利用先验重力场模型对GOCE卫星重力梯度观测值进行校准分析

GOCE卫星任务搭载了高灵敏度的重力梯度仪,其观测值用于恢复高精度高分辨率的地球重力场。本文利用EIGEN-5C、EGM2008、GOTIM3、GGM03S高精度全球重力场模型,确定了GOCE引力梯度张量的对角分量观测值(Vxx、Vyy、Vzz)的校准参数,分析了比例因子的稳定性,并讨论了相同模型不同阶次、同阶次不同模型以及是否估计漂移参数对比例因子、偏差参数及校准观测值的影响。研究表明比例因子的稳定性在10-4的量级,利用250阶的EIGEN-5C模型和EGM2008模型校准得到观测值的差异小于10-4 E,远远小于观测误差,以1d为周期估计校准参数时,是否估计漂移对校准结果的影响达到0.4E。同时,校准前后观测值差异的频谱说明校准过程主要影响Vxx、Vyy、Vzz观测值的低频部分,即来自先验重力场模型的中低(150)阶次,考虑到GOCE引力梯度的观测频带,校准后的观测值可用于恢复中高频的重力场信号。     

GOCE卫星轨道摄动的数值模拟与分析

采用动力学轨道积分方法模拟了GOCE卫星轨道,利用模拟轨道估计了GOCE卫星主要摄动加速度的量级及贡献,分析了日月引力、固体潮、海潮、大气潮和固体极潮等保守力对GOCE卫星运动和重力梯度观测值的影响。结果表明:①在1.0ⅹ10-9m/s2的非保守力测量精度内,除大气潮可忽略外,其余摄动必须考虑;②考虑GOCE预期定轨精度(3 cm),在弧长小于2.0 h的短弧定轨中,固体极潮和大气潮的影响可忽略,在长弧定轨中,忽略任何一种保守力的轨道预报时间均不足0.5 d;③各种潮汐对重力梯度观测值的影响量级均小于GOCE预期的测量精度(3 mE)。考虑潮汐对重力梯度观测值的影响不具有随机性和避免重力场信号混叠等因素,必须对重力梯度观测值进行潮汐改正。     

由GOCE引力梯度张量不变量确定卫星重力模型的半解析法

提出了利用半解析方法解算重力场与稳态海洋环流探测器(gravity field and steady-state ocean circulation explorer,GOCE)引力梯度张量不变量观测值来恢复全球卫星重力模型的方法,该方法比最小二乘方法效率高,同样可给出模型的验后方差。推导了半解析法快速解算引力梯度张量不变量的理论公式,给出了该方法利用卫星重力梯度观测数据快速求解重力场模型的基本步骤。利用89.5°倾角圆形严格重复轨道上的模拟梯度观测值验证了半解析方法用于张量不变量解算的理论严密性,并利用GOCE任务61 d 梯度仪坐标系(gradiometer reference frame,GRF)下无噪声和有噪声的I₂和V_zz模拟观测值进行了模型反演和结果分析。结果表明,利用I₂观测值求解模型的精度略优于仅用V_zz分量解算模型的精度。     

GOCE卫星重力梯度观测值的时变重力场变化改正及影响分析

GOCE卫星重力梯度观测值为高阶静态重力场反演提供了重要的数据支撑,但其在使用前需考虑扣除时变重力场变化的影响.本文研究了GOCE卫星重力梯度观测值的时变重力场变化改正方法,更新了ESA标准和背景模型,以更好地扣除时变重力场变化的影响,自主实现了由GOCE卫星Level1b重力梯度数据直接进行重力场反演.本文通过3种时...     

GOCE卫星重力梯度测量数据的预处理

GOCE(gravity field and steady-state ocean circulation explorer)计划的主要科学目标是以70 km空间分辨率1、mGal重力异常和1~2 cm大地水准面的精度测定全球静态地球重力场,卫星重力梯度测量数据的预处理是实现这一预期科学目标的重要任务之一。讨论了重力梯度测量数据的预处理方案、时变重力场信号改正、粗差探测和外部校准方法,为进一步开展GOCE卫星重力梯度测量数据的预处理研究提供参考和具体建议。     

