雷达遥感六十年：四个阶段的发展

雷达遥感问世60年来已经历了4个阶段的发展,其在对地观测中的作用正日益凸显,已经广泛应用于不同领域。4个阶段分别是单波段单极化阶段,多波段多极化阶段,极化和干涉阶段,以及以双/多站或星座、高时序高分宽幅、3维成像为代表的新阶段。本文结合作者长期在雷达遥感领域的研究经历,总结和回顾了雷达遥感的阶段发展和具有里程碑式的代表性技术;从观测技术、数据处理和应用角度阐述了新阶段雷达遥感的发展趋势,以及雷达遥感与人工智能和大数据结合的思考;最后着眼未来,介绍了月基雷达对地观测平台的前瞻性研究。     

Sentinel-1A SAR影像及其在矿区地面沉降监测中的应用研究

详细介绍了Sentinel-1A SAR影像数据的基本参数、工作模式、应用领域等。利用2016.11.09—2017.03.09的5景Sentinel-1A C波段SAR影像数据进行矿区地面沉降监测试验。基于SARscape利用双轨D-In SAR技术进行差分干涉处理,得到了研究区地面沉降分布图,直观地再现了研究区在2016.11.09—2017.03.09的沉降分布、沉降量级等。结果表明济宁某矿区在监测期间地面相对稳定,未有大面积和大量级的地面沉降发生,4个干涉对监测到的最大沉降都未超过3 cm。     

基于GAMMA的D-InSAR技术在矿区地面沉降监测中的应用

详细介绍了专业的雷达数据处理软件GAMMA和基于GAMMA的双轨D-InSAR数据处理流程;对济宁地区真实L波段的ALOS PALSAR数据进行了双轨D-InSAR处理,完成了从干涉数据的读取到形变图生成的整个流程,并生成了一系列清晰的结果图;结合GIS软件得到研究区的沉降位置、分布和沉降量等信息。研究表明:利用GAMMA软件可以对雷达影像进行双轨D-InSAR处理,得到清晰的中间结果图;双轨D-InSAR可以对矿区进行地面沉降监测,进而掌握由于煤矿开采引起的地面沉降分布和沉降程度,为煤矿区的合理开采和可持续发展提供一定的理论依据。     

SAR image despeckling with a multilayer perceptron neural network

Speckle noise in synthetic-aperture radar (SAR) images severely hinders remote sensing applications; therefore, the appropriate removal of speckle noise is crucial. This paper elaborates on the multilayer perceptron (MLP) neural-network model for SAR image despeckling by using a time series of SAR images. Unlike other filtering methods that use only a single radar intensity image to derive their parameters and filter that single image, this method can be trained using archived images over an area of interest to self-learn the intensity characteristics of image patches and then adaptively determine the weights and thresholds by using a neural network for image despeckling. Several hidden layers are designed for feedforward network training, and back-propagation stochastic gradient descent is adopted to reduce the error between the target output and neural-network output. The parameters in the network are automatically updated in the training process. The greatest advantage of MLP is that once the despeckling parameters are determined, they can be used to process not only new images in the same area but also images in completely different locations. Tests with images from TerraSAR-X in selected areas indicated that MLP shows satisfactory performance with respect to noise reduction and edge preservation. The overall image quality obtained using MLP was markedly higher than that obtained using numerous other filters. In comparison with other recently developed filters, this method yields a slightly higher image quality, and it demonstrates the powerful capabilities of computer learning using SAR images, which indicate the promising prospect of applying MLP to SAR image despeckling.     

华南飑线系统对流与层云区闪电起始和通道位置处的云微物理特征

利用广州S波段双偏振雷达观测数据和低频电场探测阵列三维闪电定位数据,分析了2017年5月4日和5月8日华南地区两次飑线过程中闪电起始和通道位置处的雷达偏振参量和降水粒子特征.两次飑线中约80％的闪电起始和通道(统称闪电放电)定位于对流区.对流区闪电放电位置处的雷达反射率(ZH)要比层云区平均大4～5 dBZ,其它偏振参...     

上海青浦CINRAD/SAD雷达和南汇WSR-88D雷达数据对比分析

上海青浦CINRAD/SAD雷达和南汇WSR 88D雷达型号不同,并且采用不同的双偏振技术升级方案,实际业务运行中2部雷达存在一定的数据偏差。为了对雷达的探测性能进行定量评估,在共同探测区域遴选2022年7—9月及2023年6月共30个过程3933个时次数据,以稳定性降水与对流性降水分类并按强度分级进行对比,评估了反射率因子ZH,差分反射率ZDR,相关系数CC和差分传播相移ΦDP的水平分布特征及随方位变化趋势,雷达灵敏度随仰角变化趋势以及ZH和ZDR偏差的定量统计。结果表明：2部雷达ZH的观测结果接近,青浦CINRAD/SAD雷达的ZH,CC和ΦDP受地物及避雷针影响较大,随方位变化不稳定,青浦CINRAD/SAD雷达在低层的非气象回波滤除效果较南汇WSR 88D雷达差。2部雷达ZH和ZDR的偏差在ZH大于40 dBz的区域较大,ZH平均偏差为0.9 dB,ZDR为-0.14 dB。本文基于台风、冰雹、短时强降水和梅雨降水数据,定量化评估了上海2部S波段双偏振天气雷达数据之间的差异,为后续算法改进以及数据订正提供参考。     

