Abstract:As an active sensor,Synthetic Aperture Radar (SAR) finds many applications in earth observation.However,the signal transmission and reception are persistently disturbed through the ionosphere layer at L-band and below.Ionospheric effect brings phase and amplitude errors to the radio signal traversed therein,and further exerts severe impact on the SAR mage quality.In this paper,we review the spatial-temporal ionospheric effects on the imaging performance of SAR systems that operate at different orbital altitudes.Three kinds of effects are investigated:the Faraday rotation,the background ionospheric effects and ionospheric scintillation.Compensation approaches for these effects are then summarized.Finally,problematic issues associated with the ionospheric effects are outlined in the context of SAR theory and applications.

Abstract:Synthetic Aperture Radar (SAR) technology has unique advantages in forest resource monitoring due to its all-day,all-weather imaging capability and sensitivity to vertical forest structure information.Therefore,SAR has become a research focus of current forest resources remote sensing survey technology.Firstly,the development background,development trajectory and related knowledge of SAR forest resources monitoring technology are introduced.Then,the technological developments of polarimetric SAR,interferometric SAR,polarimetric SAR interferometry and tomographic SAR in research of forest land cover type classification,change detection and forest parameter quantification estimation are emphasized.Finally,the existing problems and development trends for forest resource monitoring research and application of SAR are summarized and analyzed.

Abstract:Snowpack is an important factor affecting the global energy water cycle,such as radiation balance and water resources,while remote sensing is a key method to monitor the temporal and spatial distribution characteristics of snowpack and its changing trend.Synthetic aperture radar (SAR) has become an important research means in snow remote sensing because of its all-day and all-weather observation capability.In this paper,the theory and technology of snow parameter inversion methods are summarized and analyzed from aspects of the characteristics of SAR and snowpack,snow scattering models,snow parameter inversion based on SAR intensity and phase information.And the current research states as well as the problematic issues in snow inversion using SAR data are pointed out,and the future research direction is discussed.

Abstract:The Synthetic Aperture Radar (SAR) technology and its application have developed rapidly since the birth of the first SAR in April of 1960.The deepening and comprehensive technological utilization of different electromagnetic wavebands,polarization,amplitude and phase information,is characterized by the bi-static/multi-static or constellation observation,polarimetric SAR interferometric measurement,high revisit and wide swath mapping with high resolution,3D/4D structure information retrieval,and ultra-high resolution observation.In application aspects,it is featured by efforts to realize the high precision,large scale and time continuous monitoring and evaluation of the Earth surface dynamic process,under the background of major global issues such as global change and global sustainable development.In this paper,we introduce the research background and significance of the new SAR technology for earth observation,and then analyze the progresses of four typical advanced SAR technologies for the past decade,including polarimetric SAR (PolSAR),polarimetric interferometric SAR (PolInSAR),tomographic SAR (TomoSAR),and ultra-high resolution SAR (UHR SAR).Finally,the future development trend of the SAR earth observation technology is analyzed,mainly focused on four aspects:multi-channel information acquisition,multi-angle observation,high temporal observation,high resolution and wide swath mapping.

Abstract:Doppler signal is an important synthetic aperture radar (SAR) parameter for ocean dynamics remote sensing.It was first used for the retrieval of ocean surface dynamic processes in the late 1980s.In this paper,we review the researches on retrievals of sea surface dynamics from spaceborne SAR Doppler measurements including:(1) SAR interferometry techniques and related research progress for ocean surface currents retrieval;(2) SAR Doppler shift and its application in retrieval of upper ocean dynamics (i.e.geostrophic currents,quasi-geostrophic currents,and meso- and small-scale processes);(3) Relevant data fusion and important R&D programs around the world.However,China's remote sensing of sea currents is still in the initial stage,and highly focused on retrieval theory and techniques.The application of the retrieved information in study of upper ocean dynamics is still limited,so this review can serve as a reference for future studies in this direction.

