合成孔径雷达遥感地质应用综述

合成孔径雷达(synthetic aperture Radar,SAR)凭借其全天时、全天候的对地观测能力以及独特的穿透成像特性,在热带雨林及沙漠等典型覆盖地区遥感地质调查中得到了广泛应用。通过阐述地质体微波散射机理,详细总结了SAR在地质考古、岩性识别、地质构造探测和矿产勘查等应用领域的国内外研究进展;介绍了多源影像融合技术在国内外雷达地质调查中的应用情况,并结合项目实例对其重要作用进行了分析。虽然雷达技术受影像自身特点、处理技术以及数据源等问题的制约,在国内地质调查中的应用水平依然较低,但随着软硬件技术的发展,雷达遥感技术在国内地质应用中的作用也将愈发重要。     

“雷达干涉测量”课程教学设计与实践

雷达干涉测量作为遥感对地观测领域中的热点学科,受到测绘、地质、矿业、水利、国土资源、航空航天、地震等各行各业的广泛关注。为了适应科技发展对雷达干涉测量高级人才的需求,许多高校开设了或即将开设“雷达干涉测量”等相关课程。结合东北大学在“雷达干涉测量”课程教学及实践中的经验,围绕课程教学设计、教学方法、教学实践中遇到的问题及解决方案等方面进行了详细探讨,为促进高素质雷达遥感人才培养工作贡献力量。     

地质雷达在北京地铁地下空洞探测中的应用研究

地质雷达对地下空洞等异常地质的探测成果可有效避免城市地铁建设对周边环境和施工安全产生的不良影响。本文介绍了地质雷达的构成和测量原理,利用地质雷达对城市地铁建设途经部分路段地下地质情况进行了探测,针对探测成果对地下空洞位置、深度、面积等基础地理信息资料进行了分析,为制定地下空洞处理方案和消除工程施工安全隐患提供了保障。     

雷达技术在影像制作方面的应用

以机载雷达影像为主要研究对象,介绍了雷达技术作为影像制作方面的新技术,在实际生产工作中的应用及优势,阐述了雷达影像与传统光学影像的差别及各自的优缺点.     

国内高分辨率SAR正射影像生产过程中控制点数量研究

合成孔径雷达(Synthetic Aperture Radar,SAR)在摄影测量方向上的应用越来越广泛,在及时性、准确性上对可见光影像有明显的优势.本文通过对不同控制点数量生产出的国内卫星雷达正射影像精度分析,研究利用国内SAR影像进行正射影像生产时控制点的选点方式,进而达到利用国内SAR影像进行摄影测量生产应用的目的.     

地理国情普查项目数据平台的扩展应用

针对ArcGIS现有功能无法满足地理国情普查项目生产中的作业需求问题,该文提出了使用.NET语言和ArcGIS Add-in进行桌面定制和功能扩展研发、对ArcMap进行扩展和完善的方法:通过简化已有操作步骤和实现部分功能批处理,提高作业效率;将数据预处理、编辑、质量检查及外业核查都整合到ArcMap界面中,实现一体化处理,降低培训投入和作业难度。研究结果表明,ArcGIS Add-in适合于测绘生产中的快速应用开发;研发成果有助于提高测绘生产效率和成果质量,节约生产成本。     

地质雷达探测精度的分析与研究

随着地理信息技术逐步提高,地质雷达在地质勘查、交通工程和结构探测等传统领域得到进一步发展,其应用范围还扩展到地下管线探测、考古与文物保护、地理国情监测、土地资源与环境监测等与测绘科学有关的专业技术领域。目前,我国关于地质雷达探测没有统一的技术标准与规范,为了填补空白,本文通过大量实验验证地质雷达的探测精度,并作为编写吉林省地方标准《地质雷达探测测绘技术规程》的依据。     

地质雷达+三维测量内窥镜的城市道路病害检测与应用

城市道路病害体作为城市安全的重要隐患,具有隐蔽性、突发性等特点,需及时予以检测和处理。地质雷达利用电磁波反射确定地下介质分布,以其无损、快捷及浅层高分辨率优势广泛应用于城市道路病害检测中,但要对病害体作进一步处理,需要对病害体做进一步精细勘测。本文利用地质雷达在道路病害检测中的优势,结合三维测量内窥镜技术的实时视频和测量功能,实现道路地下病害体的准确定位和精准测量,为后续防治和治理提供有用数据。     

星载雷达Radarsat数据产品选择及在地质探测中的应用

结合生产科研实践,在论述星载雷达成像方式及Radarsat 数据产品主要特点的基础上,针对以岩性识别和构造分析为主要研究内容的地质探测领域,着重讨论分析了波束模式、视角范围、卫星姿态、时相、数据处理级别等影响数据产品选择的主要因素,并提出地质探测领域Radarsat 数据产品的选择原则及参考意见,供广大遥感地质工作者在充分利用这一新型遥感数据源时参考。     

