低低卫星跟踪卫星数据精化时变重力场的关键问题研究

The successful implementation of the GRACE satellite has opened a new era for the understanding of the internal structure of the earth and the migration of its shallow layers, while the time and spatial resolution of GRACE temporal gravity field model has limited its application range. How to further extract the effective information of low-low satellite-to-satellite tracking data, and comprehensively improve the accuracy and resolution of temporal gravity field, is one of the hot topics in satellite gravimetry. The primary objective of our project is to determine the high precision and high resolution temporal gravity field model after refining the observation data, prior force models and normal equations, respectively. The main contents, which focus on solving the key problems of refining temporal gravity field models with low-low satellite-to-satellite tracking data, are as follows: firstly, studying the processing method of refining the low-low satellite-to-satellite tracking data, which can dwindle the mutual influence of different observation errors; secondly, developing the method of simultaneously determining the temporal gravity field model and high-frequency non-tidal signals, which can reduce the temporal aliasing error from prior non-tidal models; thirdly, on the basis of multiple parameter regularization method and L-curve method, creating a self-adaption method to constrain the normal equation, which can solve the ill-posed problems in temporal gravity field model determination. The expected achievements can provide scientific data for us to cope with extreme climate change and major natural disaster. In addition, it will be used to accumulate experience for the development of our country's autonomous satellite program. Generally, our project has great scientific significance and practical value.

如何利用低低卫星跟踪卫星数据进一步提高时变重力场模型的精确度和分辨率，是当前卫星重力学的研究前沿和热点之一。本项目以精化时变重力场模型为目标，研究低低卫星跟踪卫星观测数据的精化处理方法、时域混频噪声的时空特征与处理方法以及时变重力场约束方程的自适应构建方法，解决不同载荷观测值误差互相影响的问题、先验大气海洋模型误差对时变重力场的时域混频问题以及时变重力场模型解算过程中的病态问题。预期研究成果不仅可为应对我国自然灾害提供重要的数据支撑，也为发展我国自主的重力卫星计划提供技术参考和软件平台，具有重要的科学意义和应用价值。

如何利用低低卫星跟踪卫星数据进一步提高时变重力场模型的精确度和分辨率，是当前卫星重力学的研究前沿和热点之一。项目组以获取高精度时变重力场模型为目标，完成了GRACE时变数据精细处理、星间距离变率低频噪声的成因分析及处理方法构建、时域混频噪声处理方法、时变重力场约束方程构建等既定研究内容，重点在“星间距离变率低频噪声的成因分析及处理方法”、“改进的动力学建模方法及HUST-Grace2019模型系列”、“卫星数据的精细处理和HUST-Grace2020模型序列”、“顾及时域混频噪声的时变重力场建模方法”、 “下一代多组重力卫星组合模拟”、“联合GRACE和GOCE卫星的静态重力场模型HUST-GOGRA2018s”、“GRACE时变重力场的科学应用研究”等方面取得了一系列理论及应用研究成果。在上述研究基础上，项目组建立了利用低低卫星跟踪卫星数据精化时变重力场的实用算法与软件平台，并最终分别解算了时变重力场模型HUST-Grace2019和HUST-Grace2020模型序列。其中，时变重力场模型序列HUST-Grace2019优于CSR、GFZ和JPL官方机构同时期发布的第五代模型产品，时变重力场模型序列HUST-Grace2020优于CSR、GFZ和JPL官方机构最新发布的第六代模型产品，最新发布的HUST-Grace2020模型序列已被国际地球重力场模型中心ICGEM收录。