联合EGM2008模型重力异常和GOCE观测数据构建超高阶地球重力场模型SGG-UGM-1

本文研究了联合卫星观测数据和重力异常数据确定超高阶重力场模型的理论方法,并使用EGM2008模型重力异常和GOCE（gravity field and ocean circulation explorer）观测数据构建了重力场模型SGG-UGM-1。重点研究了由球面格网重力异常快速构建超高阶重力场模型的块对角最小二乘方法,将OpenMP技术引入到块对角最小二乘中以提高计算效率,并基于模拟数据验证了方法及算法和软件模块的正确性。采用本文制定的联合解算策略,利用GOCE重力卫星观测数据构建的220阶次法方程和EGM2008模型重力异常构建的2159阶次块对角法方程,联合求解了2159阶次的重力场模型SGG-UGM-1。将SGG-UGM-1与EGM2008、EIGEN-6C2、EIGEN-6C4等超高阶模型在频谱域内进行了比较分析,结果表明SGG-UGM-1相对参考模型的系数误差较小,且在220阶次内的系数精度相比EGM2008模型有了提高。采用中国与美国的GPS/水准数据和毛乌素测区的航空重力观测数据对这些模型进行了外符合精度的检验。检核结果表明,在中国区域,SGG-UGM-1模型大地水准面的精度在EIGEN-6C2和EIGEN-6C4两个模型之间,优于GOSG-EGM模型和EGM2008模型,与美国区域几个模型的精度相当。利用毛乌素测区的航空重力数据对几个模型进行了检核,结果表明SGG-UGM-1模型计算的重力扰动精度与EGM2008、EIGEN-6C4模型相当,优于GOSG-EGM模型和EIGEN-6C2模型。     

利用GOCE模拟观测反演重力场的Torus法

在介绍Torus方法反演地球重力场模型的基本原理和方法的基础上,基于圆环面上均匀分布的卫星引力梯度模拟观测值解算了200阶次的地球重力场模型,在无误差情况下,Torus方法解算模型的阶误差RMS小于10-16,验证了该方法的严密性。利用61dGOCE卫星轨道上无误差的模拟引力梯度观测值解算了200阶次的地球重力场模型,分析了格网化误差、极空白对解算精度的影响,迭代3次后,在不考虑低次系数情况下,模型的大地水准面阶误差和累积误差均较小,最大值仅为0.022mm和0.099mm。在沿轨卫星引力梯度模拟数据中加入5mE/Hz1/2的白噪声,基于Torus方法和空域最小二乘法解算了200阶次的地球重力场模型,Torus方法的精度略低于空域最小二乘法的精度,在不考虑低次项的情况下,两种方法解算模型的大地水准面阶误差最大值分别为1.58cm和1.45cm,累积误差最大值分别为6.37cm和5.55cm。但由于采用了二维快速傅里叶技术和块对角最小二乘法,极大地提高了计算效率。本文数值结果说明Torus方法是一种独立有效的方法,可用于GOCE任务海量卫星引力梯度观测值反演重力场的快速解算。     

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。     

国外研究地球外部重力场的近况

当前世界上地球外部重力场的研究工作有了很大的进展,它涉及到许多学科。本文仅就近几年来的国外资料分别按下列六个方面作扼要的介绍: 一、重力测量; 二、最小二乘配置和地球重力场; 三、卫星重力的新方法; 四、大地测量基本参数和地球模型; 五、动力大地测量; 六、地球重力固体潮;     

超高阶重力场模型最小二乘快速实现

采用最小二乘方法解算超高阶重力场模型,不可避免会遇到大型矩阵的计算,直接求解是难以实现的。本文从重力场模型的基本观测方程出发,利用正余弦函数和面球谐因子的正交性,分析系数矩阵及法矩阵的特点,在法矩阵块对角化的基础上,利用系数矩阵求解法矩阵时“次m”递增的特点,对法矩阵求解方程进行约化、对Legendre函数的计算和存储方式进行了设计,结合缔合Legendre函数关于赤道的对称性,解决了大型矩阵存储及计算效率低下的难题,实现了超高阶重力场模型最小二乘方法的小存储、高效率的解算。通过试验模拟,改进后的方法相比传统块对角方法效率提高300倍,利用此方法可以在普通PC机上快速、高精度地解算2160阶次超高阶重力场模型,算法精度相比数值积分方法至少提高了5个数量级,并且在一定程度上可以评估原始观测数据的精度。     

