基于GPS和大气传输模型的InSAR大气改正方法研究

利用GPS数据改正InSAR大气影响中,GPS站网的低空间密度是限制改正精度的一个主要因素.文中引入大气传输模型（ATM）来考虑大气状态在时间上的演化,并兼顾了风向的估计,把GPS-ZWD（GPS湿延迟）时间序列观测值转换为空间上分布比较稠密的GPS-ZWD网络,然后利用该稠密网络在空间上内插产生水汽延迟图,来更好地模拟InSAR影像获取时刻的水汽场,提高大气改正精度.实验结果表明,在研究地区有限的数据条件下（即只有6个GPS点的情况下）,GPS+ATM算法在重现大气信号能力方面比单纯的使用影像获取时刻的GPS-ZWD数据要强,并且其对长波的大气误差去除更明显;用来做实验的三幅差分干涉图中,GPS+ATM算法对两幅以长波信号为主的干涉图中的大气影响分别降低了21.7%和22.6%,比仅使用SAR过境时刻GPS-ZWD数据时的结果分别改进了4.5%和8.7%.而对以短波信号为主的干涉图没有明显提高.     

福建省泉州地区断裂带地壳形变PS-InSAR监测

PS-InSAR技术能够有效降低常规差分干涉雷达受时间失相干、空间失相干和大气效应的影响,在常规D-InSAR不能形成干涉条纹的情况下,可利用时间序列的雷达影像和相位稳定的永久散射体目标点获取离散的PS像素点形变速率。以福建省泉州地区的断裂带为研究对象,对1996-1999年的22景ERS SAR数据进行PS-InSAR处理,得出研究区主要断裂的视线向位移速率为3~5mm/a,表明该区断裂仍有一定的活动性,具有潜在的地震危险。     

时序InSAR技术及其在京西北试验区微小形变的应用研究

时序InSAR技术是近些年发展起来的一种新的InSAR测量技术.其中PS-InSAR技术是通过分析高相干的永久散射体相位变化信息提取形变,受时间和空间基线的限制小,该方法需要假设形变特征为匀速,同时需要大量的SAR数据（25景）来估算大气效应贡献值;短基线技术（SBAS）可以降低几何去相干的影响,同时较短基线使DEM误差的敏感性大大降低,但该方法通过一定大小的窗体计算相干性,并据此来选择时间序列稳定点,窗体操作降低了被选像元的分辨率,但抑制了噪声相位的影响;干涉图叠加方法（interferogram stacking）是将多幅差分干涉图进行叠加,提高结果中形变信息对大气干扰的相对精度,可以获取大区域的连续形变场;CR-InSAR技术将人工角反射器作为观测对象,通过建立CR点上的形变模型,实现对重点目标如滑坡、水库和断层的形变监测.     

利用GPS和InSAR数据反演2011年日本东北MW9.0地震断层的同震滑动分布

本文首先对Envisat/ASAR数据进行干涉处理, 获取2011年日本东北M_W9.0地震的地表InSAR同震形变场; 然后通过对InSAR同震形变数据重采样方法的深入分析, 选择条纹率法结合干涉图的空间相干性对InSAR同震形变数据进行重采样; 最后基于弹性半空间位错模型, 联合InSAR与GPS形变数据, 采用最小二乘法反演发震断层的滑动分布. 研究结果表明: 考虑相干性的条纹率重采样方法, 更适用于形变场中存在除断层外的有限边界、 且形变场范围较大的InSAR数据重采样处理; 断层滑动主要发生在地表以下50 km范围内, 最大滑动量为49.9 m, 矩张量为4.89×1022 N·m, 所对应的矩震级为M_W9.1, 与地震学反演的结果比较吻合.      

SAR遥感图像在汶川地震灾害识别中的应用

汶川地震发生后,受阴雨天气的影响,光学遥感影像在救灾决策中的作用受到了很大的限制,而SAR图像由于其全天候的特点成为这次抗震救灾前期遥感信息保障十分重要的数据源.采用ENVISAT的ASAR作为数据源,利用多时相的雷达数据的幅度及相位信息对映秀及周边地区做了地震灾害识别,其中利用震前震后的幅度图像做比值变化检测,在映秀镇及紫坪铺水库等山区取得了较好的效果;利用相位信息做干涉处理得到的相干图像,经过失相干分析,发现建筑物的破坏等级与相干系数变化指数的大小高度相关.比较这两种方法,在都江堰等平原地区由于失相干现象不像山区那么严重,并且利用比值处理可以去除部分空间失相干及系统热噪声等带来的干扰因素,可以成为幅度图像的有益补充.结果表明,结合SAR幅度影像和干涉相干影像,可以在地震灾害评估中取得更好效果.随着极化干涉雷达技术的日益成熟,多时相幅度信息、相位信息等多特征SAR影像信息的融合会在救灾决策中发挥更大的作用.     