横断山脉机载SAR-X波段影像数据处理分析

针对机载SAR数据的X波段成像处理进行研究,设计出一种用于生产实践的快速有效的流程方案。介绍雷达信号成像处理的主要步骤,并根据SAR成像软件需求,编写出自动提取主要雷达参数以及用于质量检查的软件。项目生产实践表明,该成像处理流程过程简捷,使用方便,能有效提高生产效率,缩短生产周期,符合实际的大规模生产需求。     

结合正则化K-SVD和Hampel滤波的探地雷达数据重建

为减弱因地形起伏造成的探地雷达数据间的能量差异,保证探地雷达图像解译和识别的准确性,本文提出了一种正则化K-SVD字典学习和Hampel滤波算法相结合的探地雷达数据重建方法。试验采用正则化K-SVD字典学习对探地雷达信号进行能量均衡,利用Hampel滤波算法剔除均衡后的信号异常值,并对均衡后的信号进行二维可视化,从而完成探地雷达图像重建。对比试验表明,本文方法不但可以均衡原始的探地雷达信号,而且其均衡后的信号更加符合探地雷达信号传播规律,可以保证单道数据信号的质量;其重建的图像效果更好,在探地雷达图像重建方面具有较好的实用价值。     

Efficient Calculation of Born Scattering for Fixed-Offset Ground-Penetrating Radar Surveys

A formulation is presented for efficient calculation of linear electromagnetic scattering by buried penetrable objects, as involved in the analysis of fixed-offset ground-penetrating radar (GPR) systems. The actual radiation patterns of the GPR antennas are incorporated in the scattering calculation by using their plane-wave transmitting and receiving spectra     

车载探地雷达地下目标实时探测法

中国的城镇化加快了地下空间大规模开发与利用的进程。摸清地下空间目标的分布状况,保障城市可持续发展和地下空间资源的永久利用,是维护未来城市安全中的重要任务。探地雷达(GPR)凭借其数据采集速度快、成像分辨率高、无损检测等优点在地下空间资源调查中得以广泛应用。但仍存在GPR数据地下目标识别不准确、自动化程度低等缺陷,自动检测GPR数据中的地下目标或目标缺陷仍然是一个亟待解决的难题。为此,本文分析并确定了GPR影像中可进行识别的城市道路地下空间的7类典型目标(如雨水井、电缆等)。并根据其反射信号特征,标记了GSSI SIR30设备以400 MHz波段采集的GPR数据中的典型地下目标,构建了GPR地下目标样本库,共包含7类总数为3033个。通过迁移学习的方法,精调预训练后的Darknet53网络参数,通过端到端的YOLOV3检测方法完成地下目标的自动识别与定位。最后,利用深圳福田区彩田路GSSI SIR30装备以400 MHz波段采集的GPR数据进行试验验证。试验结果表明,本文提出的基于深度学习的地下目标探测方法对城市典型地下目标的检测精度和召回率达到85%以上,检测速度达到了16帧/s,能够有效探测GPR数据中的城市地下目标。     

一种WiFi距离交会加权融合定位算法

基于距离交会的WIFI室内定位算法受环境的影响,距离反演精度较低导致定位误差较大,不同距离反演模型对定位误差影响特性存在差异。考虑到GPR距离反演模型过度平滑引起定位结果扎堆的缺陷和传统损耗模型反演精度过低引起定位结果误差较大的缺陷,提出一种基于GPR预测模型和损耗模型的加权融合定位算法。实验结果表明:该融合算法能够有效提高定位精度并明显改善基于GPR模型定位算法的定位结果扎堆现象。     

Nondestructive Sensor Using Microwaves From Laser Plasma by Subnanosecond Laser Pulses

Conventional ground-penetrating radar (GPR) requires large-aperture antennas or long-span measurements to survey a remote location precisely. We propose a laser-driven GPR (LGPR) as a new detection method. LGPR uses microwaves from laser-produced plasmas as remote transmitters and can survey a remote location using a compact instrument. We performed numerical simulations to investigate the radiation mechanism of microwaves from laser plasmas and confirmed the pulsewidth of the laser suitable for LGPR. Experiments with subnanosecond pulse lasers clarified the feasibility and detection performance of LGPR.     