基于空域最小二乘法求解GOCE卫星重力场的模拟研究

本文论述了最小二乘过程中有色噪声的处理方法,提出使用AR模型对GOCE梯度观测值中的有色噪声进行时域滤波,数值模拟结果验证了该方法的有效性。利用数值模拟验证了直接求逆方法和PCCG法求解大型法方程的有效性,后者的效率远远高于前者。联合加入噪声（有色噪声和白噪声）的卫星重力梯度张量径向分量观测值Vzz和SST观测值,分别使用空域最小二乘法和SA方法恢复了180阶全球重力场模型,前者求解重力场模型的大地水准面和重力异常在180阶次的精度分别为3.01cm和0.75mGal,优于SA方法求解模型的精度。     

平稳随机函数在重力场逼近中的应用

随着卫星测高、卫星跟踪卫星和卫星重力梯度等空间重力探测技术的不断进步，出现了垂线偏差、重力梯度等新的重力场观测信息，综合有效使用上述信息资源已成为重力场研究应用的关键。本文分析了地球扰动场元的随机平稳特征，研究了综合利用各类重力场观测信息根据最小二乘配置理论逼近任一待求扰动场元的协方差函数?     

利用能量法由沿轨扰动位数据恢复位系数精度分析

讨论了在基于能量法确定地球重力场模型的过程中，利用最小二乘方法由沿轨扰动位数据解算位系数时法方程的特性，在该问题中，法方程只与卫星轨道有关。基于这一特点，阐明了最小二乘解算结果与是否使用参考重力场模型是无关的。在此基础上，根据不同的噪声水平，模拟了4种不同精度的沿轨扰动位观测值。分别进行了重力场模型恢复并分析了其恢复精度。结果表明，在现有加速度计校准水平下，能量法恢复重力场模型难以达到动力法的精度，用于时变研究尚存在一定的困难。     

GOCE卫星测量恢复地球重力场模型的理论与方法

研究了GOCE卫星测量恢复地球重力场模型的理论与方法。论文的主要工作和创新点有： (1) 建立了扰动重力梯度张量各分量没有奇异性的详细计算模型,解决了重力梯度张量Txx分量在两极地区计算的奇异性难题。 (2) 系统研究了卫星重力梯度数据向下延拓的解析法、泊松积分迭代法和卫星重力梯度数据格网化的移动平均法、反距离加权法、普通克里金法,建立了相应的数学模型,导出了相应的计算公式,并采用“直接法”和“移去-恢复法”两种方案对其向下延拓和格网化效果进行了测试。 (3) 分析了能量守恒方程中各项误差对沿轨扰动位计算结果的影响,建立了利用GOCE模拟数据确定地球重力场的最小二乘直接法、调和分析法、最小二乘配置法的实用数学模型,并做了大量的模拟计算。 (4) 建立了利用扰动引力梯度张量各单分量和组合分量确定地球重力场的最小二乘直接法去奇异性计算模型;推导了利用扰动引力梯度张量单分量和组合分量解算地球重力场的调和分析法模型;进一步推导了扰动引力梯度张量各个分量之间的自协方差和互协方差函数及其与引力位系数之间协方差函数的具体计算公式。 (5) 推导了利用不同类型重力测量数据确定地球重力场的联合平差法数学模型,介绍并分析了模型中各类数据最优定权的参数协方差法和方差分量估计法。 (6) 论述了谱组合法的基本原理,给出了多种类型重力测量数据联合处理的谱权及谱组合的通用表达式,基于调和分析方法推导了SST+SGG、SST+SGG＋Δg和SST+SGG＋Δg+N恢复地球重力场模型的谱组合公式及对应谱权的具体形式。 (7) 推导了利用迭代法联合不同类型重力测量数据反演地球重力场模型的基本原理公式,并给出了其具体实现步骤。 (8) 分析并计算了重力卫星轨道高度、卫星星间距离和卫星轨道倾角的设计指标;讨论了双星轨道长半轴的一致性要求、双星姿态俯仰角的控制要求以及双星编队保持机动的时间间隔要求。 (9) 确定了KBR系统的星间距离、星间距离变化率和星间加速度的精度指标;设计了星载GPS系统的卫星轨道位置和速度以及加速度计测量的精度指标;计算了加速度计检验质量质心到卫星质心的调整距离精度指标;分析了恒星敏感器的姿态角测量精度和稳定度;计算了参考重力场模型对于累计大地水准面精度和积分卫星轨道的影响。 (10) 研制了一套利用卫星重力测量数据反演地球重力场模型的软件平台,可对卫星重力测量数据处理及其精度评估提供一些基本方法,并为我国卫星重力测量系统的总体战技指标和主要有效载荷技术指标的量化分析、论证提供理论和技术支持,为我国未来的卫星重力测量系统提供可能的积累和参考。     