基于子带干涉测量技术的巴基斯坦地震形变获取研究

2013年9月24日发生在巴基斯坦俾路支省(Balochistan)境内阿瓦兰县(Awaran)的MW7.7级地震,在地表产生了最大达10m的滑动量.利用TerraSAR-X短波雷达数据获取的InSAR同震形变场产生了密集且大范围的干涉条纹,给后续的相位解缠带来困难.而子带干涉法是一种无需或只需进行少量相位解缠,即可获得绝对相位差的新方法.其主要思路是通过缩减带宽以增长波长,从而减少干涉条纹数,降低解缠难度或不需解缠直接得到绝对相位差.但由于带宽的缩减,导致噪声的增大和旁瓣带来的额外干扰,使干涉图质量下降,因此在子带干涉参数选取、噪声滤波以及处理流程等方面需要特殊处理,特别是子带的中心频率和带宽的选取会很大程度地影响测量精度.首先选取典型DEM实验区,以干涉图相干性和误差为评价指标,利用逐步参数选取法,研究相关参数对子带干涉测量的影响,制定最优的参数方案,认识参数选取的原则和方法.在此基础上,将子带干涉应用于巴基斯坦地震的同震形变场获取.最后,将子带干涉、Landsat 8光学影像的交叉频谱相关法、offset-tracking、常规DInSAR获取的同震形变场进行比较,并与模型拟合的形变场进行对比分析.结果表明,子带干涉虽然会受失相干的影响,其提取的形变场范围相较于Landsat 8和offset-tracking有所缺失,但在共同覆盖的区域其精度和噪声水平更优,相比较于常规DInSAR,更适用于条纹密集和形变量大的地区.     

通过InSAR与GPS数据融合获取汶川地震同震三维形变场

针对In SAR与GPS两类独立的观测数据,利用广义测量平差理论中方差分量估计法,合理分配权重,有效地融合了这两类观测数据,从而估算出了地表在三维方向上的形变场。以四川汶川地震为例,利用In SAR干涉测量结果和一定数量的GPS观测值,通过该方法获取了地震断层两侧高相干区域上三维形变场,清晰地显示了汶川地震的逆冲和右旋走滑分量的位置分布整体特征。结果表明,在EW、SN和UD方向上地表形变量与GPS结果能够很好地吻合,融合结果在三维方向上的均方根误差均不超过5cm,证明了该方法能够得到精度较高的地震同震三维形变场,也揭示了利用方差分量估计法对相互独立数据之间有效融合的可行性。     

星载重轨极化干涉SAR反演森林植被高度

机载双天线极化干涉SAR反演植被参数得到广泛应用,并取得较好的反演精度.然而对于星载的单天线极化干涉SAR系统,只能采取重轨方式获得极化干涉数据,且该数据受到较为严重的时间去相干的影响.因此,利用星载极化干涉SAR数据反演植被参数不得不考虑时间去相干的影响.由于时间去相干的影响,经典RVoG模型已经被证明对植被区域的极化干涉SAR数据进行反演的结果有较严重的偏差.针对这一问题,基于RVoG模型的TD-RVoG模型被提出,用于消除时间去相干的影响,但该模型未知参数太多,难以应用于单基线极化干涉数据反演植被高度.在原始TD-RVoG模型的基础,提出一种新的运动时间去相干模型,减少了未知参量个数,并采用三阶段法反演植被高度.利用星载重轨极化ALOS/PALSAR数据进行模型验证,结果显示新模型整体反演结果误差在1.5 m以内.     