天文潮汐对卫星重力梯度观测数据的影响分析

测定地球重力场,确定高分辨率的静态地球重力场模型,是大地测量学的主要任务之一.重力场的影响主要分为潮汐部分和非潮汐部分,天文潮汐在潮汐部分中属于直接引力效应,对重力场的影响是不可忽略的.本文以一个月的星历数据为基础,分析了天文潮汐对GOCE卫星重力梯度观测数据的影响,并统计了最大值和最小值;研究了天文潮汐对地球上单点重力梯度数据的影响特征;计算了各行星对卫星重力梯度数据影响量级.研究结果表明:天文潮汐对卫星重力梯度数据的影响量级处于0.1mE,比GOCE卫星设计精度低一个量级,但是它具有周期性,属于有色噪声,因此在卫星重力梯度数据预处理中需要扣除;天文潮汐对卫星重力梯度数据各分量的影响不同,其中对角线分量Vxx,Vyy和Vzz要比其他分量略大;月球和太阳对卫星重力梯度数据的影响最大,在所有星体中占据主导地位.     

海洋潮汐对卫星重力梯度观测数据的影响分析

采用CSR4.0、TPXO7.2和FES2004三个不同海潮模型计算了2009年11月1日至2009年12月1日海洋潮汐对GOCE卫星重力梯度观测数据的影响,其影响量级都处于0.1m E,比GOCE卫星设计精度(3.2m E)略低,但其为有色噪声源,因此,必须在数据预处理中考虑这一部分的影响。除此之外,分析了三个不同海潮模型对地球重力场位系数的影响,三者对10阶以下位系数影响存在较大的差异,说明目前海潮模型之间还存在较大的差异,海潮模型的精度仍然需要提高。     

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。     

卫星重力梯度观测数据的时变信号影响分析

系统地讨论了时变重力中潮汐信号与非潮汐信号对GOCE卫星重力梯度观测数据的影响。结果表明:(1)时变改正的量级为0.1 mE,比GOCE卫星设计精度(3.2 mE)低,但其为有色噪声,在数据预处理中必须剔除;(2)潮汐影响(0.1 mE)比非潮汐影响(0.01 mE)要高一个量级,决定着时变重力改正的精度。将本文计算结果与GOCE官方公布结果进行对比,二者具有较好一致性,验证了本文计算方法及结果的有效性。     

联合GOCE卫星轨道和重力梯度数据严密求解重力场的模拟研究

论述了联合卫星轨道和重力梯度数据严密求解重力场的方法及数据处理方案,研究了GOCE重力场反演中有色噪声的AR去相关滤波、病态法方程的Kaula正则化和观测值最优加权的方差分量估计等关键问题。模拟结果表明:①极空白问题会降低法方程求解的稳定性,导致低次位系数的求解精度较低,而Kaula正则化可有效用于GOCE病态法方程的求解,并得到合理稳定的解;②重力梯度有色噪声会降低GOCE重力场求解的整体精度,特别是对低阶位系数的影响最为明显,而AR去相关滤波法可有效处理有色噪声,但解算结果仍含有低频误差;③方差分量估计可有效确定SST和SGG两类观测值的最优权比,并且有色噪声造成的低频误差经过联合求解后得到了抑制;④利用30d、5s采样的GOCE模拟数据恢复200阶次的重力场模型,其大地水准面和重力异常精度在纬度±83°范围内分别为±3.81cm和±1.056mGal。     

Preprocessing of gravity gradients at the GOCE high-level processing facility

One of the products derived from the gravity field and steady-state ocean circulation explorer (GOCE) observations are the gravity gradients. These gravity gradients are provided in the gradiometer reference frame (GRF) and are calibrated in-flight using satellite shaking and star sensor data. To use these gravity gradients for application in Earth scienes and gravity field analysis, additional preprocessing needs to be done, including corrections for temporal gravity field signals to isolate the static gravity field part, screening for outliers, calibration by comparison with existing external gravity field information and error assessment. The temporal gravity gradient corrections consist of tidal and nontidal corrections. These are all generally below the gravity gradient error level, which is predicted to show a 1/f behaviour for low frequencies. In the outlier detection, the 1/f error is compensated for by subtracting a local median from the data, while the data error is assessed using the median absolute deviation. The local median acts as a high-pass filter and it is robust as is the median absolute deviation. Three different methods have been implemented for the calibration of the gravity gradients. All three methods use a high-pass filter to compensate for the 1/f gravity gradient error. The baseline method uses state-of-the-art global gravity field models and the most accurate results are obtained if star sensor misalignments are estimated along with the calibration parameters. A second calibration method uses GOCE GPS data to estimate a low-degree gravity field model as well as gravity gradient scale factors. Both methods allow to estimate gravity gradient scale factors down to the 10⁻³ level. The third calibration method uses high accurate terrestrial gravity data in selected regions to validate the gravity gradient scale factors, focussing on the measurement band. Gravity gradient scale factors may be estimated down to the 10⁻² level with this method.     

