共查询到19条相似文献，搜索用时 562 毫秒
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Mogi模型在长白山天池火山区的应用 总被引：6，自引：0，他引：6
文中首先介绍了Mogi模型的阻尼最小二乘反演,得出应用形变资料联合反演压力源参数的公式,再指出用等效源半径反演时不同初始值对反演结果的影响,说明选择合适的初始值可以方便地得到可靠的反演结果。然后用此方法反演长白山天池火山区压力源的大小和位置参数。采用垂直和水平位移的联合反演,数据为2002—2005年共4期的水准和GPS观测资料,最后结合其它观测资料,分析近年来岩浆可能的活动特征。结果显示岩浆的位置在发生变化,体积增量逐年减小,表明火山岩浆在2002—2005年的活动逐年减弱 相似文献
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基于三角位错的断层自动剖分方法,联合ALOS-2 InSAR和GPS同震位移数据反演了2015年尼泊尔MW7.8地震的发震断层参数及滑动分布.反演中基于赫尔默特方差分量估计方法确定InSAR、GPS水平向与垂直向的3种观测位移数据的相对权比.反演结果显示,方差分量估计方法定权得到的最大滑动量5.5 m,大于验前方差定权给出的5.1 m的结果,同时前者显示同震破裂沿东南方向传播至接近MW7.3最大余震区域,然后分别继续向北和东南传播约30 km,并形成一个滑动空区（slip gap）,而后者的结果没有表现出这种显著的滑动空区特征.方差分量估计定权得到的滑动模型能更好地解释观测到的InSAR同震形变场,其拟合残差标准差较验前方差定权的结果减小了2.5 cm,GPS的东和北分量的残差标准差分别减小了0.4 cm和0.9 cm.与两种不同的基于矩形位错的方法相比,利用方差分量估计的三角位错断层自动剖分方法的滑动误差均值和标准差相对最小,其中均值为0.037 m,标准差为0.028 m,表明该方法得到的滑动模型具有相对更好的无偏性和有效性. 相似文献
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利用最小二乘配置进行地壳形变分析,其结果的合理性关键在于经验协方差函数的拟合.考虑到观测数据存在粗差的情况,提出基于观测值中位数初值的抗差最小二乘配置方法和基于中位参数法的抗差最小二乘配置方法.两种方法首先分别利用观测值中位数给出观测值初始权阵以及利用中位参数法给出最小二乘配置初始解,然后均在给定协方差函数参数初始值的情况下,应用合适的等价权进行抗差估计并通过迭代计算,最终获得稳健的协方差函数参数估值及最小二乘配置解.利用本文提出的两种方法以及传统方法分别对庐山地震的GPS垂直位移数据和意大利L'Aquila地震的InSAR同震位移数据进行处理分析.结果表明:相对传统方法,基于观测值中位数初值的抗差最小二乘配置方法效果更好,更具稳健性. 相似文献
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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. 相似文献
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高精度静态卫星重力场模型在全球海洋环流研究、全球/区域数字高程基准面确定等领域有重要应用,本文研究仅利用GOCE卫星和联合GRACE卫星观测数据确定高精度高阶次静态重力场模型.利用GOCE卫星全周期高精度引力梯度分量(Vxx、Vyy、Vzz和Vxz)观测值基于直接最小二乘法构建300阶次的SGG(Satellite Gravity Gradiometry)法方程,并利用卫星跟踪卫星观测值基于点域加速度法构建130阶SST(Satellite-to-Satellite Tracking)法方程,然后利用方差分量估计联合SGG和SST法方程确定300阶次纯GOCE卫星重力场模型GOSG02S.利用全周期GRACE观测数据由动力学方法解算了180阶次的SWPU-GRACE2021S模型,并将其对应法方程与GOCE卫星法方程联合解算了GRACE和GOCE的联合模型WHU-SWPU-GOGR2022S.分别基于XGM2019模型和GPS水准数据对本文解算的三个模型GOSG02S、SWPU-GRACE2021S... 相似文献
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永久散射体雷达干涉(PSI)技术及其应用于区域地表形变监测已成为雷达遥感领域的研究热点之一.使用单一卫星平台所获取的单侧视SAR影像时间序列进行PSI分析,仅能获取沿雷达视线(LOS)方向的一维地表位移信息.本文提出了基于多平台永久散射体雷达干涉提取三维地表形变速度场的模型与算法,其基本策略是:首先针对每一卫星平台的SAR影像时间序列进行PSI分析,并计算各地面目标沿LOS向的位移速度值,然后联合各平台所对应的LOS向位移速度值进行建模,并基于最小二乘方法解算各地面目标的三维位移速度分量.实验选取天津市西北部作为测试区,使用2007—2010年所获取的39幅TerraSAR-X影像、23幅ENVISAT ASAR影像和16幅ALOS PALSAR影像进行分析,经联合解算得到了该测试区域的垂直位移速度场以及南北向和东西向水平位移速度分量.与地面水准和已有GPS观测结果对比分析表明:多平台PSI的垂直位移速度场精度可达毫米级,而其水平位移速度分量与已有GPS结果基本一致.多平台PSI分析无需引入任何外部形变参考信息,便可以实现形变场的偏差校准和三维形变场的恢复. 相似文献
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利用GPS垂直位移反演区域陆地水储量变化(TWSC)属于典型的病态问题,其关键是如何进行稳定求解并提高反演结果的精度和可靠性.本文引入TSVD-Tikhonov组合正则化方法对利用GPS垂直位移反演区域TWSC的病态问题进行求解,并以四川省TWSC反演为例进行分析与验证.首先,通过数值模拟对TSVD、Tikhonov和TSVD-Tikhonov正则化方法采用不同正则化参数选取策略(RMSE最小准则、GCV法和L-curve法)进行反演,结果显示基于TSVD-Tikhonov正则化反演的TWSC比单独使用TSVD或Tikhonov正则化反演结果的精度和可靠性更高,这三种正则化方法反演2005年1月至12月的TWSC差值的平均STD分别为14.97 mm、7.03 mm和5.04 mm.其次,利用中国地壳运动观测网络(CMONOC)的72个GPS测站的垂直位移数据,基于TSVD-Tikhonov正则化反演了四川省2010年12月至2021年2月的TWSC时间序列,结果表明GPS反演的TWSC与GRACE/GFO Mascon模型(JPL、CSR和GSFC)的空间分布特征及季节性变化符合较好... 相似文献
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联合高精度的GPS水平位移观测和高密度的PS-InSAR雷达视线位移测量,实现地表三维形变的精确反演.本文在准确计算卫星轨道方位角基础上,使用GPS观测位移与星载雷达LOS方向形变的投影转换模型,将雷达LOS方向形变转换为垂直方向位移,并基于地面GPS与SAR影像PS目标联合构建形变监测网,采用参数平差算法估计区域地表形变场.以地质构造活动极其活跃的台湾岛及其西南屏东高雄地区为例,联合屏东地区48个GPS监测台站与雷达PS目标,监测该地区从1995-1999年间由于板块构造挤压运动和地下水抽取导致的三维地表形变.结果表明,该地区年均水平位移量为向西30~50 mm/a,高雄沿海地区发生明显的逆时针西偏南的逐渐增大的水平位移;垂直位移为屏东平原南部呈现-10 mm/a~-15 mm/a的地面沉降,而平原北部和高雄地区呈现约+5 mm/a~+10 mm/a的地面抬升. 相似文献
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Variance component estimation in errors-in-variables models and a rigorous total least-squares approach 总被引：1，自引：0，他引：1
Vahid Mahboub 《Studia Geophysica et Geodaetica》2014,58(1):17-40
