重力卫星主要有效载荷指标分析与确定

在介绍重力卫星发展计划的基础上 ,研究讨论了重力卫星上的主要有效载荷。从重力测量的基本原理出发 ,推导了卫星轨道高度、有效荷载的精度需求、所能恢复的重力场最大空间分辨率和相应重力场参数精度之间粗略的函数关系。最后利用推导的公式计算了CHAMP、GRACE、GOCE卫星上几种主要测量有效载荷的指标 ,并将推得的指标与CHAMP、GRACE、GOCE卫星设计的指标进行了比较 ,得出了两种指标在量级上一致的结论。     

基于GOCE卫星重力测量技术确定地球重力场的研究

随着GOCE卫星的成功发射,围绕GOCE数据处理和应用研究已成为目前地学研究的热点问题之一。本文研究基于GOCE卫星重力测量技术确定地球重力场的理论和方法,研制相应的数据处理软件包与仿真模拟平台。论文的主要工作如下：     

地球重力场和海洋环流探测卫星及其应用

近年来,卫星重力学研究越来越受到各国的重视,继德国“挑战小卫星有效载荷及地球科学探索卫星”（CHAMP）和美欧合作的“地球重力场恢复和气候探索卫星”（GRACE）之后,欧洲航天局又于2009年3月发射了地球重力场和海洋环流探测卫星（GOCE）。本文概要介绍了GOCE卫星的基本情况,重点阐述了卫星载荷及卫星的科学应用情况,分析了国际上卫星重力学的研究进展。     

卫星重力梯度数据重力异常的精度分析

针对GOCE卫星确定的地球重力场模型精度的不确定性,对比分析GOCE位模型与多个不同重力场模型确定的重力异常,并将其分别与船测重力数据、南极航空重力数据、北极重力数据以及美国和中国台湾地面重力数据比较研究。结果表明:GOCE位模型的内符合精度最高,与地面重力观测数据符合最优;与船测以及航空重力测量符合相对较差、精度较低。研究表明,在一定精度前提下,GOCE卫星确定的重力数据可用于无人区,从而提高重力观测数据的覆盖率。     

GOCE地球重力场模型在青藏地区的评价及分析

2009年GOCE卫星升空以后,卫星重力梯度数据参与解算的GOCE系列重力场模型已有多家研究机构相继公布。本文分别采用青藏地区的GPS/水准和重力异常实测数据对GOCE重力场模型进行了外部测试,并在重力异常验证过程中引入了一种新的滤波方法,验证结果表明在青藏地区GOCE重力场模型相比其它系列模型的优势在于中波段。同时,探讨了GOCE重力场模型与其他系列模型在青藏地区主要差异值的空间分布以及首次利用统计分析方法找出模型之间主要差异值的阶次分布,得出如下结论：模型之间的较大差异值在空间水平方向上主要分布在喜马拉雅山脉、天山等地形起伏较大的区域,在垂直方向上主要集中在岩石圈。     

国际新一代卫星重力探测计划研究现状与进展

回顾了卫星重力探测技术的发展,讨论了当前卫星重力计划CHAMP、GRACE、GOCE研究现状和存在的主要问题,评述了国际下一代4个卫星重力计划E.motion、GRACE-FO、NGGM和GETRIS的最新研究进展,并介绍了SWARM卫星星群任务在地球重力场研究中的作用和地位,最后对我国未来卫星重力计划的实施提出了几点建议。     

重力卫星和测高卫星五年来的进展

对近年升空的重力卫星CHAMP和GRACE及将于近期升空的GOCE卫星,以及测高卫星ENVISAT,Jason1,GFO,ICESat和CryoSat的技术特点进行了介绍和评估。     