Calibrating the GOCE accelerations with star sensor data and a global gravity field model

A reliable and accurate gradiometer calibration is essential for the scientific return of the gravity field and steady-state ocean circulation explorer (GOCE) mission. This paper describes a new method for external calibration of the GOCE gradiometer accelerations. A global gravity field model in combination with star sensor quaternions is used to compute reference differential accelerations, which may be used to estimate various combinations of gradiometer scale factors, internal gradiometer misalignments and misalignments between star sensor and gradiometer. In many aspects, the new method is complementary to the GOCE in-flight calibration. In contrast to the in-flight calibration, which requires a satellite-shaking phase, the new method uses data from the nominal measurement phases. The results of a simulation study show that gradiometer scale factors can be estimated on a weekly basis with accuracies better than 2 × 10⁻³ for the ultrasensitive and 10⁻² for the less sensitive axes, which is compatible with the requirements of the gravity gradient error. Based on a 58-day data set, scale factors are found that can reduce the errors of the in-flight-calibrated measurements. The elements of the complete inverse calibration matrix, representing both the internal gradiometer misalignments and scale factors, can be estimated with accuracies in general better than 10⁻³.     

联合GOCE卫星数据和GRACE法方程确定SWJTU-GOGR01S全球重力场模型

联合地球重力场和海洋环流探测器（Gravity Field and Steady-State Ocean Circulation Explorer,GOCE）和重力恢复与气候实验（Gravity Recovery and Climate Experiment,GRACE）卫星观测数据确定全球静态重力场模型是当前大地测量学的研究热点之一。联合近3 a的GOCE卫星梯度数据和7 a左右的GRACE星间距离变率数据计算的ITG-GRACE2010S模型的法方程恢复了210阶次的重力场模型SWJTU-GOGR01S。采用带通数字滤波方法处理GOCE卫星的4个高精度梯度观测分量,利用梯度数据恢复重力场模型的观测方程直接建立在梯度仪坐标系中,可以避免坐标转换过程中高精度的梯度观测分量受低精度分量的影响;联合法方程解的最优权采用方差分量估计迭代计算,GOCE数据的两极空白引起的病态问题采用Kaula正则化方法进行约束。基于EIGEN-6C2模型和北美地区的GPS水准网观测数据,对SWJTU-GOGR01S模型进行内外符合精度分析,结果表明,SWJTU-GOGR01S模型在210阶次的大地水准面误差和累计误差分别为1.3 cm和5.7 cm,精度与欧洲空间局公布的第四代时域法模型相当,略优于GOCO02S和GOCO03S模型的精度。     

GOCE引力梯度内部校准方法

GOCE卫星引力梯度仪的精确校准是反演高精度重力场的前提之一,本文利用GOCE卫星L1b数据中的引力梯度仪及恒星敏感器数据实现了卫星引力梯度的内部校准。以最小二乘联合多个恒星敏感器观测数据确定内部校准使用的角速度,有效避免了单个恒星敏感器低精度角速度分量对坐标转换过程的影响。考虑到恒星敏感器坐标系与梯度仪坐标系间旋转矩阵随时间的变化,本文在ESA官方内部校准方法的基础上,提出了顾及旋转矩阵校准参数的内部校准模型,并利用2009年11月的GOCE实测数据验证了该方法的效果。结果表明,该旋转矩阵校准参数数值约100″,且在该月存在3″~30″的漂移;与GOCE官方内部校准方法对比,从卫星引力梯度精度结果来看,在低于0.005 Hz频段内,同时解算旋转矩阵的校准参数与梯度仪内3个加速度计对的校准参数的内部校准模型优于仅考虑加速度计对校准参数的模型;除此之外,本文讨论了以该模型为基础的GOCE梯度仪数据校准的可能方法,为GOCE及后续重力卫星的数据处理工作提供参考。     

Monitoring GOCE gradiometer calibration parameters using accelerometer and star sensor data: methodology and first results

