应用GPS速度场和地震数据反演中国大陆构造应变场

为获得更准确的中国大陆地壳应力应变场,文章基于ITRF2005全球地心坐标参考框架,采用高精度数据处理方法计算了中国地壳运动观测网络1999—2009年间的观测数据,获得了中国大陆GPS速度场以及相对欧亚板块的区域形变场,计算结果显示中国大陆形变运动仍是西强东弱的格局;并利用中国大陆同期近30年的地震矩张量及第四纪活动断层研究成果资料,联合反演了中国大陆区域的构造应变场,结果表明:从总体来看,应变相对集中的区域为喜马拉雅构造带、青藏高原、帕米尔高原、阿尔金断裂带、新疆天山及川滇地区,中国大陆区域过去10年的构造变化以挤压为主,拉张为辅。     

大地测量和地震数据联合反演地震震源破裂过程研究进展

综述了近10多年来大地测量和地震数据联合反演地震震源破裂过程的研究成果及最新进展,特别是大地测量和地震数据联合反演地震震源破裂过程的模型、算法及典型震例。展望了利用GPSI、nSAR和地震波数据联合反演震源破裂过程中顾及先验信息、附有不等式约束时反演模型的建立方法,以及相对权比的确定、全局优化方法的应用等问题。     

利用平滑先验信息方法分离高频GPS数据静态永久变形与地震波

震后高频GPS观测资料详细记录了地震引起的静态永久变形和地震波信息,如何实现二者的有效分离是准确反演地震参数的关键因素。本文引入平滑先验信息方法（SPM）对近几年3次地震的高频GPS数据进行处理和分析,尝试实现二者的有效分离。结果表明,SPM方法可以简单、快速、有效地分离高频GPS动态位移中的静态永久变形和地震波信息,数据处理结果完整、清晰地记录了由主震引起的静态永久变形、余震引起的静态永久变形和震后余滑位移以及地震波信息,可为准确反演震源参数、断层破裂过程提供重要的约束条件。     

华北地区地壳形变的GPS及地震矩张量反演分析

给出了在椭球面上利用ＧＰＳ速度场计算地壳应变率张量的公式,利用华北地区ＧＰＳ监测网１９９２年、１９９５年和１９９６年观测数据所得的速度场在椭球面上进行了应变率计算,得到了其最大剪切变态为率、主应变率的图像;并利用１９６６年以来２５次大于５．０级地震的地震矩张量,由Ｋｏｓｔｒｏｖ公式计算了地震应变率,对两种数据所得的应变率地比较分析;结合地质构造背景探讨了华北地区现今形变特征及地震危险性地区的分布。     

利用单站地基GPS数据反演电离层电子密度

利用单站GPS观测数据对GPS硬件系统延迟作出修正,得到较精确的电离层总电子含量。根据Chapman电离层理论,建立电离层模型,利用遗传算法优化选择电离层关键参量,反演得到接收机上空电子密度剖面,结果表明：该方法用于太阳活动高年白天电子密度剖面反演效果优于国际参考电离层。     

华北地区地壳形变的GPS及地震矩张量反演分析

给出了在椭球面上利用GPS速度场计算地壳应变率张量的公式,利用华北地区GPS监测网1992年、1995年和1996年观测数据所得的速度场在椭球面上进行了应变率计算,得到了其最大剪切应变率、主应变率的图像;并利用1966年以来25次大于5.0级地震的地震矩张量,由Kostrov公式计算了地震应变率,对两种数据所得的应变率进行了比较分析;结合地质构造背景探讨了华北地区现今形变特征及地震危险性地区的分布。     

运用GPS高频时间序列对地震前兆的探索研究

通过对在日本福岛地震发生前后短时间内的两个GPS测站的时间序列进行拟合以获取在短时间内的地震同震位移数据,通过动态时间序列图的形式对地震同震位移数据进行研究,结果发现,在地震发生时很短的时间内地震同震位移数据会发生大幅度的变化,在地震结束后又恢复正常。这种变化规律可以为地震前兆预测做参考。     

汶川地震震后形变的GPS反演

通过对汶川地震后震区附近的GPS连续站资料的高精度数据处理,获得各测站的时间序列。利用时间序列分析,求得震后松弛时间约为38d,并获得各测站的震后位移。基于粘弹性松弛模型,对震后位移进行了模拟,反演出龙门山地区地壳的弹性层厚度的最佳估值为45km,粘弹性层的粘滞系数的最佳估值为1.8×10¹⁹ Pa.s,该结果与地震学以及地球物理学等给出的结果基本一致。     

利用GNSS历元间差分测速方法反演地震三要素

利用高频全球卫星导航系统（global navigation satellite system, GNSS）记录监测地震可有效弥补传统地震仪近场观测量程饱和、基线偏移等问题。相比于GNSS精密单点定位（precise point positioning, PPP）,历元间差分测速方法可避免PPP收敛时间较长、需要外部改正数的问题,且测速方法获取的地震波形具有更高的信噪比。以2021年5月21日青海玛多MS 7.4地震为研究对象,提出利用载波相位历元间差分方法对该地区1 Hz高频GNSS数据进行处理,得到测站速度波形,并确定出玛多地震的震中位置、震级和发震时刻等参数。与中国地震局公布的结果比较,震中位置平均值相差约2.07 km;震级平均值相差约0.06个震级单位;发震时刻平均值相差4 s。结果表明,高频GNSS历元间差分测速方法反演地震三要素具有非常好的准确性与实用性。     