GOCE卫星重力梯度校准与无阻尼控制效果分析

GOCE卫星是首颗搭载高精度梯度仪,通过加速度计差分测量确定地球重力场的现代重力卫星。该卫星设计为无阻尼飞行状态（沿轨方向）,加速度计并未安置在卫星质心,这些特点使得GOCE与标准的卫星跟踪卫星重力测量模式有着显著的区别。本文首先指出GOCE任务中普通模式加速度校准存在不严密性问题,并提出了分别校准6个加速度计,分离偏差参数的方案。利用GOCE任务期内的几何法精密轨道,采用动力法完成校准,并分析了无阻尼控制的效果,发现：①虽然GOCE所在轨道高度的中性大气密度较GRACE高两到三个量级,但GOCE卫星在沿轨方向的残余非保守力比GRACE卫星的对应分量小一个量级,充分显示了无阻尼控制系统的补偿效果;②通过精密轨道内插的轨道速度与动力法轨道速度的比较可以得出,卫星无阻尼控制系统对GOCE卫星速度的显著影响;③计算了GOCE卫星所受的非保守力。获得了GOCE任务期间的加速度计校准参数,并讨论了利用其辅助重力梯度仪数据预处理的可能方法。     

卫星重力与卫星测高的研究进展

该文介绍了GRACE和GOCE重力卫星在地球重力场模型以及局部变化等方面的研究成果,介绍了卫星测高的检核与校验、全球和局部海平面变化监测、内陆湖和水库水位变化监测等方面的研究进展,对综合利用卫星重力、卫星测高以及合成孔径雷达差分干涉测量(DInSAR)等技术方法监测冰川和冰盖变化的成果进行了介绍,重点介绍了南极冰盖变化监测的研究成果。对综合卫星重力、卫星测高、DInSAR、GNSS/水准、GNSS等多种技术在冰川冰盖、局部形变监测等方面的应用进行了展望。     

GOCE实测数据反演高阶重力场模型的Torus方法

不同于当前广泛使用的空域法、时域法、直接解法,本文尝试采用Torus方法处理GOCE实测数据,利用71 d的GOCE卫星引力梯度数据反演了200阶次GOCE地球重力场模型,实现了对参考模型的精化。首先,采用Butterworth零相移滤波方法加移去—恢复技术,处理引力梯度观测值中的有色噪声,并利用泰勒级数展开和Kriging方法对GOCE卫星引力梯度数据进行归算和格网化,计算得到了名义轨道上格网点处的引力梯度数据。然后,利用2D-FFT技术和块对角最小二乘方法处理名义轨道上数据,获得了200阶次的GOCE地球重力场模型GOCE_Torus。利用中国和美国的GPS/水准数据进行外部检核结果说明,GOCE_Torus与ESA发布的同期模型的精度相当;GOCE_Torus模型与200阶次的EGM2008模型相比,在美国区域精度相当,但在中国区域精度提高了4.6 cm,这充分体现了GOCE卫星观测数据对地面重力稀疏区的贡献。Torus方法拥有快速高精度反演卫星重力场模型的优势,可以在重力梯度卫星的设计、误差分析及在轨快速评估等方面得到充分应用。     

Adaptive filtering of GOCE-derived gravity gradients of the disturbing potential in the context of the space-wise approach

Filtering and signal processing techniques have been widely used in the processing of satellite gravity observations to reduce measurement noise and correlation errors. The parameters and types of filters used depend on the statistical and spectral properties of the signal under investigation. Filtering is usually applied in a non-real-time environment. The present work focuses on the implementation of an adaptive filtering technique to process satellite gravity gradiometry data for gravity field modeling. Adaptive filtering algorithms are commonly used in communication systems, noise and echo cancellation, and biomedical applications. Two independent studies have been performed to introduce adaptive signal processing techniques and test the performance of the least mean-squared (LMS) adaptive algorithm for filtering satellite measurements obtained by the gravity field and steady-state ocean circulation explorer (GOCE) mission. In the first study, a Monte Carlo simulation is performed in order to gain insights about the implementation of the LMS algorithm on data with spectral behavior close to that of real GOCE data. In the second study, the LMS algorithm is implemented on real GOCE data. Experiments are also performed to determine suitable filtering parameters. Only the four accurate components of the full GOCE gravity gradient tensor of the disturbing potential are used. The characteristics of the filtered gravity gradients are examined in the time and spectral domain. The obtained filtered GOCE gravity gradients show an agreement of 63–84 mEötvös (depending on the gravity gradient component), in terms of RMS error, when compared to the gravity gradients derived from the EGM2008 geopotential model. Spectral-domain analysis of the filtered gradients shows that the adaptive filters slightly suppress frequencies in the bandwidth of approximately 10–30 mHz. The limitations of the adaptive LMS algorithm are also discussed. The tested filtering algorithm can be connected to and employed in the first computational steps of the space-wise approach, where a time-wise Wiener filter is applied at the first stage of GOCE gravity gradient filtering. The results of this work can be extended to using other adaptive filtering algorithms, such as the recursive least-squares and recursive least-squares lattice filters.     

