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1.
研究地壳形变的理论和方法主要有两大类：地球物理模型方法和几何方法．由于基准误差、观测误差和模型误差等,两种方法得到的结果往往存在差异．为合理利用几何信息和物理信息,控制几何观测及物理模型误差对形变参数估计的影响,并平衡两类信息对形变参数的贡献,本文提出一种利用自适应滤波综合估计形变参数的方法．采用抗差等价权控制几何观测异常误差的影响,引入自适应因子平衡几何观测和地球物理模型信息对形变模型参数估计的贡献,利用高精度IGS站速度确定局部形变的基准．利用一实测GPS监测网进行计算,结果表明该混合估计策略可充分利用局部重复几何观测信息减弱地球物理模型信息带来的形变系统误差,提高了形变参数解算精度． 相似文献
2.
重力辅助惯性导航系统是未来水下载体导航的重要方式,实时提供重力测量数据是实现水下载体重力辅助导航的关键技术之一.详细探讨了水下载体重力观测数据的厄特弗斯改正和水平扰动加速度改正的数学模型,通过仿真计算分析了载体的位置、航向角和速度误差对厄特弗斯改正精度的影响.仿真结果表明,航向角误差和速度误差对厄特弗斯改正的影响较大;当V=8节、φ=30°时,载体向北航行时,0.5°的航向角误差造成的厄特弗斯改正误差约0.5mGal,载体向东航行时,0.1节的速度误差造成的厄特弗斯改正误差约0.6mGal;要保证厄特弗斯改正精度在±1mGal以内,则要求航向角误差在±1°以内,且航速测量误差在±0.1节以内. 相似文献
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本文对拉柯斯特重力仪的各种误差来源以及各种外界干扰因素进行分析,认为影响仪器观测精度的误差有两类:一类是仪器本身产生的包括仪器读数、置平、格值及零漂等;另一类是外界干扰诸如温度、气压、振动及潮汐等,其中以温度和振动的影响为最大,如果能适当消除这两项影响,拉柯斯特重力仪就能达到很高的观测精度. 相似文献
4.
在对全国地磁台站磁通门磁力仪记录数据的质量效能评估中发现,多个台站存在同台观测仪器的记录数据曲线不一致问题.针对这类问题,研究人员对多种地磁观测数据影响因素进行了定性或定量的分析.本文通过分析格值系数及姿态角对磁通门磁力仪记录数据的影响规律,建立磁通门磁力仪三轴校正模型,构建目标函数,并利用遗传算法对模型进行求解,测定仪器姿态角和格值系数,根据测定结果对记录数据进行一致性校正.数值模拟计算和台站实测实验结果表明:利用该算法解算的格值系数精度优于0.002,姿态角精度优于0.15°.根据解算结果计算,日变幅为50 nT时引入的日变形态不一致误差小于0.13 nT,满足国家地磁台网对地磁相对记录数据日变形态不一致误差的要求. 相似文献
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江苏省溧阳体应变自1994年开始观测以来，经历了1994年至2000年以整点值为主的模拟观测，和2001年至今以分钟值为主的数字化观测两个阶段，对这两个观测阶段观测资料变化形态、观测质量和观测精度、潮汐因子中误差、地震波记录能力等参数进行对比研究，同时采用固体潮汐残差矢量分析方法，对溧阳台1996年以来的观测资料进行了计算分析。结果表明：①溧阳台数字化观测和模拟观测资料的形态、观测精度、方差、潮汐因子中误差、相位滞后等参数无显著差异；影响观测资料精度的主要因素是仪器故障、水位、气压、气温等；②溧阳体应变固体潮汐残差矢量对1996年11月9日长江口6．1级地震异常特征明显，映震效果显著。 相似文献
6.
拉科斯特重力仪干扰因素分析 总被引：1，自引：0，他引：1
本文根据多年重力监测工作情况，结合拉科斯特重力仪的结构特点，对仪器在观测中的干扰因素进行分析，认为影响仪器观测精度的干扰因素有两类：一类是仪器本身产生的系统误差，如格值误差、零飘及弹性后效等；另一类是外界干扰因素，如振动、温度、人为观测方法不当等，如果在观测中能消除或减小这些干扰因素影响，拉科斯特重力仪就可能达到更高的观测精度。 相似文献
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对2017—2019年衡水冀16井水位观测资料的完整率和稳定性、变化形态、观测精度、潮汐因子、中误差、同震效应等进行分析,结果表明：①衡水冀16井水位观测资料完整率较高,仪器工作稳定,符合地下水位观测规范要求;②固体潮效应显著,潮汐响应能力较强,潮汐因子平均值为2.1—2.2,观测精度均值为0.01左右,相对误差较小,且较稳定;③同震响应能力较强,能记录到全球7级以上地震,同震水震波波形清晰;④水位与气压变化之间相关性较好,整体呈负相关;⑤水位观测资料年、月、日变化规律清晰,有望在地震地球物理监测中发挥一定效能。 相似文献
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10.