基于方差分量估计的多源InSAR数据自适应融合形变测量

近年来,合成孔径雷达干涉测量(Interferometric Synthetic Aperture Radar,InSAR)技术在地面沉降监测方面展现了巨大的应用潜力,但受其重访周期和一维形变测量能力的限制,仅利用单一轨道卫星观测数据很难揭示真实的地表形变特征及其演化规律.随着在轨运行的SAR卫星系统不断增加,使得融合相同时间段内覆盖同一区域的多源多轨道InSAR数据成为可能.然而目前普遍采用的多源InSAR数据融合方法均为针对大尺度形变监测设计,或者忽略南北向形变甚至水平形变,容易造成误判.为此,本文对经典小基线集(Small Baseline Subset, SBAS)时序InSAR分析方法进行改进,在其形变反演模型中加入东西向和南北向形变参数,采用方差分量估计方法解算多源观测数据验后方差,通过迭代精化确定权重矩阵,从而获得形变参数的最优估值.使用美国南加州地区的ALOS PALSAR和ENVISAT ASAR数据开展实验,利用南加州综合GPS网(SCIGN)位于研究区域内的9个站点观测数据进行验证,结果表明本文方法得到的融合形变测量结果在垂直向上能够准确反映地表形变波动,周期性与GPS观测比较一致;同时,融合得到的三维形变场显示南加州洛杉矶地区存在不可忽略的水平形变,东西向形变测量精度略高于南北向.因此,基于方差分量估计的多源InSAR融合方法在提高形变测量时间序列连续性的同时,能够更准确地反演研究区域三维形变特征.     

ERS卫星雷达干涉测量:1999年台湾集集大地震震前和同震地表位移

1999年集集大地震(Mw=7.6)是20世纪以来台湾岛内最大的地震.在本研究中,5个不同时间获取的ERS-1/2卫星合成孔径雷达图像被组合,并被处理成多个差分干涉图,以此来考查与该地震相关的地表位移场.这些差分干涉图(空间分辨率为50m×50m)详细地揭示了沿台湾西海岸震中附近150km2陆地范围内的震前和同震地表形变.几个具有较长时间(2-3a)跨度的震前干涉图呈现出高度的相关性和一致性,并均显示出约1个干涉条纹,相当于沿kd 雷达视线方向的地表位移在空间尺度上呈相对总量为28.3mm的分布;而具有短时间跨度(0.5-la)的同震干涉图呈现出显著的反映地震形变的干涉条纹(9-10个条纹),相当于沿雷达视线方向的地表位移在空间尺度上呈相对总量为25.5-28.3cm的分布,这些由干涉处理所得到的形变观测结果与GPS测量结果吻合程度很高(相关系数达0.95),证实了干涉形变精度可达1cm.特别地,这些高分辨率的同震形变干涉结果可以为该地震的物理机制解释提供极好的观测数据,同时也展示了使用短波段InSAR监测长时间累积的微小震前地表位移是可能的.     

Common-offset common-reflection-surface attributes estimation with differential evolution

Common-reflection surface is a method to describe the shape of seismic events, typically the slopes (dip) and curvature portions (traveltime). The most systematic approach to estimate the common-reflection surface traveltime attributes is to employ a sequence of single-variable search procedures, inheriting the advantage of a low computational cost, but also the disadvantage of a poor estimation quality. A search strategy where the common-reflection surface attributes are globally estimated in a single stage may yield more accurate estimates. In this paper, we propose to use the bio-inspired global optimization algorithm differential evolution to estimate all the two-dimensional common-offset common-reflection surface attributes simultaneously. The differential evolution algorithm can provide accurate estimates for the common-reflection surface traveltime attributes, with the benefit of having a small set of input parameters to be configured. We apply the differential evolution algorithm to estimate the two-dimensional common-reflection surface attributes in the synthetic Marmousi data set, contaminated by noise, and in a land field data with a small fold. By analysing the stacked and coherence sections, we could see that the differential evolution based common-offset common-reflection surface approach presented significant signal-to-noise ratio enhancement.     

时变地震谱估计的非参数方法评价及应用

针对工程中常见的非平稳地震动激励,进一步建立了时变功率谱估计的理论框架。首先,在多个样本情形下,采用信号处理中的时频分析方法对非平稳激励的时变谱估计理论进行了讨论。当激励样本数量有限时,对Priestley提出的估计方法进行了介绍。其次,以地震工程中常用的Kanai-Tajimi谱模型为目标,分别对均匀调制与一般调制谱的估计结果以及不同估计方法的精度与收敛性进行评价后,提出了能够方便工程应用的建议。最后,针对SMART-Ⅰ(Strong Motion Array in Taiwan,Phase Ⅰ)密集台阵第45次地震记录的多组三维样本,揭示了EW、NS、UD三个方向时变谱的典型特征以及各方向间的时变相干性。结果表明:与短时Fourier变换相比,复Morlet小波与广义谐和小波估计谱具有较好的精度与收敛性,Priestley方法估计单个样本具有优势;SMART-Ⅰ台阵地震动具有强度和频率的双重非平稳性,三个方向具有弱相干性。研究结论可为拓展谱估计理论的工程应用以及后续大跨结构多维多点非平稳地震响应的分析提供参考。     