利用GPS资料反演汶川Mw7.9级地震滑动分布

2008年5月12日,青藏高原东缘龙门山断裂带发生Mw 7.9级汶川地震,该地震使得北川-映秀断裂、灌县-江油断裂和汉旺-白鹿断裂带发生了同震破裂。本文主要利用“中国地壳运动观测网络”项目组提供的GPS同震位移资料,采用基于敏感度迭代拟合法(SBIF)及分段发震断层模型,分别应用均匀半空间和分层地壳结构两种方法反演分析了该次地震的精细同震滑动分布。结果表明：（1）SBIF反演方法应用于相对较小的GPS数据集仍然可以获得理想的同震滑动分布;（2）采用考虑分层地壳结构模型的反演结果整体上要优于均匀半空间模型的结果;（3）同震滑动主要发生在10-19千米深度以上,且存在五个滑动峰值区域及北川断裂南西端存在明显的深部滑动区,与震后野外考察结果及余震分布相吻合,同时能够较好地解释GPS观测数据;（4）青川断裂存在明显的右旋走滑分量,其平均滑动量为1.99米,北川断裂主要发生逆冲滑动,平均滑动量为3.35米,灌县断裂的平均滑动量为0.65米;（5）反演得到的地震矩为8.74×1020Nm(Mw 7.90),与地震学结果吻合。     

Denoising effect of multiscale multiway analysis on high-rate GPS observations

GPS Solutions - In general, high-rate GPS data sets are subject to common mode error (CME), multipath error, and high-frequency random noise, which adversely affect the GPS positioning accuracy. In...     

Very high-rate GPS for measuring dynamic seismic displacements without aliasing: performance evaluation of the variometric approach

Very high-rate global positioning system (GPS) data has the capacity to quickly resolve seismically related ground displacements, thereby providing great potential for rapidly determining the magnitude and the nature of an earthquake’s rupture process and for providing timely warnings for earthquakes and tsunamis. The GPS variometric approach can measure ground displacements with comparable precision to relative positioning and precise point positioning (PPP) within a short period of time. The variometric approach is based on single-differencing over time of carrier phase observations using only the broadcast ephemeris and a single receiver to estimate velocities, which are then integrated to derive displacements. We evaluate the performance of the variometric approach to measure displacements using 50 Hz GPS data, which were recorded during the 2013 M_W 6.6 Lushan earthquake and the 2011 M_W 9.0 Tohoku-Oki earthquake. The comparison between 50 and 1 Hz seismic displacements demonstrates that 1 Hz solutions often fail to faithfully manifest the seismic waves containing high-frequency seismic signals due to aliasing, which is common for near-field stations of a moderate-magnitude earthquake. Results indicate that 10–50 Hz sampling GPS sites deployed close to the source or the ruptured fault are needed for measuring dynamic seismic displacements of moderate-magnitude events. Comparisons with post-processed PPP results reveal that the variometric approach can determine seismic displacements with accuracies of 0.3–4.1, 0.5–2.3 and 0.8–6.8 cm in the east, north and up components, respectively. Moreover, the power spectral density analysis demonstrates that high-frequency noises of seismic displacements, derived using the variometric approach, are smaller than those of PPP-derived displacements in these three components.     

Estimation and analysis of GPS satellite DCB based on LEO observations

The Global Positioning System (GPS) satellite differential code bias (DCB) should be precisely calibrated when obtaining ionospheric slant total electron content (TEC). So far, it is ground-based GPS observations that have been used to estimate GPS satellite DCB. With the increased Low Earth Orbit (LEO) missions in the near future, the real-time satellite DCB estimation is a crucial factor in real-time LEO GPS data applications. One alternative way is estimating GPS DCB based on the LEO observations themselves, instead of using ground observations. We propose an approach to estimate the satellite DCB based on Constellation Observing System for Meteorology, Ionosphere, and Climate (COSMIC) and Challenging Minisatellite Payload (CHAMP) GPS observations during the years 2002–2012. The results have been validated through comparisons with those issued by Center for Orbit Determination in Europe (CODE). The evaluations indicate that: The approach can estimate satellite DCB in a reasonable way; the DCB estimated based on CHAMP observations is much better than those on COSMIC observations; the accuracy and precision of DCB show a possible dependency on the ionospheric ionization level. This method is significance for the real-time processing of LEO-based GNSS TEC data from the perspective of real-time applications.     