青藏高原1993年GPS观测成果的精度分析 总被引：3，自引：1，他引：3
应用线性回归、符号检验等数理统计方法研究了１９９３年完成的跨青藏高原首期ＧＰＳ网３９条基线的数据处理结果。通过对单基线观测中误差、重复观测基线互差及异步环闭合差的精度分析，认为由１６个观测点组成的跨青藏高原ＧＰＳ监测网的基线平均相对精度达０．１ｐｐｍ。 相似文献
11.
Hydrological model and observation errors are often non-Gaussian and/or biased, and the statistical properties of the errors are often unknown or not fully known. Thus, determining the true error covariance matrices is a challenge for data assimilation approaches such as the most widely used Kalman filter (KF) and its extensions, which assume Gaussian error nature and need fully known error statistics. This paper introduces H-infinite filter (HF) to hydrological modeling and compares HF with KF under various model and observation error conditions. HF is basically a robust version of KF. When model performance is not well known, or changes unpredictably, HF may be preferred over KF. HF is especially suitable for the cases where the estimation performance in the worst error case needs to be guaranteed. Through the application of HF to a hypothetical hydrologic model, this paper shows that HF is less sensitive to the uncertainty in the initial condition, corrects system bias more effectively, and converges to true state faster after interruptions than KF. In particular, HF performs better in dealing with instant human inputs (irrigation is used as an example), which are characterized by non-stationary, non-Gaussian and not fully known errors. However HF design can be more difficult than KF design due to the sensitivity of HF performance to design parameters (weights for model and observation error terms). Through sensitivity analysis, this paper shows the existence of a certain range of those parameters, in which the “best” value of the parameters is located. The tuning of HF design parameters, which can be based on users’ prior knowledge on the nature of model and observation errors, is critical for the implementation of HF. 相似文献
12.
介绍了一种考虑电离层沿GNSS掩星射线路径分布不对称且兼顾一阶和二阶项的大气掩星电离层误差修正新方法,它综合地基GNSS VTEC的水平变化信息和电离层模式的垂直变化信息,在沿"入射线"与"出射线"双边局部球对称假设下,估算GNSS掩星射线路径上的电子密度;进而计算一阶和二阶项弯曲角电离层误差廓线.采用太阳活动低年的2008年7月15日和太阳活动较高年的2013年7月15日两天的MetOp-A和GRACE掩星观测资料和IGS的GNSS VTEC数据,计算了GNSS大气掩星弯曲角一阶和二阶项电离层误差廓线.对比分析表明：新方法经验模型和理论模型的二阶项弯曲角电离层残差,以及经验模型与实测数据的一阶和二阶项弯曲角电离层误差均具有良好的一致性,因此该方法可用于L2信号数据质量较差或L2信号中断的掩星事件,同时修正大气掩星一阶和二阶电离层误差,从而提高弯曲角精度和掩星观测资料的利用率. 相似文献
13.
基于航空重力测量的基本数学模型,详细分析了航空重力测量的系统误差来源.大致可将系统误差分为三类,即停机坪重力基准值、比力初值的观测误差,格值、交叉耦合系数、摆杆尺度因子的标定误差和水平加速度改正的模型化误差等.然后,对每类系统误差的量级及其补偿方法进行了研究,指出水平加速度改正是引起系统误差的主要因素之一.大同、哈尔滨和渤海湾航空重力测量的实测数据分析均表明,在各项系统误差尤其是水平加速度改正得到有效补偿后,航空重力与地面(或船测)参考值的系统误差将小于1×10-5m·s-2. 相似文献
14.
The problem of variational data assimilation for a nonlinear evolution model is formulated as an optimal control problem to
find the initial condition function. The equation for the error of the optimal solution (analysis) is derived through the
errors of the input data (background and observation errors). The numerical algorithm is developed to compute the sensitivity
coefficients for the analysis error using the fundamental control functions. Application to the variational data assimilation
problem for a model of ocean thermodynamics is considered. 相似文献
15.
本文介绍了固体潮观测数据的平滑检验和NAKAI法检验之方法原理和具体应用。平滑检验可以有效地监测並改正观测数据中的随机错误,突跳或坏读数;经平滑改正后,可使观测数据的读数误差小于1毫米。用NAKAI(1975)提出的方法检验观测数据可以监测仪器灵敏度变化情况和数据质量好坏,根据该检验计算获得的有关参数(主要是漂移系数和方差)剔除质量不好的48小时数据组或修正某些质量不好的数据可提高调和分析结果的精度。 相似文献
16.
Hydrological modelling of the Chaohe Basin in China: Statistical model formulation and Bayesian inference 总被引：4，自引：0，他引：4
Calibration of hydrologic models is very difficult because of measurement errors in input and response, errors in model structure, and the large number of non-identifiable parameters of distributed models. The difficulties even increase in arid regions with high seasonal variation of precipitation, where the modelled residuals often exhibit high heteroscedasticity and autocorrelation. On the other hand, support of water management by hydrologic models is important in arid regions, particularly if there is increasing water demand due to urbanization. The use and assessment of model results for this purpose require a careful calibration and uncertainty analysis. Extending earlier work in this field, we developed a procedure to overcome (i) the problem of non-identifiability of distributed parameters by introducing aggregate parameters and using Bayesian inference, (ii) the problem of heteroscedasticity of errors by combining a Box–Cox transformation of results and data with seasonally dependent error variances, (iii) the problems of autocorrelated errors, missing data and outlier omission with a continuous-time autoregressive error model, and (iv) the problem of the seasonal variation of error correlations with seasonally dependent characteristic correlation times. The technique was tested with the calibration of the hydrologic sub-model of the Soil and Water Assessment Tool (SWAT) in the Chaohe Basin in North China. The results demonstrated the good performance of this approach to uncertainty analysis, particularly with respect to the fulfilment of statistical assumptions of the error model. A comparison with an independent error model and with error models that only considered a subset of the suggested techniques clearly showed the superiority of the approach based on all the features (i)–(iv) mentioned above. 相似文献
17.
