对地观测卫星访问区域目标时间窗口快速算法

为减少对地观测卫星访问区域目标时间窗口的计算,根据建立的卫星对区域目标的观测模型,提出了卫星观测区域目标时间窗口的大圆近似快速算法,给出了算法具体步骤。仿真算例结果表明:时间窗口起点误差小于0.5 s,时间窗口长度误差小于0.723%,计算时间减少了99.87%.     

2012–2014 China's Earth Observation and Earth Science Development

Human beings are now facing global and regional sustainable development challenges.In China, Earth observation data play a fundamental role in Earth system science research. The support given by Earth observation data is required by many studies, including those on Earth's limited natural resources, the rapid development of economic and social needs, global change, extreme events, food security, water resources, sustainable economic and urban development, and emergency response. Application operation systems in many ministries and departments in China have entered a stage of sustainable development, and the State Key Project of High-Resolution Earth Observation Systems has been progressing since 2006. Earth observation technology in China has entered a period of rapid development.     

Real-time zenith tropospheric delays in support of numerical weather prediction applications

The Geodetic Observatory Pecný (GOP) routinely estimates near real-time zenith total delays (ZTD) from GPS permanent stations for assimilation in numerical weather prediction (NWP) models more than 12 years. Besides European regional, global and GPS and GLONASS solutions, we have recently developed real-time estimates aimed at supporting NWP nowcasting or severe weather event monitoring. While all previous solutions are based on data batch processing in a network mode, the real-time solution exploits real-time global orbits and clocks from the International GNSS Service (IGS) and Precise Point Positioning (PPP) processing strategy. New application G-Nut/Tefnut has been developed and real-time ZTDs have been continuously processed in the nine-month demonstration campaign (February–October, 2013) for selected 36 European and global stations. Resulting ZTDs can be characterized by mean standard deviations of 6–10 mm, but still remaining large biases up to 20 mm due to missing precise models in the software. These results fulfilled threshold requirements for the operational NWP nowcasting (i.e. 30 mm in ZTD). Since remaining ZTD biases can be effectively eliminated using the bias-reduction procedure prior to the assimilation, results are approaching the target requirements in terms of relative accuracy (i.e. 6 mm in ZTD). Real-time strategy and software are under the development and we foresee further improvements in reducing biases and in optimizing the accuracy within required timeliness. The real-time products from the International GNSS Service were found accurate and stable for supporting PPP-based tropospheric estimates for the NWP nowcasting.     

一种卫星导航模拟器置信度评估方案及应用

置信度评估能够为卫星导航模拟器的研制与改进提供依据。提出了一种基于对数最小二乘的模糊层次分析法和相似度法相结合的置信度评估方案。该方案利用基于对数最小二乘的模糊层次分析法将卫星导航模拟器系统分解为若干子系统或模型,并利用相似度法计算各个子系统或模型的置信度,同时使用模糊层次分析法计算各子系统或模型的权重向量,而后再逐级综合得到模拟器系统的总置信度。该方案能够将复杂系统逐层细化,且求解的子系统或模型的权重向量与置信度较为客观真实,具有重要的工程参考价值。     

Adaptive neural network control of nonlinear systems with unknown dynamics

In this study, an adaptive neural network control approach is proposed to achieve accurate and robust control of nonlinear systems with unknown dynamics, wherein the neural network is innovatively used to learn the inverse problem of system dynamics with guaranteed convergence. This study focuses on the following three contributions. First, the considered system is transformed into a multi-integrator system using an input–output linearization technique, and an extended state observation technique is used to identify the transformed states. Second, an iterative control learning algorithm is proposed to achieve the neural network training, and stability analysis is given to prove that the network’s predictions converge to ideal control inputs with guaranteed convergence. Third, an adaptive neural network controller is developed by combining the trained network and a proportional-integral controller, and the long-standing challenge of model-based methods for control determination of unknown dynamics is resolved. Simulation results of a virtual control mission and an aerospace altitude tracking mission are provided to substantiate the effectiveness of the proposed techniques and illustrate the adaptability and robustness of the proposed controller.     

A priori zenith wet delays in the analysis of VLBI CONT sessions

Tropospheric delay is one of the major sources of error in VLBI (Very Long Baseline Interferometry) analysis. The principal component of this error can be accurately computed through reliable surface pressure data —hydrostatic delay— yet there is also a small but volatile component —wet delay— which is difficult to be modelled a priori. In VLBI analysis, troposphere delay is typically modelled in the theoretical delays using Zenith Hydrostatic Delays (ZHD) and a dry mapping function. Zenith Wet Delay (ZWD) is not modelled but estimated in the analysis process. This work studies inter alia the impact of including external GNSS estimates to model a priori ZWD in VLBI analysis, as well as other models of a priori ZWD.In a first stage, two different sources of GNSS troposphere products are compared to VLBI troposphere estimates in a period of 5 years. The solution with the best agreement to VLBI results is injected in the VLBI analysis as a priori ZWD value and is compared to other options to model a priori ZWD. The dataset used for this empirical analysis consists of the six CONT campaigns.It has been found that modelling a priori ZWD has no significant impact either on baseline length and coordinates repeatabilities. Nevertheless, modelling a priori ZWD can change the magnitude of the estimated coordinates a few millimeters in the up component with respect to the non-modelling approach. In addition, the influence of a priori ZWD on Earth Orientation Parameters (EOP) and troposphere estimates —Zenith Total Delays (ZTD) and gradients—has also been analysed, resulting in a small but significant impact on both geodetic products.     

