The construction of large-scale hydropower stations could solve the problem of China’s power and energy shortages. However, the construction of hydropower stations requires reservoir water storage. Artificially raising the water level by several tens of meters or even hundreds of meters will undoubtedly change the hydrogeological conditions of an area, which will lead to surface deformation near the reservoir. In this paper, we first used SBAS-InSAR technology to monitor the surface deformation near the Xiluodu reservoir area for various data and analyzed the surface deformation of the Xiluodu reservoir area from 2014 to 2019. By using the 12 ALOS2 ascending data, the 100 Sentinel-1 ascending data, and the 97 Sentinel-1 descending data, the horizontal and vertical deformations of the Xiluodu reservoir area were obtained. We found that the Xiluodu reservoir area is mainly deformed along the vertical shore, with a maximum deformation rate of 250 mm/a, accompanied by vertical deformation, and the maximum deformation rate is 60 mm/a. Furthermore, by analyzing the relationship between the horizontal deformation sequence, the vertical deformation sequence, and the impoundment, we found the following: (1) Since the commencement of Xiluodu water storage, the vertical shore direction displacement has continued to increase, indicating that the deformation caused by the water storage is not due to the elastic displacement caused by the load, but by irreversible shaping displacement. According to its development trend, we speculate that the vertical shore direction displacement will continue to increase until it eventually stabilizes; (2) Vertical displacement increases rapidly in the initial stage of water storage; after two water-storage cycles, absolute settlement begins to slow down in the vertical direction, but its deformation still changes with the change in the storage period.

The Lost Hills oilfield, located ∼70 km northwest of Bakersfield in the San Joaquin Valley, has a long history of oil/gas extraction, and it suffers from long-term ground deformation. Many SAR datasets include information about the Lost Hills oilfield over the past two decades. This study focused on calculating and analysing the long-term vertical ground deformation due to oil and gas extraction in the Lost Hills oilfield and proposed a new strategy inspired by the “Small Baseline Subset” idea for jointly processing multi-track SAR images to obtain long-term time-series deformations. The experimental results showed a maximum vertical deformation rate of 20 mm/year in the uplift region and –90 mm/year in the subsidence region of the Lost Hills field from August 1995 to September 2010, and the long-term vertical time-series deformations had a precision of 5 mm. In addition, a multivariate polynomial regression model was used to quantify the relationship between surface deformation volume changes and water, oil, and gas injection-production data. The results demonstrated that the relationship between the ground volume change and injection/production dataset in the subsidence region followed a multivariate linear model, whereas the uplift region satisfied a multivariate quadratic polynomial model. The modelling results provided a new perspective on interpreting ground deformation due to oil/gas extraction.

Natural factors or human activities can alter the stress of earth surface or its interior part, which generally causes disaster events. Obtaining the key geoscience paramters of disaster events and their developing progress is essential for us to accurately understand the disaster progress, scientifically interpret the disaster mechanism, and properly formulate acting strategy. InSAR is widely used in the parameter inversion of disaster events and their developing progress caused by natural factors or human activities. This paper firstly introduces the development of InSAR satellites and the basic principles of InSAR surface deformation monitoring. Subsequently, the research status of InSAR geoscience parameter inversion in various disaster-causing events is summarized, including earthquake, volcanic activity, groundwater extraction, mining, permafrost freezing and thawing, glacier movement, and underground fluid migration, etc. Finally, we conclude the main challenges and issues of InSAR geoscience parameter inversion.