基于SAR干涉点目标分析技术的城市地表形变监测

通过深入研究干涉点目标的相位模型,提出基于空间搜索的邻近点目标干涉相位差解缠方法,用以计算点目标的地形残差和线性形变,以及分离点目标大气延迟相位和非线性形变相位的时空域滤波方法,解决干涉点目标分析中的关键问题.最后,以苏州地区地表沉降监测为应用试验,利用形成的SAR干涉点目标形变信息提取技术,获取苏州市区1992-2002年间的地表沉降信息.研究结果与已有文献记录保持比较好的一致性,证明SAR干涉点目标技术完全可以发展成为应用于城市地表形变监测的实用化技术.

Abstract：

Interferometric point target analysis (IPTA) is one of the latest developments in radar interferometric processing. It is achieved by analysis of the interferometric phases of some individual point targets, which are discrete and present temporarily stable backscattering characteristics, in long temporal series of interferometric SAR images. This paper analyzes the interferometric phase model of point targets, and then addresses two key issues within IPTA process. Firstly, a spatial searching method is proposed to unwrap the interferometric phase difference between two neighboring point targets. The height residual error and linear deformation rate of each point target can then be calculated, when a global reference point with known height correction and deformation history is chosen. Secondly, a spatial-temporal filtering scheme is proposed to further separate the atmosphere phase and nonlinear deformation phase from the residual interferometric phase. Finally, an experiment of the developed IPTA methodology is conducted over Suzhou urban area. Totally 38 ERS-1/2 SAR scenes are analyzed, and the deformation information over 3 546 point targets in the time span of 1992-2002 are generated. The IPTA-derivecl deformation shows very good agreement with the published result, which demonstrates that the IPTA technique can be developed into an operational tool to map the ground subsidence over urban area.     

基于边缘分析的海面溢油检测

提出一种基于边缘检测的快速溢油信息提取方法, 首先对溢油图像进行ROA(radio of average)边缘检测, 根据检测结果进行AOI(area of interest)提取, 然后使用改进的Weibull-CFAR检测算法对AOI进行溢油检测, 并与全局CFAR检测结果进行对比。实验结果证明, 所提出的方法对于非均匀灰度SAR图像溢油检测准确性较好、效率较高, 特别适用于大图像的快速溢油检测。     

全极化SAR数据反演桥面高度

根据高分辨率SAR图像上建筑区的影像特征, 提出了基于灰度共生矩阵(gray-level cooccurrence Matrix, GLCM)纹理分析的建筑区提取方法, 该方法由初步定位和边界调整2个步骤组成, 均遵循特征计算、基于Bhattacharyya距离的特征选择和KNN分类流程, 所不同的是2个步骤中分别采用了逐块和逐点计算纹理特征的方式以兼顾纹理分析的效率和准确性。文中对不同SAR传感器获取的图像进行了实验。实验结果表明, 选用具有最大Bhattacharyya距离值的3或4个特征可以获得较好的初步定位结果, 建筑区的检测率超过80%, 虚警率低于10%;随着边界调整的进行, 检测到的建筑区边界逐渐接近于真实边界。实验结果验证了该算法的有效性。     

基于主成分分析的ENVISAT ASAR数据在福建省漳州市香蕉园地提取中的应用(英文)

Banana is one of the main economic agrotypes in Zhangzhou, Fujian Province. The multi-temporal ENVISAT ASAR data with different polarization are used to classify the banana fields in this paper. Principal component analysis (PCA) was applied for six pairs of ASAR dual-polarization data. For its large leaves, banana has high backscatter. So the value of banana fields is high and shows very bright in the 1st component, which makes it much easier for banana fields extraction. Dual-polarization data provide more information, and the VV and VH backscatter of banana show different characters with other land covers. Based on the analysis of the radar signature of banana fields and other land covers and the 1st component, banana fields are classified using object-oriented classifier. Compared to the field survey data and ASTER data, the accuracy of banana fields in the study area is 83.5%. It shows that the principal component analysis provides the useful information in SAR images analysis and makes the extraction of banana fields easier. Supported by the Program for New Century Excellent Talents in University (NCET-05-0573), Fujian Science and Technology Project (No.2006I0018), the Science Project of the Education Department of Fujian Province(No. 2006F5022).