L. B. PEDERSEN 《Geophysical Prospecting》1982,30(2):188-210
Approaches to the reduction of bias in the computation of the elements of the magnetotelluric impedance tensor have been proposed in the past by several authors. In this paper a clear distinction is made between random errors and bias errors. No effort is made to reduce either, but the emphasis is on their estimation. Both types of errors depend critically upon the polarization of the magnetic field. The random error increases with increasing noise-to-signal ratio in the electrical field, and it is rather insensitive to noise in the magnetic field. The bias error increases with increasing noise-to-signal ratio in the magnetic field. Expressions for random errors and maximum bias errors are developed and discussed using a single station set-up. Random errors with a reference station set-up are also calculated. 相似文献
18.
The influence of the uncertainties of intra-seasonal wind stress forcing on Spring Predictability Barrier (SPB) in El Niño–Southern Oscillation (ENSO) prediction is studied with the Zebiak–Cane model and observational wind data which are analyzed with Continuous Wavelet Transform (CWT) and utilized to extract intra-seasonal wind stress signals as external forcing. The observational intra-seasonal wind stress forcing are joined into Zebiak–Cane model to get the Zebiak–Cane-add model and subsequently with the Conditional Nonlinear Optimal Perturbation (CNOP) method, the evolutions of the optimal initial errors (i.e., CNOPs), model errors caused by intra-seasonal wind stress uncertainties, and their joint errors based on ENSO events are calculated. By investigating their error growth rates and prediction errors of Niño-3 indices, the effect of observational intra-seasonal wind stress forcing on seasonal error growth of ENSO is explored and the impact of initial error and model error on ENSO predictability is compared quantitatively. The results show that the model errors led by observational intra-seasonal wind stress forcing could scarcely cause a significant SPB whereas the initial errors and their joint errors can do; hence, the initial errors are most likely the main error source of SPB. In fact, this result emphasizes the primary influence of initial errors on ENSO predictability and lays the basis of adaptive data assimilation for ENSO forecast. 相似文献
19.
太湖叶绿素a同化系统敏感性分析 总被引：1，自引：1，他引：0
太湖叶绿素a同化系统对于不同参数的敏感性将直接影响到该系统能否精确的估算太湖叶绿素a的浓度分布.利用2009年4月21日环境一号卫星(HJ-1B CCD2)影像数据反演太湖叶绿素a浓度场信息.以此作为背景场信息,结合基于集合均方根滤波的太湖叶绿素a同化系统,分析和评价了样本数目、同化时长、背景场误差、观测误差和模型误差对于同化系统性能的影响.结果表明:从计算成本、系统运行时间和同化效果等方面分析,当集合样本数目达到30~40左右时同化系统取得了较好的结果;同化系统对于背景场误差的估计变化不是很敏感,即初始场的估计是否准确对于同化系统的性能影响不是很大;同化系统对于模型误差和观测误差的变化较为敏感,不同的测试点位由于水体动力学性质不一,其敏感性的表现形式有所差异;利用数据同化方法可以有效地估算太湖叶绿素a浓度. 相似文献
20.
Mohammad Bagherbandi Robert Tenzer Lars E. Sjöberg 《Studia Geophysica et Geodaetica》2014,58(2):227-248
We formulate an error propagation model based on solving the Vening Meinesz-Moritz (VMM) inverse problem of isostasy. The system of observation equations in the VMM model defines the relation between the isostatic gravity data and the Moho depth by means of a second-order Fredholm integral equation of the first kind. The corresponding error model (derived in a spectral domain) functionally relates the Moho depth errors with the commission errors of used gravity and topographic/bathymetric models. The error model also incorporates the non-isostatic bias which describes the disagreement, mainly of systematic nature, between the isostatic and seismic models. The error analysis is conducted at the study area of the Tibetan Plateau and Himalayas with the world largest crustal thickness. The Moho depth uncertainties due to errors of the currently available global gravity and topographic models are estimated to be typically up to 1–2 km, provided that the GOCE gravity gradient observables improved the medium-wavelength gravity spectra. The errors due to disregarding sedimentary basins can locally exceed ～2 km. The largest errors (which cause a systematic bias between isostatic and seismic models) are attributed to unmodeled mantle heterogeneities (including the core-mantle boundary) and other geophysical processes. These errors are mostly less than 2 km under significant orogens (Himalayas, Ural), but can reach up to ～10 km under the oceanic crust. 相似文献