Distributed scatterers (DSs) are necessary to increase point density in multi-temporal InSAR (MT-InSAR) monitoring. The identification of homogeneous pixels (HPs) is the first and key step for DS processing to overcome the low signal-to-noise ratio condition. Since multi-polarization data are good at describing geometrical structures and dielectric properties of ground objects, they have been applied for HP identification. However, polarimetric information is not enough for identifying areas with similar ground objects but different deformation. We propose a novel DS preprocessing algorithm based on polarimetric interferometric homogeneous pixel (PIHP) identification. Firstly, a novel Polarimetric InSAR (PolInSAR) similarity that combines polarimetric intensity, interferometric coherence, and phase is proposed, which is readily available in multi-baseline and multi-polarization data and flexible by controlling weighting factors. Secondly, based on the binary partition tree (BPT) framework, object-orientated multi-scale PIHP identification is achieved, which is suitable for complex deformation scenes. Tested with simulated quad-polarization data, our method shows improvement in phase quality and point density, especially in the deformed areas, compared with the traditional HP identification method based on the polarimetric homogeneity (PolHom) test and the method with ground object type map. Tested with 30 quad-polarization Radarsat-2 images over Kilauea Volcano, the point density of our method is three times higher than that of the PolHom test in vegetation areas. Our method is proven to be more sensitive and mechanically more advanced to homogeneous pixels identification than the traditional ones, which is helpful for phase optimization, spatial enlargement of monitoring points, and stability of the MT-InSAR algorithm.

According to the HyperSonic Vehicle (HSV) borne radar platform system, a multi-channel SAR-GMTI clutter suppression method is presented based on hypersonic platform forward squint mode. First, range walk correction and range compression are completed in the time domain, and the distance envelope is aligned simultaneously with phase error compensation. Then, the Doppler extended signal is compressed by three-order azimuth Chirp Fourier Transform (CFT), and the azimuth envelope of the echo is aligned with phase error compensation simultaneously. Next, the Digital Beam Forming (DBF) technology is applied to the range time-azimuth CFT domain by nulling the clutter and its ambiguous components to achieve Space-Time Adaptive Processing (STAP). The stationary clutter and its ambiguous components can be suppressed effectively and the echo signs of the moving target without blurring can be extracted.

Global navigation satellite system (GNSS) and interferometric synthetic aperture radar (InSAR) data are integrated to extract the 3-D surface deformations, which are of great significance for studying geological hazards. In this study, two major problems are focused on integration. For one thing, we propose an iterated almost unbiased estimation (IAUE) method to estimate the variance components of GNSS and InSAR for the case where the estimation of variance components of multisource data by traditional variance component estimation methods may be negative and inaccurate. For another, considering that heterogeneous data errors may lead to unstable 3-D solutions, we propose adding the Laplacian smoothness constraint (LSC) to the function model, which can smooth the solutions by minimizing the second derivative of the displacements. These two methods are abbreviated as IAUE-LSC. In the simulation experiment, the performance of traditional Helmert variance component estimation is first compared with IAUE. IAUE can not only converge more quickly, but also avoid negative variances. Furthermore, we find that the excessively large relative error ratio between GNSS and InSAR is an essential factor leading to the instability of the 3-D solutions. The IAUE-LSC method is immune to this instability and can obtain more stable results. In addition, the 2018 Hawaii case demonstrates that IAUE achieves improvements of 2.58, 2.77, and 7.69 cm in the east, north, and up directions relative to the traditional weighted least-squares method, while the combined IAUE-LSC achieves improvements of 2.29, 0.32, and 1.68 cm compared to the IAUE alone.

Interferometric synthetic aperture radar (InSAR) products may be significantly distorted by microwave signals traveling through the ionosphere, especially with long wavelengths. The split-spectrum method (SSM) is used to separate the ionospheric and the nondispersive phase terms with lower and higher spectral sub-band interferogram images. However, the ionospheric path delay phase is very delicate to the synthetic aperture radar (SAR) parameters including orbit vectors, slant range, and target height. In this paper, we get the impact of SAR parameter errors on the ionospheric phase by two steps. The first step is getting the derivates of geolocation with reference to SAR parameters based on the range-Doppler (RD) imaging model and the second step is calculating the derivates of the ionospheric phase delay with respect to geometric positioning. Through the numerical simulation, we demonstrate that the deviation of ionospheric phase has a linear relationship with SAR parameter errors. The experimental results show that the estimation of SAR parameters should be accurate enough since the parameter errors significantly affect the performance of ionospheric correction. The root mean square error (RMSE) between the corrected differential interferometric SAR (DInSAR) phase with SAR parameter errors and the corrected DInSAR phase without parameter errors varies from centimeter to decimeter level with the L-band data acquired by the Advanced Land Observing Satellite (ALOS) Phased Array type L-band SAR (PALSAR) over Antofagasta, Chile. Furthermore, the effectiveness of SSM can be improved when SAR parameters are accurately estimated.