WAVELET ESTIMATION USING THE MULTITAPER METHOD1

An accurate estimate of the seismic wavelet on a seismic section is extremely important for interpretation of fine details on the section and for estimation of acoustic impedance. In the absence of well-control, the recognized best approach to wavelet estimation is to use the technique of multiple coherence analysis to estimate the coherent signal and its amplitude spectrum, and thence construct the seismic wavelet under the minimum-phase assumption. The construction of the minimum-phase wavelet is critically dependent on the decay of the spectrum at the low-frequency end. Traditional methods of cross-spectral estimation, such as frequency smoothing using a Papoulis window, suffer from substantial side-lobe leakage in the areas of the spectrum where there is a large change of power over a relatively small frequency range. The low-frequency end of the seismic spectrum (less than 4 Hz) decays rapidly to zero. Side-lobe leakage causes poor estimates of the low-frequency decay, resulting in degraded wavelet estimates. Thomson's multitaper method of cross-spectral estimation which suffers little from side-lobe leakage is applied here, and compared with the result of using frequency smoothing with the Papoulis window. The multitaper method seems much less prone to estimating spuriously high coherences at very low frequencies. The wavelet estimated by the multitaper approach from the data used here is equivalent to imposing a low-frequency roll-off of some 48 dB/oct (below 3.91 Hz) on the amplitude spectrum. Using Papoulis smoothing the equivalent roll-off is only about 36 dB/oct. Thus the multitaper method gives a low-frequency decay rate of the amplitude spectrum which is some 4 times greater than for Papoulis smoothing. It also gives more consistent results across the section. Furthermore, the wavelet obtained using the multi-taper method and seismic data only (with no reference to well data) has more attractive physical characteristics when compared with a wavelet extracted using well data, than does an estimate using traditional smoothing.     

基于深度卷积神经网络的地震数据局部信噪比估计

估计地震数据的信噪比对于地震数据的处理和解释具有重要作用.以往估计地震数据信噪比的方法都需要分离数据中的有效信号和噪声,然后再估计相应的信噪比.这些估计方法的精度严重依赖信号估计方法或噪声压制方法的有效性,往往存在偏差.本文提出一种估计地震数据局部信噪比的深度卷积神经网络模型,通过迭代训练优化参数,构建从含噪地震数据到其信噪比的特征映射.然后使用该神经网络完成信噪比的推理预测,不需要分离地震数据中的有效信号和噪声.模拟数据和实际资料的处理结果都表明,本文的方法可以准确而高效地估计局部地震数据的信噪比,为地震数据质量的定量评价提供依据.     

Spatial coherence of seismic wave fields across an alluvial valley (weak motion)

The loss of coherence of seismic waves, even over small distances, can become significant and consequently important for engineering applications. This coherence loss depends on several parameters (frequency, inter-station distance), but their dependencies are not well understood yet. We show the results of a detailed analysis of the spatial variability of the coherence between two signals. This analysis is based on a simple model which is an exponential function of inter-station distance and frequency. Data from a temporary network of 36 weak-motion instruments installed at the EURO-SEISTEST site, north-east of Thessaloniki (Greece), is used in this work. The data offers the unique possibility to study the loss of coherence over a wide range of distances, as the inter-station distances are between 8 m and 5488 m. We test the influence on the coherence of the length of the time-window of the signals, of the type of the waves present in the time-window and of the common energy of the signals. We also show that, at least at this particular site, the loss of coherence with distance is probably marked by a "cross over" distance, distinguishing two different ranges: one for inter-station distances up to 100 m and the other above 100 m. Finally, we find that the coherence determined from noise recordings behaves in a rather similar way to the one determined from coda-waves and more stationary (longer) signals. Therefore, noise can be useful for a rough, but quick estimation of the loss of coherence, at least for inter-station distances larger than 100 m.     

Windowless Q-factor tomography by the instantaneous frequency

The estimation of the Q factor of rocks by seismic surveys is a powerful tool for reservoir characterization, as it helps detecting possible fractures and saturating fluids. Seismic tomography allows building 3D macro-models for the Q factor, using methods as the spectral ratio and the frequency shift. Both these algorithms require windowing the seismic signal accurately in the time domain; however, this process can hardly follow the continuous variations of the wavelet length as a function of offset and propagation effects, and it is biased by the interpreter choice. In this paper, we highlight some drawback of signal windowing in the frequency-shift method, and introduce a tomographic approach to estimate the Q factor using the complex attributes of the seismic trace. We show that such approach is particularly needed when the dispersion is broadening the waveforms of signals with a long wave-path. Our method still requires an interpretative event picking, but no other parameters as the time window length and its possible smoothing options. We validate the new method with synthetic and real data examples, involving the joint tomographic inversion of direct and reflected signals. We show that a calibration of the frequency-shift method is needed to improve the estimation of the absolute Q factor, otherwise only relative contrasts are obtained.     