Abstract:The spaceborne synthetic aperture radar (SAR) plays an important role in ocean observation owing to its capability of working all-day and being insusceptible to sunlight,cloudiness or rainfall.It has unique advantages in retrieval of ocean surface dynamic parameters and study of multi-scale ocean dynamic processes with high spatial resolution,multi-polarization,and multi-imaging modes.Since the late 1970s,spaceborne SAR technology has developed rapidly.When combined with big data and machine learning techniques,spaceborne SAR exhibits more powerful vitality in ocean observation.In this paper,the 5‘V’ characteristics of spaceborne SAR big data are elaborated.Then two typical cases,i.e.retrieval of the sea surface wind speed,and scientific recognition of mesoscale dynamic processes of ocean internal waves,are presented to demonstrate the integration of spaceborne SAR,machine learning,and big data in assistance of high-resolution inversion of ocean environmental factors and deep understanding of marine dynamic processes.Finally,the prospective of spaceborne SAR big data for ocean remote sensing is given.

Abstract:By steering antenna beam in along-track direction,space-borne synthetic aperture radar (SAR) can achieve wide swath coverage in Terrain Observation by Progressive Scans (TOPS) mode.In TOPS mode,the beam switches in range and steers along azimuth several times to perform wider swath both in range and azimuth.In order to obtain a whole imaging result with uniform azimuth intervals,the re-sampling operation is usually required,which means large computation load and low processing efficiency.In this paper,a modified three-step algorithm based on Graphics Processing Units (GPU) is proposed.Firstly,a new interpolation method is introduced into the de-ramp operation (the third step of the three-step focusing algorithm),which avoids the up-sampling operation and can conveniently adjust the azimuth interval of final images.Then,a parallel framework of GPU is designed to accelerate the imaging processing exponentially.Finally,experiments based on simulation data are conducted to verify the validness and efficiency of the imaging algorithm.

Abstract:Deep learning methods such as convolutional neural networks (CNN) have been widely used in fields of image processing and object recognition.However,the SAR images cannot yet be efficiently detected by CNN methods.Compared with traditional images,the SAR images have the advantage of all-day and all-weather acquisition,but they cannot obtain enough annotation due to the difficulty for interpretation and short of users.This paper proposes a SAR target detection method based on scene synthesis and anchor constraint.Firstly,the target and its shadow are segmented by region growing as well as threshold algorithm,and then the target detection data set is synthesized by randomly embedding the reasonable region into the SAR complex scene.Considering the SAR target's geometric characteristics and image resolution parameters,the anchor's size of Faster-RCNN is constrained to reduce the candidate frames that cannot meet the SAR target detection frame size,which massively reduce redundancy calculations so as to improve the efficiency and accuracy of training and testing process.

Abstract:The frequent occurrence of geological disasters has brought irreversible great harm to natural environment and human society directly or indirectly.In recent years,China has been strengthening the efforts of early identification and effective prevention of geological disasters.Interferometric Synthetic Aperture Radar (InSAR) has been recognized as an important deformation detecting method with the advantages of all-time,all-weather,high accuracy,and large scale monitoring.In this paper,potential geological hazard points in Qiandongnan prefecture of Guizhou were detected by processing ALOS-2/PALSAR-2 and Sentinel-1 SAR data with D-InSAR and SBAS time series InSAR.The detection results of four representative research areas revealed that:D-InSAR has advantage in large-scale detecting while SBAS has superiority in high-precision monitoring.Hence,the two methods can complement each other and improve the reliability of identification for geological hazards.The cumulative deformation time series and average deformation velocity can be obtained by SBAS simultaneously,which provides valuable reference for geological disaster prevention in Guizhou.

Abstract:The systematic error of InSAR is composed of orbit error and long-wavelength atmospheric delay,which is one of the most important factors that affect the accuracy of InSAR deformation monitoring.Traditional method models the systematic error of each individual interferogram in spatial domain,so it is difficult to distinguish between the long-wavelength deformation and systematic error.In this study,we modeled the systematic errors in spatio-temporal domain,determined the weight matrix of the observations according to its quality,and estimated the deformation parameters and systematic error by the weighted least square method.The simulation results show that,even in the extreme cases where the spatial characteristics of deformation and systematic error are completely consistent,the proposed method can separate the deformation and systematic errors effectively.The deformation rate RMSE of the proposed method is 98.8% lower than that of traditional method.The experiment with ASAR shows that,the proposed method and traditional method obtain similar results when the deformation scale is small and scattered over the study area.However,when large scale long-wavelength deformation occurs in the study area,the results obtained by the proposed method are more robust than those obtained by traditional method.