Gaussian processes uncertainty estimates in experimental Sentinel-2 LAI and leaf chlorophyll content retrieval

ESA’s upcoming Sentinel-2 (S2) Multispectral Instrument (MSI) foresees to provide continuity to land monitoring services by relying on optical payload with visible, near infrared and shortwave infrared sensors with high spectral, spatial and temporal resolution. This unprecedented data availability leads to an urgent need for developing robust and accurate retrieval methods, which ideally should provide uncertainty intervals for the predictions. Statistical learning regression algorithms are powerful candidats for the estimation of biophysical parameters from satellite reflectance measurements because of their ability to perform adaptive, nonlinear data fitting. In this paper, we focus on a new emerging technique in the field of Bayesian nonparametric modeling. We exploit Gaussian process regression (GPR) for retrieval, which is an accurate method that also provides uncertainty intervals along with the mean estimates. This distinct feature is not shared by other machine learning approaches. In view of implementing the regressor into operational monitoring applications, here the portability of locally trained GPR models was evaluated. Experimental data came from the ESA-led field campaign SPARC (Barrax, Spain). For various simulated S2 configurations (S2-10m, S2-20m and S2-60m) two important biophysical parameters were estimated: leaf chlorophyll content (LCC) and leaf area index (LAI). Local evaluation of an extended training dataset with more variation over bare soil sites led to improved LCC and LAI mapping with reduced uncertainties. GPR reached the 10% precision required by end users, with for LCC a NRMSE of 3.5–9.2% (r²: 0.95–0.99) and for LAI a NRMSE of 6.5–7.3% (r²: 0.95–0.96). The developed GPR models were subsequently applied to simulated Sentinel images over various sites. The associated uncertainty maps proved to be a good indicator for evaluating the robustness of the retrieval performance. The generally low uncertainty intervals over vegetated surfaces suggest that the locally trained GPR models are portable to other sites and conditions.     

CMP Antenna Array GPR and Signal-to-Clutter Ratio Improvement

Ground-penetrating radar (GPR) is recognized as a promising sensor for detecting buried landmines. In this case, the GPR antenna(s) must be elevated above the ground. However, this requirement results in heavy surface clutter. It is therefore necessary to overcome the effect. A commonly used procedure of time gating and background averaging cannot suit to small shallow nonmetallic landmine beneath a rough ground surface. In this letter, we proposed techniques to enhance the target signal through common midpoint (CMP) antenna array and data processing techniques, including velocity spectrum and CMP multifold stacking. The method has been tested using experiment data over a rough ground under which small plastic antipersonnel landmines is shallowly buried. The result shows the signal-to-clutter ratio was dramatically improved.     

冲击型探地雷达回波信号的等效采样方法研究

提出了一种基于等效时间采样方法的冲击型探地雷达回波信号高速采样系统，设计实现了等效时间采样的关键电路，包括步进采样脉冲发生器、采样门电路。实验证明了使用该方法采样回波信号的有效性。     

Measurement of soil water content using ground-penetrating radar: a review of current methods

Soil water content (SWC) is a crucial parameter in ecology, agriculture, hydrology, and engineering studies. Research on non-invasive monitoring of SWC has been a long-lasting topic in these fields. Ground penetrating radar (GPR), a non-destructive geophysical technique, has the advantages of high resolution, deep detection depth, and high efficiency in SWC measurements at medium scale. It has been successfully applied in field investigations. This paper summarizes the recent progress in developing GPR-based SWC measurement methods, including reflected wave, ground wave, surface reflection, borehole GPR, full waveform inversion, average envelope amplitude, and frequency shift methods. The principles, advantages, limitations, and applications of these methods are described in detail. A comprehensive technical framework, which comprises the seven methods, is proposed to understand their principles and applicability. Two key procedures, namely, data acquisition and data processing, are emphasized as crucial to method applications. The suitable methods that will satisfy diverse application demands and field conditions are recommended. Future development, potential applications, and advances in hardware and data processing techniques are also highlighted.     

Estimation of glacier depth and moraine cover study using ground penetrating radar (GPR) in the Himalayan region

Himalayan region has one of the largest concentrations of mountain glaciers whose areal extent is changing due to global warming. In order to assess future changes in glacier extent due to global warming, information about glacier depth and debris cover is important. In this paper, application of ground penetrating radar (GPR) is discussed to assess glacier depth and debris cover. This investigation was carried out at Patseo and Samudratapu glaciers in Himachal Pradesh (West Himalaya). Antennas of frequency 50 and 100 MHz have been used for glacier depth and 500 MHz for moraine depth estimation. GPR signatures of glaciers were collected and further analyzed using velocities of electromagnetic waves in different media. The depth of Patseo glacier was estimated as 40 m. However, depth of the larger Samudra Tapu glacier could not be estimated using 50 and 100 MHz antennas. The depth of moraines was estimated using 500 MHz antenna and it varies from 0.35 cm to 0.85 cm for medial and around 1–2 m for lateral moraine at the experimental site.