非稳态地震记录时变子波估计

地震子波估计是地震资料处理和解释中的一个关键问题,子波估计的可靠性会直接影响反褶积和反演的准确度.现有的子波估计方法分为确定型和统计型两种类型,本文通过结合这两类方法,利用确定型的谱分析法和统计型的偏度最大化方法,分别提取时变子波的振幅和相位信息,得到估计的时变子波.这种方法不需要对子波进行任何时不变或相位等的假设,具有对时变相位的估计能力.进而利用估计时变子波进行非稳态反褶积,提高地震记录的保真度,为精细储层预测和描述提供高质量的剖面.理论模型试算验证了方法的可行性,通过实际地震资料的处理应用,表明该方法能有效地提取出子波时变信息.     

Coherence among climate signals, precipitation, and groundwater

Climate signals may affect groundwater level at different time scales in different geographical regions, and those patterns or time scales can be estimated using coherence analysis. This study shows that the synthesis effort required to search for patterns at the physical geography scale is possible, and this approach should be applicable in other regions of the world. The relations between climate signals, Southern Oscillation Index, Pacific Decadal Oscillation, North Atlantic Oscillation, North Pacific Pattern (SOI, PDO, NAO, and NP), precipitation, and groundwater level in three geographical areas of Wisconsin are examined using a three-tiered coherence analysis. In the high frequency band (<4(-1) cycles/year), there is a significant coherence between four climate signals and groundwater level in all three areas. In the low frequency band (>8(-1) to ≤23(-1) cycles/year), we found significant coherence between the SOI and NP signals and groundwater level in the forested area, characterized by shallow wells constructed in sand and gravel aquifers. In the high frequency band, there is significant coherence between the four climate signals and precipitation in all three areas. In the low frequency band, the four climate signals have effect on precipitation in the agricultural area, and SOI and NP have effect on precipitation in the forested and driftless areas. Precipitation affects groundwater level in all three areas, and in high, low and intermediate frequency bands. In the agricultural area, deeper aquifers and a more complex hydrostratigraphy and land use dilute the effect of precipitation on groundwater level for interdecadal frequencies.     

A comparison of windows and maximum entropy methods for MT transfer function estimation

The ability of the Maximum Entropy Spectral Estimate (MEM) to handle magnetotelluric signals was investigated. To this end simulations of naturally occurring signals and real data were spectral analyzed both by a standard FFT technique and by MEM. The method developed for the simulation of the time series, provides accurate amplitudes and phase, and turns out to be a good test procedure for spectral analysis methods, as they apply to MT signal processing. The final estimation of the apparent resistivity was better achieved by the FFT technique. Oscillations were observed in the estimation of the apparent resistivities by MEM.     

Waveform Retrieval and Phase Identification for Seismic Data from the CASS Experiment

The little destruction to the deployment site and high repeatability of the Controlled Accurate Seismic Source (CASS) shows its potential for investigating seismic wave velocities in the Earth's crust. However, the difficulty in retrieving impulsive seismic waveforms from the CASS data and identifying the seismic phases substantially prevents its wide applications. For example, identification of the seismic phases and accurate measurement of travel times are essential for resolving the spatial distribution of seismic velocities in the crust. Until now, it still remains a challenging task to estimate the accurate travel times of different seismic phases from the CASS data which features extended wave trains, unlike processing of the waveforms from impulsive events such as earthquakes or explosive sources. In this study, we introduce a time-frequency analysis method to process the CASS data, and try to retrieve the seismic waveforms and identify the major seismic phases traveling through the crust. We adopt the Wigner-Ville Distribution (WVD) approach which has been used in signal detection and parameter estimation for linear frequency modulation (LFM) signals, and proves to feature the best time-frequency convergence capability. The Wigner-Hough transform (WHT) is applied to retrieve the impulsive waveforms from multi-component LFM signals, which comprise seismic phases with different arrival times. We processed the seismic data of the 40-ton CASS in the field experiment around the Xinfengjiang reservoir with the WVD and WHT methods. The results demonstrate that these methods are effective in waveform retrieval and phase identification, especially for high frequency seismic phases such as PmP and SmS with strong amplitudes in large epicenter distance of 80–120 km. Further studies are still needed to improve the accuracy on travel time estimation, so as to further promote applicability of the CASS for and imaging the seismic velocity structure.