As an indispensable ecological parameter, surface soil moisture (SSM) is of great significance for understanding the growth status of vegetation. The cooperative use of synthetic aperture radar (SAR) and optical data has the advantage of considering both vegetation and underlying soil scattering information, which is suitable for SSM monitoring of vegetation areas. The main purpose of this paper is to establish an inversion approach using Terra-SAR and Landsat-7 data to estimate SSM at three different stages of corn growth in the irrigated area. A combined scattering model that can adequately represent the scattering characteristics of the vegetation coverage area is proposed by modifying the water cloud model (WCM) to reduce the effect of vegetation on the total SAR backscattering. The backscattering from the underlying soil is expressed by an empirical model with good performance in X-band. The modified water cloud model (MWCM) as a function of normalized differential vegetation index (NDVI) considers the contribution of vegetation to the backscattering signal. An inversion technique based on artificial neural network (ANN) is used to invert the combined scattering model for SSM estimation. The inversion method is established and verified using datasets of three different growth stages of corn. Using the proposed method, we estimate the SSM with a correlation coefficient R ≥ 0.72 and root-mean-square error R M S E ≤ 0.043 cm 3 /cm 3 at the emergence stage, with R ≥ 0.87 and R M S E ≤ 0.046 cm 3 /cm 3 at the trefoil stage and with R ≥ 0.70 and R M S E ≤ 0.064 cm 3 /cm 3 at the jointing stage. The results suggest that the method proposed in this paper has operational potential in estimating SSM from Terra-SAR and Landsat-7 data at different stages of early corn growth.

对海面舰船目标进行成像模拟是获取任意条件下海面舰船合成孔径雷达(SAR)图像的一种有效手段,在海上目标识别、判读人员训练、SAR系统设计优化与性能评估等应用中具有重要意义.基于工作过程的信号级SAR成像模拟方案具有逼真度高等显著优势,但存在数据量和运算量巨大、实时性差等问题.介绍了海面舰船SAR成像信号级模拟流程,从模型层面、算法层面、平台层面上总结了目前实现SAR成像信号级快速模拟的方法,对其研究现状进行综述.

高分三号(GF-3)是我国第一部全极化星载合成孔径雷达,也是世界上最为先进的全极化星载合成孔径雷达之一,在轨测试和定标是其定量化和全极化应用的前提,卫星发射后,开展了为期三个月的在轨测试和定标.本文提出了一种新型全极化有源定标器设计方案,利用研制的新型全极化有源定标器获取的在轨测试数据,分析了SAR(Synthetic Aperture Radar)天线方向图、SAR发射脉冲特性以及SAR发射天线极化隔离度等指标,分析结果表明,高分三号SAR具有良好的性能指标.根据全极化成像结果对极化有源定标器指标进行了验证,验证结果表明,有源定标器可以提供不同的散射矩阵且具有良好的点目标特性和极化隔离度指标.

Range ambiguity is one of the factors which affect the SAR image quality. Alternately transmitting up and down chirp modulation pulses is one of the methods used to suppress the range ambiguity. However, the defocusing range ambiguous signal can still hold the stronger backscattering intensity than the mainlobe imaging area in some case, which has a severe impact on visual effects and subsequent applications. In this paper, a novel hybrid range ambiguity suppression method for up and down chirp modulation is proposed. The method can obtain the ambiguity area image and reduce the ambiguity signal power appropriately, by applying pulse compression using a contrary modulation rate and CFAR detecting method. The effectiveness and correctness of the approach is demonstrated by processing the archive images acquired by Chinese Gaofen-3 SAR sensor in full-polarization mode.