Improving GOCE cross-track gravity gradients

The GOCE gravity gradiometer measured highly accurate gravity gradients along the orbit during GOCE’s mission lifetime from March 17, 2009, to November 11, 2013. These measurements contain unique information on the gravity field at a spatial resolution of 80 km half wavelength, which is not provided to the same accuracy level by any other satellite mission now and in the foreseeable future. Unfortunately, the gravity gradient in cross-track direction is heavily perturbed in the regions around the geomagnetic poles. We show in this paper that the perturbing effect can be modeled accurately as a quadratic function of the non-gravitational acceleration of the satellite in cross-track direction. Most importantly, we can remove the perturbation from the cross-track gravity gradient to a great extent, which significantly improves the accuracy of the latter and offers opportunities for better scientific exploitation of the GOCE gravity gradient data set.     

Geoid and high resolution sea surface topography modelling in the mediterranean from gravimetry,altimetry and GOCE data: evaluation by simulation

The determination of local geoid models has traditionally been carried out on land and at sea using gravity anomaly and satellite altimetry data, while it will be aided by the data expected from satellite missions such as those from the Gravity field and steady-state ocean circulation explorer (GOCE). To assess the performance of heterogeneous data combination to local geoid determination, simulated data for the central Mediterranean Sea are analyzed. These data include marine and land gravity anomalies, altimetric sea surface heights, and GOCE observations processed with the space-wise approach. A spectral analysis of the aforementioned data shows their complementary character. GOCE data cover long wavelengths and account for the lack of such information from gravity anomalies. This is exploited for the estimation of local covariance function models, where it is seen that models computed with GOCE data and gravity anomaly empirical covariance functions perform better than models computed without GOCE data. The geoid is estimated by different data combinations and the results show that GOCE data improve the solutions for areas covered poorly with other data types, while also accounting for any long wavelength errors of the adopted reference model that exist even when the ground gravity data are dense. At sea, the altimetric data provide the dominant geoid information. However, the geoid accuracy is sensitive to orbit calibration errors and unmodeled sea surface topography (SST) effects. If such effects are present, the combination of GOCE and gravity anomaly data can improve the geoid accuracy. The present work also presents results from simulations for the recovery of the stationary SST, which show that the combination of geoid heights obtained from a spherical harmonic geopotential model derived from GOCE with satellite altimetry data can provide SST models with some centimeters of error. However, combining data from GOCE with gravity anomalies in a collocation approach can result in the estimation of a higher resolution geoid, more suitable for high resolution mean dynamic SST modeling. Such simulations can be performed toward the development and evaluation of SST recovery methods.     

GOCE卫星重力梯度数据反演重力场的滤波器设计与比较分析

地球重力场和海洋环流探测（gravity field and steady-state ocean circulation explorer,GOCE）卫星重力梯度数据有色噪声和低频系统误差的滤波处理是反演高精度地球重力场的一个关键问题。针对GOCE卫星重力梯度数据的滤波处理,基于移动平均（moving average,MA）方法和CPR(circle per revolution)经验参数方法设计了两类低频系统误差滤波器,并分别将这两类滤波器与基于自回归移动平均（auto-regressive and moving average,ARMA）模型设计的有色噪声滤波器组合起来形成级联滤波器。为了分析滤波器处理的实际效果,基于空域最小二乘法采用70 d的GOCE观测数据,并联合重力恢复与气候实验（gravity recovery and climate experiment,GRACE）数据分别反演了224阶次的重力场模型GOGR-MA(MA+ARMA级联滤波)和GOGR-CPR(CPR+ARMA级联滤波)。将反演模型与采用同期数据求解的第一代GOCE系列模型及GOCE和GRACE联合模...     