Low-degree earth deformation from reprocessed GPS observations

Surface mass variations of low spherical harmonic degree are derived from residual displacements of continuously tracking global positioning system (GPS) sites. Reprocessed GPS observations of 14 years are adjusted to obtain surface load coefficients up to degree n _max = 6 together with station positions and velocities from a rigorous parameter combination. Amplitude and phase estimates of the degree-1 annual variations are partly in good agreement with previously published results, but also show interannual differences of up to 2 mm and about 30 days, respectively. The results of this paper reveal significant impacts from different GPS observation modeling approaches on estimated degree-1 coefficients. We obtain displacements of the center of figure (CF) relative to the center of mass (CM), Δr _CF–CM, that differ by about 10 mm in maximum when compared to those of the commonly used coordinate residual approach. Neglected higher-order ionospheric terms are found to induce artificial seasonal and long-term variations especially for the z-component of Δr _CF–CM. Daily degree-1 estimates are examined in the frequency domain to assess alias contributions from model deficiencies with regard to satellite orbits. Finally, we directly compare our estimated low-degree surface load coefficients with recent results that involve data from the Gravity Recovery and Climate Experiment (GRACE) satellite mission.     

Tropospheric corrections to SAR interferometry from GPS observations

Interferometric synthetic aperture radar (InSAR) techniques have been recognized as an ideal tool for many ground deformation monitoring applications. However, the spatially and temporally variable delay of the radar signal propagating through the atmosphere is a major limitation to accuracy. The dominant factor to be considered is the tropospheric heterogeneity, which can lead to misinterpretation of InSAR results. In this paper, a between-site (BS) and between-epoch (BE) double-differencing algorithm for the generation of tropospheric corrections to InSAR results based on GPS observations is tested. In order to correct the radar results on a pixel-by-pixel basis, the GPS-derived corrections have to be interpolated. Using experimental data it has been found that the inverse distance weighted and kriging interpolation methods are more suitable than the spline interpolation method. Differential corrections as large as several centimeters may have to be applied in order to ensure sub-centimeter accuracy for the InSAR result. The algorithm and procedures described in this paper could easily be implemented in a continuous GPS network data center. The interpolated image of BS, single-differenced tropospheric delays can be derived as a routine product to assist radar interferometry.     

Estimating atmospheric pressure loading regression coefficients from GPS observations

The loading exerted by atmospheric pressure on the surface of the Earth causes deformations, mainly in vertical direction. Consequently, these deformations are also subject to pressure variations. At present this effect is only modeled by a few research groups in the post-processing of very long baseline interferometry (VLBI) and global positioning system (GPS) observations. As the displacements may clearly exceed the accuracy goals, we implement vertical pressure loading regression coefficients as a new estimable parameter type in the Bernese GPS software. This development is applied to a network of 60 European permanent GPS stations extending from 35 to 79° northern latitude. The analysis comprises 1,055 days of observations between January 2001 and February 2004. During that period pressure variations as large as 80 hPa occurred at high latitude sites. A least squares solution including all observations and all relevant parameters yields significant regression coefficients for all stations but reveals also some critical issues with regard to the capability of this geodetic approach to verify results based on the geophysical convolution method.An erratum to this article can be found at     

Assessment of observing time-variable gravity from GOCE GPS and accelerometer observations

An assessment has been made of the possibility to estimate time-variable gravity from GPS-derived orbit perturbations and common-mode accelerometer observations of ESA’s GOCE Earth Explorer. A number of 20-day time series of Earth’s global long-wavelength gravity field have been derived for the period November 2009 to November 2012 using different parameter setups and estimation techniques. These techniques include a conventional approach where for each period, one set of gravity coefficients is estimated, either excluding or including empirical accelerations, and the so-called Wiese approach where higher frequency coefficients are estimated for the very long wavelengths. A principal component analysis of especially the time series of gravity field coefficients obtained by the Wiese approach and the conventional approach with empirical accelerations reveals an annual signal. When fitting this annual signal directly through the time series, the sine component (maximum in spring) displays features that are similar to well-known continental hydrological mass changes for the low latitude areas, such as mass variations in the Amazon basin, Africa and Australia for spatial scales down to 1,500 km. The cosine component (maximum in winter), however, displays large signals that can not be attributed to actual mass variations in the Earth system. The estimated gravity field changes from GOCE orbit perturbations are likely affected by missing GPS observations in case of high ionospheric perturbations during periods of increased solar activity, which is minimal in Summer and maximal towards the end of autumn.     

Vertical velocities of European coastal sites derived from continuous GPS observations

Vertical velocities of 30 European permanent Global Positioning System (GPS) stations at or close to tide gauge sites are estimated from more than 3 years of continuous observations. The results of two different solution strategies are presented and compared. The first approach accumulates the daily free network normal equations, the second introduces all sets of daily ellipsoidal height estimates and their covariance matrix into a subsequent common least squares adjustment. In both solutions, mean station heights at a reference epoch, linear vertical velocities, height discontinuities and short period height offsets are estimated. The second approach solves in addition for periodic annual signals and for site-specific pressure loading coefficients. The vertical velocities range from +8 mm/year in the center of the Fennoscandian uplift area to –4 mm/year at a few subsiding locations. Apart from these extrema, most of the sites experience only very small vertical motions. The standard deviations from the second approach providing more realistic error estimates are well below 0.15 mm/year. Some specific data problems are discussed.