利用卫星重力数据确定地球外部重力场的一种方法及模拟实验检验

假定给定了海量的卫星重力观测数据，基于球谐展开法并应用最小二乘原理可以确定地球重力场模型EGM，由此确定的重力场模型在地球表面附近的空间区域未必有效。设想有一个包含了地球的大球Ks，假定EGM在大球的外部成立，则可根据虚拟压缩恢复法求出一种新的重力场模型NEGM，它是对原有重力场模型的进一步精化，适合于整个地球外部空间，从理论上可以解决重力场的“向下延拓”问题。初步的模拟实验检验支持虚拟压缩恢复法以及由此而引中出的“向下延拓”法。     

Exploring gravity field determination from orbit perturbations of the European Gravity Mission GOCE

 A comparison was made between two methods for gravity field recovery from orbit perturbations that can be derived from global positioning system satellite-to-satellite tracking observations of the future European gravity field mission GOCE (Gravity Field and Steady-State Ocean Circulation Explorer). The first method is based on the analytical linear orbit perturbation theory that leads under certain conditions to a block-diagonal normal matrix for the gravity unknowns, significantly reducing the required computation time. The second method makes use of numerical integration to derive the observation equations, leading to a full set of normal equations requiring powerful computer facilities. Simulations were carried out for gravity field recovery experiments up to spherical harmonic degree and order 80 from 10 days of observation. It was found that the first method leads to large approximation errors as soon as the maximum degree surpasses the first resonance orders and great care has to be taken with modeling resonance orbit perturbations, thereby loosing the block-diagonal structure. The second method proved to be successful, provided a proper division of the data period into orbital arcs that are not too long. Received: 28 April 2000 / Accepted: 6 November 2000     

Efficient GOCE satellite gravity field recovery based on least-squares using QR decomposition

We develop and apply an efficient strategy for Earth gravity field recovery from satellite gravity gradiometry data. Our approach is based upon the Paige-Saunders iterative least-squares method using QR decomposition (LSQR). We modify the original algorithm for space-geodetic applications: firstly, we investigate how convergence can be accelerated by means of both subspace and block-diagonal preconditioning. The efficiency of the latter dominates if the design matrix exhibits block-dominant structure. Secondly, we address Tikhonov-Phillips regularization in general. Thirdly, we demonstrate an effective implementation of the algorithm in a high-performance computing environment. In this context, an important issue is to avoid the twofold computation of the design matrix in each iteration. The computational platform is a 64-processor shared-memory supercomputer. The runtime results prove the successful parallelization of the LSQR solver. The numerical examples are chosen in view of the forthcoming satellite mission GOCE (Gravity field and steady-state Ocean Circulation Explorer). The closed-loop scenario covers 1 month of simulated data with 5 s sampling. We focus exclusively on the analysis of radial components of satellite accelerations and gravity gradients. Our extensions to the basic algorithm enable the method to be competitive with well-established inversion strategies in satellite geodesy, such as conjugate gradient methods or the brute-force approach. In its current development stage, the LSQR method appears ready to deal with real-data applications.     

