The verification of GNSS tropospheric tomography model in a mountainous area

The GNSS (Global Navigation Satellite System) has not been developed as a meteorological data source provider, but with a careful and sophisticated processing strategy it might be used as one. The term GNSS tomography refers to the usage of the ray traced GNSS signal as scanning rays in the tomographic model input. The model is divided into a number of voxels. The system is inverted and value of refractivity is obtained. Typically, as in the most of the inverse processing, there is a problem of the undetermined system and as a consequence the cofactor matrix is close to singular. To avoid singularity additional conditions or constrains should be added to the system. Here, additional parameters are derived with the help of the air flow analysis in the Sudety mountains (south-west region of Poland), and special Slant Wet Delay (SWD) trimming procedure. The flow’s synthetic parameters like the Bruint-Väisälä frequency and the Froude number are determined. This way the type of the flow is recognized and the analysis of the impact of orographic barrier has been quantified. The SWDs from the GNSS observations were tested against, SWD from raytracing through the COAMPS model field. The modified GNSS tomography model was tested for the real GNSS observations delivered from the GNSS network Karkonosze located in the Sudety mountains and compared with the COAMPS model. The solution shows a considerable improvement in comparison with plain tomographic model results.     

Near real-time PPP-based monitoring of the ionosphere using dual-frequency GPS/BDS/Galileo data

Ionosphere delay is very important to GNSS observations, since it is one of the main error sources which have to be mitigated even eliminated in order to determine reliable and precise positions. The ionosphere is a dispersive medium to radio signal, so the value of the group delay or phase advance of GNSS radio signal depends on the signal frequency. Ground-based GNSS stations have been used for ionosphere monitoring and modeling for a long time. In this paper we will introduce a novel approach suitable for single-receiver operation based on the precise point positioning (PPP) technique. One of the main characteristic is that only carrier-phase observations are used to avoid particular effects of pseudorange observations. The technique consists of introducing ionosphere ambiguity parameters obtained from PPP filter into the geometry-free combination of observations to estimate ionospheric delays. Observational data from stations that are capable of tracking the GPS/BDS/GALILEO from the International GNSS Service (IGS) Multi-GNSS Experiments (MGEX) network are processed. For the purpose of performance validation, ionospheric delays series derived from the novel approach are compared with the global ionospheric map (GIM) from Ionospheric Associate Analysis Centers (IAACs). The results are encouraging and offer potential solutions to the near real-time ionosphere monitoring.     

2006年12月13日太阳射电暴对GPS观测的影响

日地空间环境不仅影响航天器运行和安全, 也是导航、定位和通信等无线 电应用系统主要的误差源. 其中来自太阳L波段的射电暴被认为是全球导航卫星 系统(GNSS)稳定和性能的潜在威胁因素, 当L波段射电爆发达到一定阈值时, 将给用户带来不同程度的射电噪声干扰, 严重时会引起接收机失锁和定位服务 中断. 本文对2006年12月13日太阳射电暴对GPS造成的影响进行了研究, 利用太阳射电 观测数据、L波段闪烁观测数据和向阳面不同区域的GPS观测网数据, 分析 GPS观测对射电暴的响应. 结果表明, 此次事件对GPS观测产生了明显的影响, 射 电暴期间GPS发生幅度闪烁事件和明显失锁现象, 多个台站上空的多颗GPS 卫星 信号完全中断长达6min左右, 且多个台站上空锁定的卫星数目小于4颗, 使 得GPS定位完全失效. 相对而言, 射电暴期间日下点附近的GPS台站受到的影响 比远离日下点的大.      

Electron density retrieval from occulting GNSS signals using a gradient-aided inversion technique

In the coming years, opportunities for remote sensing of electron density in the Earth’s ionosphere will expand with the advent of Galileo, which will become part of the global navigation satellite system (GNSS). Methods for accurate electron density retrieval from radio occultation data continue to improve. We describe a new method of electron density retrieval using total electron content measurements obtained in low Earth orbit. This method can be applied to data from dual-frequency receivers tracking the GPS or Galileo transmitters. This simulation study demonstrates that the method significantly improves retrieval accuracy compared to the standard Abel inversion approach that assumes a spherically symmetric ionosphere. Our method incorporates horizontal gradient information available from global maps of Total Electron Content (TEC), which are available from the International GNSS Service (IGS) on a routine basis. The combination of ground and space measurements allows us to improve the accuracy of electron density profiles near the occultation tangent point in the E and F regions of the ionosphere.     

