基于高分三号数据的干涉测量研究

合成孔径雷达技术与传统测量技术相比,实现全天时、全天候对地观测,并监测地面的形变信息。2012年前,INSAR研究和应用团队仍然停留在依赖于国外数据的窘迫现状。随着资源三号、环境一号卫星的发射,作为光学卫星为我国测绘事业提供不少便利,但是国内并没有一颗真正意义的SAR卫星。2016年,高分三号作为首颗SAR卫星解决国内SAR卫星数据短缺的问题,研究高分三号卫星的InSAR能力,同时将高分三号卫星应用范围得以拓展。本文对高分三号河南省登封市周围地区进行实验分析,并与InSAR技术成熟的哨兵一号卫星数据进行对比分析,得出结论:①合成孔径雷达采集时间间隔29 d或者29 d的倍数并且雷达入射角相同的高分三号数据可以用于InSAR试验,通过合成孔径雷达干涉测量技术对地表进行形变监测,验证高分三号的干涉测量能力;②通过高分三号数据进行山区形变监测,利用哨兵一号数据对测区进行对比分析,验证高分三号提取地表形变信息的能力。     

Investigation of the ground displacement in Saint Petersburg,Russia, using multiple-track differential synthetic aperture radar interferometry

Global sea level rise and local land subsidence might exacerbate the risk of flooding in coastal plains. Among other cities, this is also the case for the high-latitude city of St. Petersburg, which has long been threatened by flood events. To protect the urban area from storm surges, the Union of Soviet Socialist Republics (USSR) in 1978 approved the construction of the 25 km long Flood Prevention Facility Complex (FPFC), which was completed in 2011. The risk of flooding in the city area of St. Petersburg is amplified by the fact that large sections of the coastal area have been reclaimed from the sea. In this study, we investigate the temporal evolution of the ground displacement in St. Petersburg. To this end, we perform an extended analysis based on the application of a simplified version of the differential interferometric synthetic aperture radar technique, known as the minimum acceleration (MinA) approach. The MinA algorithm is a multi-satellite/multi-track interferometric combination technique that allows working with multiple sets of SAR images. The method allowed generation of time series of two-dimensional (2-D) (i.e. East-West and Up-Down) deformation of the terrain by processing two sequences of Sentinel-1A/B (S-1A/B) SAR images acquired from 2016 to 2018, along the ascending and descending flight passes. The Small BAseline Subset (SBAS) algorithm was independently applied to the two sets of SAR data to generate the relevant Line-Of-Sight (LOS)-projected ground deformation time series. Subsequently, the LOS-projected deformation products were geocoded and jointly combined. The results indicate that the deformation in the city is predominantly vertical (i.e. it is subsiding) with a maximum subsidence rate of about 20 mm/year corresponding to the newly sea-reclaimed lands. Finally, the error budget of the retrieved 2-D deformation time series has also been addressed.     

Savonius型桨叶水动力特性研究

Savonius桨叶是一种典型的垂直轴阻力型桨叶,在风力发电中广泛应用。这种桨叶具有在多风向作用下单向转动的特性。利用该特性,将其应用于捕获水质点运动方向发生周期性或非周期性改变的波浪能的相关研究。采用Fluent数值仿真软件并基于UDF二次开发技术建立桨叶三维数值模型,分析叶片重叠率、相对入水深度和开口率等参数对桨叶动转矩和功率等水动力特性的影响,搭建实验平台,开展物理模型对照试验。研究结果表明:叶片重叠率有助于减小S型桨叶负转矩;当桨叶在水面上高度与波幅相等时,其功率系数达到最大;在叶片上增加弹片阀开口,可以增大桨叶动转矩系数,当开口面积达到一半时,动转矩系数比未开口桨叶提高28.3%。     

双轨D-InSAR技术监测矿区地面沉降的应用

合成孔径雷达差分干涉测量(Differential interferometry synthetic aperture radar,D-InSAR)技术在矿区地面沉降监测领域具有独特的优势和巨大的发展潜力。为分析并掌握济宁某矿区地面沉降的变化状况,选取具备高穿透植被能力的L波段的ALOS PALSAR数据,基于双轨D-InSAR技术对采煤塌陷进行动态监测,获取矿区的形变信息,并与水准数据进行对比分析,进而为有效的进行矿山地质环境保护与治理恢复提供一定的理论依据和技术支持。     

基于间断自适应MRF的相位解缠算法

合成孔径干涉雷达（InSAR）技术已被广泛应用于地面高程信息的获取。相位解缠作为其关键步骤直接关系到地表高程的提取精度。然而,相位解缠受相位连续性假设的限制无法识别间断相位,影响在陡峭地形区域的高程反演精度。针对上述问题,本文提出了一种基于间断自适应马尔可夫随机场模型（DA-MRF）的相位解缠算法处理间断相位。首先构建DA-MRF模型的能量函数能够自适应地在连续相位处保持像素连接,同时在间断相位处阻断像素连接;然后再利用图割算法优化能量函数,完成相位解缠。仿真和实测数据试验证明,本文方法与常用的相位解缠算法相比,具有更强的间断相位保持能力,更适用于地形变化剧烈场景中的地形重建。     

一种快速非局部平均合成孔径雷达海洋图像斑点噪声抑制方法

合成孔径雷达在海洋环境监测和海洋研究中扮演着越来越重要的角色。受其成像机制的影响,合成孔径雷达图像总是受到斑点噪声的污染。斑点噪声的存在会增大目标识别、跟踪和分类的难度,也会降低雷达信号的信噪比。合成孔径雷达海洋图像具有一些特殊的性质：海洋现象在雷达图像中主要呈现为条带状或斑块状的结构。这些条带状或斑块状的结构呈现出高度的自相似性或信息冗余。非局部平均方法能够衡量图像中不同图像块之间纹理结构的相似性,并利用图像的自相似性对图像进行去噪。但非局部平均去燥方法存在计算量巨大、计算耗时长的缺点,这几乎限制了其实际应用。本文采用一种自适应方法将雷达图像中的像素点区分为纹理区像素点和平坦区像素点。对纹理区像素点,采用较大的相似窗和搜索窗,对平坦区像素点,采用较小的相似窗和搜索窗,从而提高计算速度。进一步,本文基于计算统一设备并行架构（CUDA）技术,利用计算机图形处理器（GPU）对前述算法进行并行加速。与经典非局部平均算法相比,加速后算法的计算效率提高了200倍。     

利用星载InSAR技术获取DEM及误差来源分析

星载干涉合成孔径雷达(InSAR)技术是一种高效的数字高程模型(DEM)获取方法,对其展开探讨具有十分重要的意义。本文对InSAR高程测量原理进行简要概述,提出获取DEM的相关技术流程,并分析了利用星载InSAR技术获取DEM的误差来源。     

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.     

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.     

矩形Cartogram自动构建方法探究

矩形Cartogram作为一种同时表达拓扑及数据属性的面域Cartogram,因其表达内容简单、直观的特点,具有较大的潜力。矩形Cartogram尝试用简单的矩形表示复杂地理所具有的拓扑及数据属性,这两个属性在其自动构建过程中往往是矛盾的,因此产生了很多截然不同的构造方法。对其自动构建方法进行研究,有助于地理信息与统计数据融合方法的探索。本文首先简要介绍了矩形Cartogram的研究背景、研究现状及其意义;归纳了矩形Cartogram的特点与评价标准,进而分析了两类构造矩形Cartogram的典型算法,总结了自动构建算法难点;最后探讨了现有矩形Cartogram研究存在的问题,并对其发展方向进行了展望。