two-dimensional(2D)deformation from an interferometric pair;recently,the integration of ascending and descending pairs has allowed the observation of precise three-dimensional(3D)deformation.Precise 3D deformation measurement has been applied to better understand geological events such as earthquakes and volcanic eruptions.The surface deformation related to the 2016 Kumamoto earthquake was large and complex near the fault line;hence,precise 3D deformation retrieval had not yet been attempted.The objectives of this study were to①perform a feasibility test of precise 3D deformation retrieval in large and complex deformation areas through the integration of offset-based unwrapped and improved multiple-aperture SAR interferograms and②observe the 3D deformation field related to the 2016 Kumamoto earthquake,even near the fault lines.Two ascending pairs and one descending the Advanced Land Observing Satellite-2(ALOS-2)Phased Array-type L-band Synthetic Aperture Radar-2(PALSAR-2)pair were used for the 3D deformation retrieval.Eleven in situ Global Positioning System(GPS)measurements were used to validate the 3D deformation measurement accuracy.The achieved accuracy was approximately 2.96,3.75,and 2.86 cm in the east,north,and up directions,respectively.The results show the feasibility of precise 3D deformation measured through the integration of the improved methods,even in a case of large and complex deformation.

3D motion and geometric information system of single-antenna radar based on incomplete 1D range data

A 3D motion and geometric information system of single-antenna radar is proposed,which can be supported by spotlight synthetic aperture radar（SAR） system and inverse SAR（ISAR） system involving relative 3D motion of the rigid target.In this system,applying the geometry invariance of the rigid target,the unknown 3D shape and motion of the radar target can be reconstructed from the 1D range data of some scatterers extracted from the high-resolution range image.Compared with the current 1D-to-3D algorithm,in the proposed algorithm,the requirement of the 1D range data is expanded to incomplete formation involving large angular motion of the target and hence,the quantity of the scatterers and the abundance of 3D motion are enriched.Furthermore,with the three selected affine coordinates fixed,the multi-solution problem of the reconstruction is solved and the technique of nonlinear optimization can be successfully utilized in the system.Two simulations are implemented which verify the higher robustness of the system and the better performance of the 3D reconstruction for the radar target with unknown relative motion.

CROSS-TRACK THREE APERTURES MILLIMETER WAVE SAR SIDE-LOOKING THREE-DIMENSIONAL IMAGING

The airborne cross-track three apertures MilliMeter Wave (MMW) Synthetic Aperture Radar (SAR) side-looking three-Dimensional (3D) imaging is investigated in this paper. Three apertures are distributed along the cross-track direction, and three virtual phase centers will be obtained through one-input and three-output. These three virtual phase centers form a sparse array which can be used to obtain the cross-track resolution. Because the cross-track array is short, the cross-track resolution is low. When the system works in side-looking mode, the cross-track resolution and height resolution will be coupling, and the low cross-track resolution will partly be transformed into the height uncertainty. The beam pattern of the real aperture is used as a weight to improve the Peak to SideLobe Ratio (PSLR) and Integrated SideLobe Ratio (ISLR) of the cross-track sparse array. In order to suppress the high cross-track sidelobes, a weighting preprocessing method is proposed. The 3D images of a point target and a simulation scene are achieved to verify the feasibility of the proposed method. And the imaging result of the real data obtained by the cross-track three-baseline MMW InSAR prototype is presented as a beneficial attempt.

SAR regional all-azimuth observation orbit design for target 3D reconstruction

Three-dimensional(3D) synthetic aperture radar(SAR)extends the conventional 2D images into 3D features by several acquisitions in different aspects. Compared with 3D techniques via multiple observations in elevation, e.g. SAR interferometry(InSAR) and SAR tomography(TomoSAR), holographic SAR can retrieve 3D structure by observations in azimuth. This paper focuses on designing a novel type of orbit to achieve SAR regional all-azimuth observation(AAO) for embedded targets detection and holographic 3D reconstruction. The ground tracks of the AAO orbit separate the earth surface into grids. Target in these grids can be accessed with an azimuth angle span of360°, which is similar to the flight path of airborne circular SAR(CSAR). Inspired from the successive coverage orbits of optical sensors, several optimizations are made in the proposed method to ensure favorable grazing angles, the performance of 3D reconstruction, and long-term supervision for SAR sensors. Simulation experiments show the regional AAO can be completed within five hours. In addition, a second AAO of the same area can be duplicated in two days. Finally, an airborne SAR data process result is presented to illustrate the significance of AAO in 3D reconstruction.