Abstract:In the context of global warming,the calving events of Antarctic ice shelves are becoming more and more frequent.The icebergs calved from ice shelves are an active component of Antarctic ice sheet-ice shelf-ocean system,while the drifting characteristics and temporal-spatial distribution of icebergs are very important in Antarctic ocean currents,ecology and hydrology.To better understand the underlying relationship between Antarctic icebergs and global climate change,it is essential to investigate the icebergs' drifting characteristics,mass loss due to calving and melting,icebergs distribution,and the interaction between icebergs and the ocean.Based on the object-oriented multiscale image segmentation algorithm of Easy Interpretation software,a total of 32 267 Antarctic icebergs in coastal waters with area larger than 0.06 km² were extracted from 63 ENVISAT ASAR images acquired in August 2006.The spatial distribution characteristics of icebergs were also analyzed,and it is found that small-sized icebergs play an important role in freshwater flux into the Southern Ocean.

Abstract:Geosynchronous Synthetic Aperture Radar (GEO SAR) has the advantages of short revisit period and wide coverage,and has great potential in disaster prevention and mitigation.In this paper,a distributed GEO SAR system containing both close and sparse formation is proposed.On the basis of monostatic GEO SAR,multiple phase centers are formed by adding companion satellites only receiving signals,which has the advantages of rich tasks and low cost.However,different tasks require different spatial baselines for formation.Aiming at the configuration of close formation,this paper proposes a method of correcting the relative motion equation based on coordinate rotation,through which the analytical expression of spatial baseline under the influence of earth rotation can be obtained;furthermore,a method of linear time-varying baseline design based on semi-major axis correction is proposed,which can be applied to SAR tomography.For sparse formation,the minimum Position Dilution of Precision criterion under the measurable constraints of global scene is proposed,which can realize the design of sparse formation with the best combination of line of sight (LOS) thus can achieve the best three-dimensional (3D) deformation retrieval performance.Finally,the system performances of the designed distributed GEO SAR formation are simulated and analyzed,including the diurnal variation of baseline,the resolution in altitude direction and the 3D deformation retrieval accuracy in typical observation areas.

Abstract:Interferometric synthetic aperture radar (InSAR) has become one of the key technologies to obtain high-precision Digital Orthophoto Map (DOM) and Digital Surface Model (DSM).It is not affected by weather conditions and can acquire data in all day and weather conditions.Airborne dual-antenna millimeter-wave InSAR is independent of loss-of-correlation which has the characteristics of small size,high resolution,high flexibility,etc.And it can obtain large-scale and high-precision images.This paper uses airborne dual-antenna millimeter-wave InSAR to acquire high-precision DOM and DSM in Shibing experimental area of Guizhou (mountainous) and Qionglai experimental area of Sichuan (alpine) through interference processing,block adjustment,geocoding,and image mosaic.Besides,the ground control points (GCPs) are used to verify the accuracy.The results show that the accuracy of DSM obtained meets the requirement of 1:5000 terrain mapping.It has been proven that the airborne dual-antenna millimeter-wave InSAR has the ability to generate DOM/DSM with different terrains,which provides a new technical means for solving the lack of DOM/DSM data in tough areas.

Abstract:Orientation-averaged lidar linear depolarization ratios (LLDR) of spheroid dust aerosols are carried out based on discrete dipole approximation (DDA) for size parameters from 0.1 to 23 (corresponding to effective radius from 0.01 to 2 μm at wavelength of 550 nm).The effects of the asphericity degree on the LLDRs for both monodisperse and polydisperse dust aerosols are performed by comparing LLDRs at different spheroid aspect ratios.For monodisperse spheroid,the dust LLDRs show strong dependences on aspect ratio and size parameter.For prolate spheroid dust particles,small LLDR values are found in the Rayleigh domain as opposed to large values in the Mie domain.Nevertheless,for oblate spheroid,large LLDR dust particles in the Mie domain can produce small LLDR values.For example,the dust LLDR has a value of about 0.1% at spheroid aspect ratio of 1/16 when the size parameter reaches 3.For monodisperse dust particles,the aspherical degree increases their LLDRs only at size parameters smaller than 0.5.However,for polydisperse aerosols,the degree of dust asphericity enhances their LLDRs.