A method for variance component estimation (VCE) in errors-in-variables (EIV) models is proposed, which leads to a novel rigorous total least-squares (TLS) approach. To achieve a realistic estimation of parameters, knowledge about the stochastic model, in addition to the functional model, is required. For an EIV model, the existing TLS techniques either do not consider the stochastic model at all or assume approximate models such as those with only one variance component. In contrast to such TLS techniques, the proposed method considers an unknown structure for the stochastic model in the adjustment of an EIV model. It simultaneously predicts the stochastic model and estimates the unknown parameters of the functional model. Moreover the method shows how an EIV model can support the Gauss-Helmert model in some cases. To make the VCE theory into EIV model more applicable, two simplified algorithms are also proposed. The proposed methods can be applied to linear regression and datum transformation. We apply these methods to these examples. In particular a 3-D non-linear close to identical similarity transformation is performed. Two simulation studies besides an experimental example give insight into the efficiency of the algorithms. 相似文献
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Until the present time the ‘ rock-coal-rock’ layer sequence and offsets in coal-seams in underground coal mines have been detected with the aid of seismic waves and geoelectric measurements. In order to determine the geometrical and petrophysical parameters of the coal-seam situation, the data recorded using seismic and geoelectric methods have been inverted independently. In consequence, the inversion of partially inaccurate data resulted in a certain degree of ambiguity. This paper presents the first results of a joint inversion scheme to process underground vertical seismic profiling data, geolectric resistivity and resistance data. The joint inversion algorithm makes use of the damped least-squares method and its weighted version to solve the linearized set of equations for the seismic and geolectric unknowns. In order to estimate the accuracy and reliability of the derived geometrical and petrophysical layer parameters, both a model covariance matrix and a correlation matrix are calculated. The weighted least-squares algorithm is based on the method of most frequent values (MFV). The weight factors depend on the difference between measured data and those calculated by an iteration process. The joint inversion algorithm is tested by means of synthetic data. Compared to the damped least-squares algorithm, the MFV inversion leads to smaller estimation errors as well as lower sensitivities due to the choice of the initial model. It is shown that, compared to an independent inversion, the correlation between the model parameters is definitely reduced, while the accuracy of the parameter estimation is appreciably increased by the joint inversion process. Thus the ambiguity is significantly reduced. Finally, the joint inversion algorithm using the MFV method is applied to underground field data. The model parameters can be derived with a sufficient degree of accuracy, even in the case of noisy data. 相似文献