Synthetic aperture radar tomography sampling criteria and three-dimensional range migration algorithm with elevation digital spotlighting

Based on the general geometric model of multi-baseline Synthetic Aperture Radar Tomography （TomoSAR）, the three-dimensional （3-D） sampling criteria, the analytic expression of the 3-D Point Spread Function （PSF） and the 3-D resolution are derived in the 3-D wavenumber domain in this paper. Considering the relationship between the observation geometry and the size of illuminated scenario, a 3-D Range Migration Algorithm with Elevation Digital Spotlighting （RMA-EDS） is proposed. With this algorithm 3-D images of the area of interest can be directly and accurately reconstructed in the 3-D space avoiding the complex operations of 3-D geometric correction. Finally, theoretical analyses and simulation results are presented to demonstrate the shift-varying property of the 3-D PSF and the spatialvarying property of the 3-D resolution and to demonstrate the validity of the 3-D RMA-EDS.

基于Landsat与Sentinel-3A卫星数据的当惹雍错1988—2018年湖泊水位—水量变化及归因

湖泊变化是气候变化的指示器.为探索利用单一短时间尺度的卫星水位数据源估算长时间序列的湖泊水量变化的可行性,本文利用短时间尺度(2016-2018年)Sentinel-3A合成孔径雷达高度计(SRAL)作为唯一卫星水位数据源,以藏北高原内陆湖泊当惹雍错为例,结合基于Landsat光学遥感数据提取的1988-2018年的湖泊面积,综合分析2016-2018年间的非结冰期遥感湖泊面积与遥感湖泊水位变化,基于该时段范围的水位变化面积变化关系和水量估算公式,估算1988-2018年湖泊水位水量变化与2001-2018年的年内变化,并结合GLDAS产品数据与雪线变化情况初步探讨湖泊变化的可能原因.结果表明:当惹雍错近30年湖泊面积扩张明显,湖泊水位、水量增加显著,相比1988年,2018年的湖泊面积、水位、水量分别增加21.1 km^2、5.29 m、44.75亿m^3.其中1988-1998年湖泊面积水位水量有所减少,2000-2018年间湖泊变化总体呈增加趋势.2001-2018年内湖泊面积、水位、水量变化呈现干湿季特征.1996-2014/2015年湖泊水量变化为38.3亿/35.5亿m^3,水量变化趋势、变化量与以往对应时间段的研究结果具有较强的一致性.湖泊面积扩张主要发生在水下地形平缓的东南部和中西部区域.结合气候因素与雪线变化的分析表明,湖泊水量变化受降雨、气温影响复杂,长时间年际尺度上的湖泊水量增长与气温的一致性较降水量强,湖泊湿季受降水量与气温的影响都较大,其中2008-2018年的湿季降水量、气温与水量变化散点拟合的确定性系数R^2分别为0.613、0.845.该研究表明Sentinel-3A合成孔径雷达数据在湖泊水量变化估算上的潜力,为利用单一且只具有短时段数据的卫星雷达数据估算长时间序列湖泊水量变化提供依据.