现代低轨卫星对地球重力场探测的实践和进展

综述了现代低轨卫星对地球重力场测量的特点和近况，介绍了已经和即将发射的重力卫星CHAMP、GRACE、GOCE和新型测高卫星，讨论了作为现代重力卫星首次实践－－CHAMP卫星的进展和目前尚待解决的问题。     

星载原子干涉技术用于地球重力场测量及其精度评估

重力梯度卫星GOCE通过搭载静电式重力梯度仪,将全球静态重力场恢复至200阶以上。目前GOCE卫星已结束寿命,亟须发展下一代更高分辨率的卫星重力梯度测量来完善200~360阶的全球静态重力场模型。原子干涉型的重力梯度测量在空间微重力环境下可获得较长的干涉时间,因此具有很高的星载测量精度,是下一代卫星重力梯度测量的候选技术之一。本文针对未来更高分辨率全球重力场测量的科学需求,提出了一种适用于空间微重力环境下的原子干涉重力梯度测量方案,其梯度测量噪声可低至0.85mE/Hz1/2。文中对不同类型的卫星重力梯度测量方案进行了重力场反演精度的对比评估,仿真结果表明,相比于现有静电式卫星重力梯度测量,原子干涉型的卫星重力梯度测量有望将重力场的恢复阶数提升至252~290阶,对应的累积大地水准面误差7~8cm,累积重力异常误差3×10-5 m/s2。     

Mission design,operation and exploitation of the gravity field and steady-state ocean circulation explorer mission

The European Space Agency’s Gravity field and steady-state ocean circulation explorer mission (GOCE) was launched on 17 March 2009. As the first of the Earth Explorer family of satellites within the Agency’s Living Planet Programme, it is aiming at a better understanding of the Earth system. The mission objective of GOCE is the determination of the Earth’s gravity field and geoid with high accuracy and maximum spatial resolution. The geoid, combined with the de facto mean ocean surface derived from twenty-odd years of satellite radar altimetry, yields the global dynamic ocean topography. It serves ocean circulation and ocean transport studies and sea level research. GOCE geoid heights allow the conversion of global positioning system (GPS) heights to high precision heights above sea level. Gravity anomalies and also gravity gradients from GOCE are used for gravity-to-density inversion and in particular for studies of the Earth’s lithosphere and upper mantle. GOCE is the first-ever satellite to carry a gravitational gradiometer, and in order to achieve its challenging mission objectives the satellite embarks a number of world-first technologies. In essence the spacecraft together with its sensors can be regarded as a spaceborne gravimeter. In this work, we describe the mission and the way it is operated and exploited in order to make available the best-possible measurements of the Earth gravity field. The main lessons learned from the first 19 months in orbit are also provided, in as far as they affect the quality of the science data products and therefore are of specific interest for GOCE data users.     

联合高低卫-卫跟踪和卫星重力梯度数据恢复地球重力场的谱组合法

GOCE采用的高低卫-卫跟踪和卫星重力梯度测量技术在恢复重力场方面各有所长并互为补充,如何有效利用这两类观测数据最优确定地球重力场是GOCE重力场反演的关键问题。本文研究了联合高低卫-卫跟踪和卫星重力梯度数据恢复地球重力场的最小二乘谱组合法,基于球谐分析方法推导并建立了卫星轨道面扰动位T和径向重力梯度Tzz、以及扰动位T和重力梯度分量组合{Tzz-Txx-Tyy}的谱组合计算模型与误差估计公式。数值模拟结果表明,谱组合计算模型可以有效顾及各类数据的精度和频谱特性进行最优联合求解。采用61天GOCE实测数据反演的两个180阶次地球重力场模型WHU_GOCE_SC01S（扰动位和径向重力梯度数据求解）和WHU_GOCE_SC02S（扰动位和重力梯度分量组合数据求解）,结果显示后者精度优于前者,并且它们的整体精度优于GOCE时域解,而与GOCE空域解的精度接近,验证了谱组合法的可行性与有效性。