The Gravity field and steady-state Ocean Circulation Explorer (GOCE) satellite, launched on 17 March 2009, is designed to measure the Earth’s mean gravity field with unprecedented accuracy at spatial resolutions down to 100?km. The accurate calibration of the gravity gradiometer on-board GOCE is of utmost importance for achieving the mission goals. ESA’s baseline method for the calibration uses star sensor and accelerometer data of a dedicated calibration procedure, which is executed every 2?months. In this paper, we describe a method for monitoring the evolution of calibration parameter during that time. The method works with star sensor and accelerometer data and does not require gravity field models, which distinguishes it from other existing methods. We present time series of calibration parameters estimated from GOCE data from 1 November 2009 to 17 May 2010. The time series confirm drifts in the calibration parameters that are present in the results of other methods, including ESA’s baseline method. Although these drifts are very small, they degrade the gravity gradients, leading to the conclusion that the calibration parameters of the ESA’s baseline method need to be linearly interpolated. Further, we find a correction of ?36 × 10^?6 for one calibration parameter (in-line differential scale factor of the cross-track gradiometer arm), which improves the gravity gradient performance. The results are validated by investigating the trace of the calibrated gravity gradients and comparing calibrated gravity gradients with reference gradients computed along the GOCE orbit using the ITG-Grace-2010s gravity field model.     

The gravity field model IGGT_R1 based on the second invariant of the GOCE gravitational gradient tensor

Based on tensor theory, three invariants of the gravitational gradient tensor (IGGT) are independent of the gradiometer reference frame (GRF). Compared to traditional methods for calculation of gravity field models based on the gravity field and steady-state ocean circulation explorer (GOCE) data, which are affected by errors in the attitude indicator, using IGGT and least squares method avoids the problem of inaccurate rotation matrices. The IGGT approach as studied in this paper is a quadratic function of the gravity field model’s spherical harmonic coefficients. The linearized observation equations for the least squares method are obtained using a Taylor expansion, and the weighting equation is derived using the law of error propagation. We also investigate the linearization errors using existing gravity field models and find that this error can be ignored since the used a-priori model EIGEN-5C is sufficiently accurate. One problem when using this approach is that it needs all six independent gravitational gradients (GGs), but the components \(V_{xy}\) and \(V_{yz}\) of GOCE are worse due to the non-sensitive axes of the GOCE gradiometer. Therefore, we use synthetic GGs for both inaccurate gravitational gradient components derived from the a-priori gravity field model EIGEN-5C. Another problem is that the GOCE GGs are measured in a band-limited manner. Therefore, a forward and backward finite impulse response band-pass filter is applied to the data, which can also eliminate filter caused phase change. The spherical cap regularization approach (SCRA) and the Kaula rule are then applied to solve the polar gap problem caused by GOCE’s inclination of \(96.7^{\circ }\). With the techniques described above, a degree/order 240 gravity field model called IGGT_R1 is computed. Since the synthetic components of \(V_{xy}\) and \(V_{yz}\) are not band-pass filtered, the signals outside the measurement bandwidth are replaced by the a-priori model EIGEN-5C. Therefore, this model is practically a combined gravity field model which contains GOCE GGs signals and long wavelength signals from the a-priori model EIGEN-5C. Finally, IGGT_R1’s accuracy is evaluated by comparison with other gravity field models in terms of difference degree amplitudes, the geostrophic velocity in the Agulhas current area, gravity anomaly differences as well as by comparison to GNSS/leveling data.     

Alternative method for angular rate determination within the GOCE gradiometer processing

The most crucial part of the GOCE gradiometer processing is, besides the internal calibration of the gradiometer, the determination of the satellite’s inertial angular rate. This paper describes a new method for the angular rate determination. It is based on the stochastic properties of the GOCE star sensors and the gradiometer. The attitude information of both instrument types is combined at the level of angular rates. The combination is done in the spectral domain by Wiener filtering, and thus using an optimal relative weighting of the star sensor and gradiometer attitude information. Since the complete processing chain from raw measurements to gravity field solutions is performed, the results are not only analyzed at the level of gravity gradients, but also of gravity field solutions. Compared to the nominal method, already the resulting gravity gradients show a significantly improved performance for the frequencies (mainly) below the gradiometer measurement bandwidth. This can be verified by analysis of the gravity gradient trace. The improvement is propagated to the level of gravity field models, where a better accuracy can be observed for selected groups of coefficients at characteristic bands at orders k × 16, with integer k, up to high harmonic degrees.