GF-3号SAR卫星遥感围填海监测方法研究——以大连金州湾为例

依据不同围填海类型在高分三号(GF-3)合成孔径雷达(synthetic aperture radar,SAR)卫星遥感影像上可分性,建立围填海遥感分类体系及相应的围填海类型解译标志,进而分析SAR图像岸线提取方法,构建GF-3围填海监测技术流程。采用几何主动轮廓模型进行GF-3 SAR影像自动提取海岸线,获得围填海专题图。通过外业精度调查验证GF-3 SAR卫星遥感影像可以有效获取围填海信息。

基于3D-OMP算法的SAR动目标成像方法

针对稀疏场景下的SAR动目标成像问题展开研究,提出一种基于三维正交匹配追踪(3D-OMP)算法的稀疏成像方法。首先对成像区域进行网格划分,然后以运动目标的二维速度作为动态参数构建三维稀疏字典矩阵,即参数化稀疏表征。在算法迭代过程中,通过计算回波数据矩阵与三维稀疏字典矩阵各层之间的相关度筛选出信号的支撑集。最后利用最小二乘准则,计算出支撑集下目标场景的稀疏表征系数。该3DOMP算法是经典OMP算法的改进与拓展,因此继承了OMP算法计算复杂度低、信号稀疏特征增强明显的优势,同时具备了重构SAR动目标图像的能力。仿真实验结果验证了该SAR动目标成像方法的有效性。

基于GF-3影像的金沙江堰塞湖电网受灾区域提取

云南地区降雨频发,暴雨易导致洪涝等灾害发生,显著威胁电网的安全运行。基于合成孔径雷达遥感影像的检测技术近年来广泛应用于水体提取。文章提出一种基于深度学习的洪涝灾害区域提取技术,通过神经网络水体提取和差分变化检测完成电网受灾单位识别。在云南地区"高分三号"卫星影像上对比了与阈值算法(OTSU)、Snake算法、CV分割算法的提取精度,证实了方法的有效性。结果显示,相对经典的分割方法,深度学习方法可以较好的处理复杂场景。该方法用于金沙江流域堰塞湖泄洪受灾检测应用,检出受灾电网单位与现场勘察相符,为电网监测管控提供了保障。该研究可为水体提取、洪涝灾害变化监测研究与应用,以及更广泛的其他地物分割场景提供参考。

基于局部自适应阈值的GF-3 SAR影像洪涝水体提取

针对全局阈值法在大场景SAR图像水体提取时存在的局限性以及山体阴影对水体提取的干扰,提出一种DEM辅助下基于自适应阈值的SAR影像洪涝水体提取方法。首先结合DEM和SAR卫星轨道参数去除山体阴影产生的辐射失真区域,利用K-means聚类算法得到初始的水体分布图;然后在初始水体信息基础上,通过窗口提取局部区域的水体和非水体,并采用KI算法对局部区域进行自适应阈值的计算,实现自适应阈值水体信息的快速提取。利用湖南省东北部GF-3精细条带2成像模式(FSII)SAR影像进行洪涝水体提取实验,研究表明该方法既保留了水体的细节信息,又能减弱噪声、山体阴影等的影响,F-Measure指数高于全局阈值法,其查准率较全局阈值法提高了7.97%,尤其适用于含山区影像的大范围洪涝水体快速提取。

GF-3 data real-time processing method based on multi-satellite distributed data processing system

Due to the limited scenes that synthetic aperture radar(SAR)satellites can detect,the full-track utilization rate is not high.Because of the computing and storage limitation of one satellite,it is difficult to process large amounts of data of spaceborne synthetic aperture radars.It is proposed to use a new method of networked satellite data processing for improving the efficiency of data processing.A multi-satellite distributed SAR real-time processing method based on Chirp Scaling(CS)imaging algorithm is studied in this paper,and a distributed data processing system is built with field programmable gate array(FPGA)chips as the kernel.Different from the traditional CS algorithm processing,the system divides data processing into three stages.The computing tasks are reasonably allocated to different data processing units(i.e.,satellites)in each stage.The method effectively saves computing and storage resources of satellites,improves the utilization rate of a single satellite,and shortens the data processing time.Gaofen-3(GF-3)satellite SAR raw data is processed by the system,with the performance of the method verified.