SAR(synthetic aperture radar)image quality is a series of important parameters to char-acterize the radar imaging and quantitative application ability of SAR satellites.In the system de-sign of GF-3 satellite,according to the ocean application,disaster mitigation,water conservancy, meteorology and others,the image performance requirements are presented to meet the require-ments of different users in typical application and quantitative analysis,and the geometric quality and radiation quality of 2 categories and 13 image quality parameters are determined.The influ-ences of the satellite platform,SAR payload,signal transmission,ground calibration and image processing on image quality are determined,as well as the methods to ensure the image quality parameters through satellite system design are summarized.The conformity of the image quality parameters are verified by the test and operation on orbit,which provides references in design for the subsequent SAR satellites.

Resolution is an important parameter that reflects the imaging quality of bistatic synthetic aperture radar (SAR).The calculation of general configuration bistatic SAR resolution is researched in this paper.Firstly,formula of ground resolution is derived based on the special gradient method and formula of azimuth resolution is derived according to the change of 0Doppler frequencies from transmit and receive platform.Then the real factors that affect the bistatic SAR resolution are pointed out based on theory derivation and simulation.Finally,analysis of ground resolution and azimuth resolution for imaging area under three different kinds of configuration is presented,which can provide reference for bistatic SAR system design.

To deal with the lack of practical data and the high time-consuming of the traditional method,this paper introduces a bistatic synthetic aperture radar (SAR) echo simulation method based on graphic processing unit (GPU) acceleration.Scatterers' corresponding amplitudes and phase are added along the equal slant line,then convoluted with transmit signals.The computation is carried out in the form of array,and GPU is used to further increase the speed.The simulation results show that the proposed method can not only accelerate the simulation speed dramatically compared with traditional method,but also satisfy the image requirement.

本文阐述了高分辨率遥感卫星及其遥感数据处理分析与区域应用情况。高分辨率遥感卫星的技术创新点主要表现在:建成了国内首个多星遥感数据综合处理及海量遥感数据共享存储和分发服务平台;提出了高精度几何校正和辐射校正技术;建成了青海生态环境高分遥感应用示范系统。高分辨率遥感卫星的研究成果已在我国农业、林业、水利、国土、城市、环保、灾害等众多领域得到广泛应用。

Based on the GF-3 satellite sliding spotlight imaging model and echo signal characteris-tics,according to the characteristics of the sliding spotlight meter level high resolution and highly sensitive to echo signal error,SAR focusing on the sliding spotlight high-resolution imaging algo-rithm into the deep research,this paper presents a combination of internal calibration signal am-plitude and phase error compensation of the sliding spotlight high resolution DCS imaging algo-rithm,and presents the algorithm detailed implementation steps and technical process.The measured data by using the high GF-3 satellite is processed to verify the effectiveness,the results show that the combination of internal calibration signal amplitude and phase error compensation of DCS imaging algorithm can effectively improve the image quality of sliding spotlight high-resolution SAR imaging,and imaging processing can be obtained better focusing effect and algo-rithm than traditional methods.

Range Doppler algorithm is used for image location of HJ-1C satellite . The initial location accuracy is about 1 100~1 400m, which cannot meet the needs of the application properly. Furthermore, azi-muth error is the major location error of HJ-1C image. By analyzing the impact factors on the HJ-1C satellite location accuracy, it is concluded that time error is the most critical factor affecting the geometric location. So the time error needs to be compensated. First SAR time errors need be calculated and compensated. Secondly, range Doppler algorithm is used for location. Finally the method is verified by HJ-1C satellite images. The re-sults indicate that location accuracy of HJ-1C satellite is improved from 1 100~1 400m to around 300m.

Some satellites that does not provide rational polynomial coefficient(RPC) parameters,which is inconvenient to user.And even if it has,all based on rigorous sensor model and adopts method of terrain irrelevant.In this process,ephemeris,attitude and other auxiliary data of remote sensing imagery is needed.So the geometrical location accuracy of RPC model influenced by auxiliary data measurment precision,the computational method,which uses a small amount of ground control points(GCP)and adopts strictly affine transformation model to calculate the RPC parameters of remote sensing imagery,is developed.By testing the high resolution(HR) remote sensing imagery of CBERS-02B satellite,the results showed that the method is feasible.