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Total least squares (TLS) can solve the issue of parameter estimation in the errors-invariables (EIV) model, however, the estimated parameters are affected or even severely distorted when the observation vector and coefficient matrix are contaminated by gross errors. Currently, the use of existing robust TLS (RTLS) methods for the EIV model is unreasonable. Original residuals are directly used in most studies to construct the weight factor function, thus the robustness for the structure space is not considered. In this study, a robust weighted total least squares (RWTLS) algorithm for the partial EIV model is proposed based on Newton-Gauss method and the equivalent weight principle of general robust estimation. The algorithm utilizes the standardized residuals to construct the weight factor function and employs the median method to obtain a robust estimator of the variance component. Therefore, the algorithm possesses good robustness in both the observation and structure spaces. To obtain standardized residuals, we use the linearly approximate cofactor propagation law for deriving the expression of the cofactor matrix of WTLS residuals. The iterative procedure and precision assessment approach for RWTLS are presented. Finally, the robustness of RWTLS method is verified by two experiments involving line fitting and plane coordinate transformation. The results show that RWTLS algorithm possesses better robustness than the general robust estimation and the robust total least squares algorithm directly constructed with original residuals. 相似文献
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Prestack amplitude versus angle inversion for Young's modulus and Poisson's ratio based on the exact Zoeppritz equations 
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下载免费PDF全文 Elastic parameters such as Young's modulus, Poisson's ratio, and density are very important characteristic parameters that are required to properly characterise shale gas reservoir rock brittleness, evaluate gas characteristics of reservoirs, and directly interpret lithology and oil‐bearing properties. Therefore, it is significant to obtain accurate information of these elastic parameters. Conventionally, they are indirectly calculated by the rock physics method or estimated by approximate formula inversion. The cumulative errors caused by the indirect calculation and low calculation accuracy of the approximate Zoeppritz equations make accurate estimation of Young's modulus, Poisson's ratio, and density difficult in the conventional method. In this paper, based on the assumption of isotropy, we perform several substitutions to convert the Zoeppritz equations from the classical form to a new form containing the chosen elastic constants of Young's modulus, Poisson's ratio, and density. The inversion objective function is then constructed by utilising Bayesian theory. Meanwhile, the Cauchy distribution is introduced as a priori information. We then combine the idea of generalised linear inversion with an iterative reweighed least squares algorithm in order to solve the problem. Finally, we obtain the iterative updating formula of the three elastic parameters and achieve the direct inversion of these elastic parameters based on the exact Zoeppritz equations. Both synthetic and field data examples show that the new method is not only able to obtain the two elastic parameters of Young's modulus and Poisson's ratio stably and reasonably from prestack seismic data but also able to provide an accurate estimation of density information, which demonstrates the feasibility and effectiveness of the proposed method. The proposed method offers an efficient seismic method to identify a “sweet spot” within a shale gas reservoir. 相似文献
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Conventional joint PP—PS inversion is based on approximations of the Zoeppritz equations and assumes constant VP/VS; therefore, the inversion precision and stability cannot satisfy current exploration requirements. We propose a joint PP—PS inversion method based on the exact Zoeppritz equations that combines Bayesian statistics and generalized linear inversion. A forward model based on the exact Zoeppritz equations is built to minimize the error of the approximations in the large-angle data, the prior distribution of the model parameters is added as a regularization item to decrease the ill-posed nature of the inversion, low-frequency constraints are introduced to stabilize the low-frequency data and improve robustness, and a fast algorithm is used to solve the objective function while minimizing the computational load. The proposed method has superior antinoising properties and well reproduces real data. 相似文献