Sparse flight spotlight mode 3-D imaging of spaceborne SAR based on sparse spectrum and principal component analysis

The spaceborne synthetic aperture radar(SAR)sparse flight 3-D imaging technology through multiple observations of the cross-track direction is designed to form the cross-track equivalent aperture,and achieve the third dimensionality recognition.In this paper,combined with the actual triple star orbits,a sparse flight spaceborne SAR 3-D imaging method based on the sparse spectrum of interferometry and the principal component analysis(PCA)is presented.Firstly,interferometric processing is utilized to reach an effective sparse representation of radar images in the frequency domain.Secondly,as a method with simple principle and fast calculation,the PCA is introduced to extract the main features of the image spectrum according to its principal characteristics.Finally,the 3-D image can be obtained by inverse transformation of the reconstructed spectrum by the PCA.The simulation results of 4.84 km equivalent cross-track aperture and corresponding 1.78 m cross-track resolution verify the effective suppression of this method on high-frequency sidelobe noise introduced by sparse flight with a sparsity of 49%and random noise introduced by the receiver.Meanwhile,due to the influence of orbit distribution of the actual triple star orbits,the simulation results of the sparse flight with the 7-bit Barker code orbits are given as a comparison and reference to illuminate the significance of orbit distribution for this reconstruction results.This method has prospects for sparse flight 3-D imaging in high latitude areas for its short revisit period.

高分3号星载合成孔径雷达极地海冰自动检测方法研究

随着全球变暖等一系列气候变化的发生,极地海冰成为人们日益关注的焦点。由于不受光线和云雨影响,合成孔径雷达(SAR)可以进行全天时全天候的观测。高分3号是我国高分系列卫星中的一颗星载合成孔径雷达成像卫星,具有多种成像模式,可以在全球获取SAR数据。全天时全天候的工作特性和高空间分辨率的优势,使得高分3号星载SAR在极地海冰遥感监测中发挥重要的作用。本文基于高分3号水平-垂直(Horizontal-Vertical,HV)极化数据,提出了一种基于支持向量机的无需人工干预的海冰检测方法,实现海水和海冰的自动分离。利用该方法得到的海冰和海水分离结果同辅以人工解译的半监督分类结果相比较为吻合,为高分3号服务于极区海冰监测奠定了良好的基础。

Airborne sparse flight array SAR 3D imaging based on compressed sensing in frequency domain

In airborne array synthetic aperture radar(SAR), the three-dimensional(3D) imaging performance and cross-track resolution depends on the length of the equivalent array. In this paper, Barker sequence criterion is used for sparse flight sampling of airborne array SAR, in order to obtain high cross-track resolution in as few times of flights as possible. Under each flight, the imaging algorithm of back projection(BP) and the data extraction method based on modified uniformly redundant arrays(MURAs) are utilized to obtain complex 3D image pairs. To solve the side-lobe noise in images, the interferometry between each image pair is implemented, and compressed sensing(CS) reconstruction is adopted in the frequency domain. Furthermore, to restore the geometrical relationship between each flight, the phase information corresponding to negative MURA is compensated on each single-pass image reconstructed by CS. Finally,by coherent accumulation of each complex image, the high resolution in cross-track direction is obtained. Simulations and experiments in X-band verify the availability.

A Downsampled SAR-BM3D Despeckling Approach for Single-Look SAR Images in High Resolution

SAR-BM3D is one of the state of the art despeckling algorithms for SAR images. However, when tackling with high resolution SAR images, it often has an unsatisfying despeckling performance in the homogeneous smooth regions, together with a high time complexity. In this paper, a novel downsampled SAR-BM3D despeckling approach combined with edge compensation is proposed. The proposed algorithm consists of two steps. First, despeckle the image which is a downsampled version of original image with SAR-BM3D. Then, compensate edges in each level when upsampling. This approach not only utilizes the good ability of feature preservation, but also improves performance of smoothing homogenous regions. When it comes to high resolution SAR images, the efficiency can be raised by six to seven times, compared to original SAR-BM3D. Experiments on simulated and real SAR images show that the proposed method reaches a high level in terms of visual quality and act more efficiently.