Marine gravity and geoid determination by optimal combination of satellite altimetry and shipborne gravimetry data

. Satellite altimetry derived geoid heights and marine gravity anomalies can be combined to determine a detailed gravity field over the oceans using the least-squares collocation method and spectral combination techniques. Least-squares collocation, least-squares adjustment in the frequency domain and input-output system theory are employed to determine the gravity field (both geoid and anomalies) and its errors. This paper intercompares these three techniques using simulated data. Simulation studies show that best results are obtained by the input-output system theory among the three prediction methods. The least-squares collocation method gives results which are very close to but a little bit worse than those obtained using input-output system theory. This slightly poorer performance of the least-squares collocation method can be explained by the fact that it uses isotropic structured covariance (thus approximate signal PSD information) while the system theory method uses detailed signal PSD information. The method of least-squares adjustment in the frequency domain gives the poorest results among these three methods because it uses less information than the other two methods (it ignores the signal PSDs). The computations also show that the least-squares collocation and input-output system theory methods are not as sensitive to noise levels as the least-squares adjustment in the frequency domain method is. Received 19 January 1996; Accepted 17 July 1996     

Solving three types of satellite gravity gradient boundary value problems by least-squares

The principle and method for solving three types of satellite gravity gradient boundary value problems by least-squares are discussed in detail. Also, kernel function expressions of the least-squares solution of three geodetic boundary value problems with the observations {Гzz}, {Гxz, Гyz} and {Гxx ? Гyy, 2Гxy} are presented. From the results of recovering gravity field using simulated gravity gradient tensor data, we can draw a conclusion that satellite gravity gradient integral formulas derived from least-squares are valid and rigorous for recovering the gravity field.     

Short-wavelength Spectral Properties of the Gravity Field from a Range of Regional Data Sets

The GRACE (gravity recovery and climate experiment) and GOCE (gravity field and steady-state ocean circulation explorer) dedicated gravity satellite missions are expected to deliver the long-wavelength scales of the Earth’s gravity field with extreme precision. For many applications in Earth sciences, future research activities will have to focus on a similar precision on shorter scales not recovered by satellite missions. Here, we investigate the signal power of gravity anomalies at such short scales. We derive an average degree variance and power spectral density model for topography-reduced gravity anomalies (residual terrain model anomalies and de-trended refined Bouguer anomalies), which is valid for wavelengths between 0.7 and 100  km. The model is based on the analysis of gravity anomalies from 13 test regions in various geographical areas and geophysical settings, using various power spectrum computation approaches. The power of the derived average topography-reduced model is considerably lower than the Tscherning–Rapp free air anomaly model. The signal power of the individual test regions deviates from the obtained average model by less than a factor of 4 in terms of square-root power spectral amplitudes. Despite the topographic reduction, the highest signal power is found in mountainous areas and the lowest signal power in flat terrain. For the derived average power spectral model, a validation procedure is developed based on least-squares prediction tests. The validation shows that the model leads to a good prediction quality and realistic error measures. Therefore, for least-squares prediction, the model could replace the use of autocovariance functions derived from local or regional data.     

重力三层点质量模型的构造与分析

点质量模型理论是研究区域重力场的一个非常重要的方法,本文简要介绍了点质量模型逼近区域重力场的原理,计算分析了构造点质量模型过程中系数矩阵元素的特性。以32~34N和103~105E为计算中心区域,利用EGM2008的720阶次的位系数计算出的重力异常作为观测数据,在36阶次位系数模型的基础上,构造了四层点质量组分频段从低到高来逼近该区域重力场。数值试验的结果表明：三层点质量模型效果较好,点质量模型计算的扰动重力在径向上的截断误差优于2 .