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Data-snooping procedure applied to errors-in-variables models 总被引：1，自引：0，他引：1
The theory of Baarda’s data snooping — normal and F tests respectively based on the known and unknown posteriori variance — is applied to detect blunders in errors-invariables (EIV) models, in which gross errors are in the vector of observations and/or in the coefficient matrix. This work is a follow-up to an earlier work in which we presented the formulation of the weighted total least squares (WTLS) based on the standard least squares theory. This method allows one to directly apply the existing body of knowledge of the least squares theory to the errors-in-variables models. Among those applications, data snooping methods in an EIV model are of particular interest, which is the subject of discussion in the present contribution. This paper generalizes the Baarda’s data snooping procedure of the standard least squares theory to an EIV model. Two empirical examples, a linear regression model and a 2-D affine transformation, using simulated and real data are presented to show the efficacy of the presented formulation. It is highlighted that the method presented is capable of detecting outlying equations (rather than outlying observations) in a straightforward manner. Further, the WTLS method can be used to handle different TLS problems. For example, the WTLS problem for the conditions and mixed models, the WTLS problem subject to constraints and variance component estimation for an EIV model can easily be established. These issues are in progress for future publications. 相似文献
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在已有研究成果的基础上,为了适应物性参数剧烈变化的复杂模型并满足联合反演的要求,开发了速度和电阻率随机分布共网格单元模型的建模技术.基于这种统一的物性随机分布的网格介质模型,利用有限元方法和改进的射线追踪法分别正演计算大地电磁场和地震走时,结合改进的模拟退火算法,研究实现了电阻率和速度随机分布条件下的大地电磁与地震资料的同步联合反演.对物性界面不完全一致和物性变化剧烈的带地形复杂模型的试验,表明了该方法在精细反演复杂电阻率和速度结构方面的效果,克服了以往研究局限于简单模型的不足.对地震资料品质差的地区开展的实际资料联合反演,表明了方法的适用性,先验信息约束下的联合反演提高了反演精度. 相似文献
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An algorithmic approach to the total least-squares problem with linear and quadratic constraints 总被引：5，自引：0，他引：5
Proper incorporation of linear and quadratic constraints is critical in estimating parameters from a system of equations.
These constraints may be used to avoid a trivial solution, to mitigate biases, to guarantee the stability of the estimation,
to impose a certain “natural” structure on the system involved, and to incorporate prior knowledge about the system. The Total
Least-Squares (TLS) approach as applied to the Errors-In-Variables (EIV) model is the proper method to treat problems where
all the data are affected by random errors. A set of efficient algorithms has been developed previously to solve the TLS problem,
and a few procedures have been proposed to treat TLS problems with linear constraints and TLS problems with a quadratic constraint.
In this contribution, a new algorithm is presented to solve TLS problems with both linear and quadratic constraints. The new
algorithm is developed using the Euler-Lagrange theorem while following an optimization process that minimizes a target function.
Two numerical examples are employed to demonstrate the use of the new approach in a geodetic setting. 相似文献