GPS/BDS组合定位精度分析

随着定位技术的不断发展及多系统导航定位技术的逐步推广，多系统组合导航定位已经成为了GNSS导航定位领域中的主要发展趋势。主要阐述了GPS/BDS组合相对定位的观测方程和数学模型，并根据实测数据对比分析，从卫星可见性、精度因子、定位精度和均方根误差等方面对GPS、BDS及GPS/BDS组合定位系统的定位性能、定位精度进行了比较。研究结果表明，较单一的GPS和BDS系统定位，采用GPS/BDS组合定位可有效提高卫星可见数目和DOP值，且稳定性更好。GPS/BDS组合定位的定位精度也明显优于单一系统，这对GNSS高精度导航定位具有重要的参考价值。     

Accuracy analysis of GNSS-IR snow depth inversion algorithms

In recent years, with the continuous development of Global Navigation Satellite System (GNSS), it has been applied not only to navigation and positioning, but also to Earth surface environment monitoring. At present, when performing GNSS-IR (GNSS Interferometric Reflectometry) snow depth inversion, Lomb-Scargle Periodogram (LSP) spectrum analysis is mainly used to calculate the vertical height from the antenna phase center to the reflection surface. However, it has the problem of low identification of power spectrum analysis, which may lead to frequency leakage. Therefore, Fast Fourier Transform (FFT) spectrum analysis and Nonlinear Least Square Fitting (NLSF) are introduced to calculate the vertical height in this paper. The GNSS-IR snow depth inversion experiment is carried out by using the observation data of P351 station in PBO (Plate Boundary Observatory) network of the United States from 2013 to 2016. Three algorithms are used to invert the snow depth and compared with the actual snow depth provided by the station 490 in the SNOTEL network. The observations data of L1 and L2 bands are respectively used to find the optimal combination between different algorithms further to improve the accuracy of GNSS-IR snow depth inversion. For L1 band, different snow depths correspond to different optimal algorithms. When the snow depth is less than 0.8 m, the inversion accuracy of NLSF algorithm is the highest. When the snow depth is greater than 0.8 m, the inversion accuracy of FFT algorithm is higher. Therefore, according to the different snow depth, a combined algorithm of NLSF + FFT is proposed for GNSS-IR snow depth inversion. Compared with the traditional LSP algorithm, the inversion accuracy of the combined algorithm is improved by 10%. For L2 band data, the results show that the accuracy of snow depth inversion of various algorithms do not change with the variations of snow depth. Among the three single algorithms, the inversion accuracy of FFT algorithm is better than that of LSP and NLSF algorithms.     

Total electron content monitoring using triple frequency GNSS: Results with Giove-A/-B data

Triple frequency GNSS will be fully operational within the next decade, opening opportunities for new applications. Dual frequency GNSS already allow to study the ionosphere through the estimation of Total Electron Content (TEC). However, the precision is limited by the ambiguity resolution process. This paper studies a triple frequency TEC monitoring technique in which the use of Geometry-Free and Iono-Free linear combinations improves the ambiguity resolution process and therefore the precision of TEC. We have tested it on a set of triple frequency Giove-A/-B data from January and December 2008. The conclusions achieved are (1) TEC values are affected by an error of about 2–2.5 TECU produced through the ambiguity resolution process; (2) the error caused by the Geometric Free phase combination delays (hardware, multipath, noise, antenna phase center) on TEC is about 0.2 TECU; (3) the total error on TEC approximately reach 2–3 TECU.     

不同GNSS在高纬度地区时间传递性能分析

全球卫星导航系统（GNSS）载波相位时间传递技术是高精度时间传递领域的主要研究方法之一，但目前关于该部分的研究主要集中在中低纬度地区，在高纬度地区并不多见。不同GNSS由于星座设计不同，在高纬度地区结构差异较大，因此需要对不同GNSS在高纬度地区的时间传递性能进行分析。实验结果表明，在高纬度地区时间传递中，Galileo稳定度最高，GPS和BDS次之，GLONASS最差。同时因在高纬度地区卫星的高度角普遍偏低，为合理平衡低高度角时可视卫星多和多路径误差大的矛盾，对不同截止高度角下获取的链路时间传递性能进行了分析。结果表明，在5°截止高度角下，高纬度地区的时间传递链路稳定性最好。