System Design for the Event Horizon Imaging Experiment Using the PECMEO Concept

The concept for space interferometry from Polar or Equatorial Circular Medium Earth Orbits (the PECMEO concept) is a promising way to acquire the image of the “shadow” of the event horizon of Sagittarius A* with an angular resolution of circa 5 microarcseconds. The concept is intended to decrease the size of the main reflector of the instrument to about 3 m using a precise orbit reconstruction based on Global Navigation Satellite System (GNSS) navigation, inter-satellite range and range-rate measurements, and data from the Attitude and Orbit Determination System (AODS). The paper provides the current progress on the definition of the subsystems required for the concept on the basis of simulations, radio regulations, and available technology. The paper proposes the requirement for the localization of the phase centre of the main reflector. The paper provides information about the visibility of GNSS satellites and the needed accuracies of the AODS. The paper proposes the frequency plan for the instrument and its Inter-Satellite Links (ISLs). The concepts for measurement of range and range rate using ISLs (as well as for the data exchange at these ISLs) are presented. The block diagram of the interferometer is described and its sensitivity is estimated. The link budget for both ISLs is given as well as their critical components. The calculated measurement quality factors are given. The paper shows the expected performance of the sub-systems of the interferometer. The requirements for the localization of the main reflectors and the information about the availability of the GNSS satellites are based on the simulations results. The frequency plan is obtained according to the PECMEO concept and taking into account the radio regulations. The existing technology defines the accuracies of the AODS as well as the link budgets and the measurement accuracies for both ISLs and the sensitivity of the instrument. The paper provides input information for the development of the orbit reconstruction filter and the whole PECMEO system.      

粒子群优化粒子滤波的接收机自主完好性监测

接收机自主完好性监测（RAIM）是航空卫星导航接收机必不可少的功能,为保持全球卫星导航系统（GNSS）在卫星发生故障时系统性能不降级,需要对卫星故障进行检测和隔离。针对接收机观测噪声非高斯分布的特点,提出一种基于粒子群优化粒子滤波（PSO-PF）的故障检测和隔离算法。通过粒子群优化粒子滤波对状态估计进行一致性检验实现故障检测。采集实测数据验证算法的检测性能,并与基于基本粒子滤波的完好性监测算法进行比较,结果表明:本文所提算法在非高斯测量噪声下可检测并隔离全球定位系统（GPS）故障卫星,其性能优于基于基本粒子滤波的完好性监测算法性能,对研究北斗卫星导航系统（BDS）接收机自主完好性监测具有一定的意义。      

一种基于GNSS数据的全球电离层不规则结构活动表征方法

针对如何利用GNSS(Global Navigation Satellite System)数据进行电离层扰动监测的问题,提出了一种基于GNSS数据表征全球电离层扰动的方法.利用大约400个GNSS地面站点的观测数据,计算总电子含量(Total Electron Content,TEC)变化率的标准差——ROTI(Ra...     

The multi-source data fusion global ionospheric modeling software—IonoGim

We introduce a new global ionospheric modeling software—IonoGim, using ground-based GNSS data, the altimetry satellite and LEO (Low Earth Orbit) occultation data to establish the global ionospheric model. The software is programmed by C++ with fast computing speed and highly automatic degree, it is especially suitable for automatic ionosphere modeling. The global ionospheric model and DCBs obtained from IonoGim were compared with the CODE (Center for Orbit Determination in Europe) to verify its accuracy and reliability. The results show that IonoGim and CODE have good agreement with small difference, indicating that IonoGim owns high accuracy and reliability, and can be fully applicable for high-precision ionospheric research. In addition, through comparison between only using ground-based GNSS observations and multi-source data model, it can be demonstrated that the space-based ionospheric data effectively improve the model precision in marine areas where the ground-based GNSS tracking station lacks.     

Characterization of ionospheric amplitude scintillations using wavelet entropy detrended GNSS data

The extensive monitoring networks of Global Navigation Satellite System (GNSS) ionospheric scintillation have been established to continuously log observation data. Further, the amplitude scintillation index and the phase scintillation index, which are derived from scintillation observations, are anticipated to accommodate the accuracy requirement of both the user level and the monitoring station level. However, raw scintillation observations essentially measure superposed waveform impairments of GNSS signals propagating through ionosphere and troposphere. It implies that fluctuations of raw scintillation observations are caused by multiple factors from the entire radio propagation environment. Hence, it is crucial to characterize ionospheric scintillations from GNSS observation data. And the characterization is implemented through extracting fluctuations of raw observations merely induced by ionospheric scintillations. Designed to address this problem by means of Fourier filtering detrending, the present work investigates the influence of varying detrending cutoff frequencies on wavelet statistical energy and wavelet entropy distributions of scintillation data. It consequently derives criteria on the optimum detrending cutoff frequency for three types of raw amplitude scintillation data, which are classified by their wavelet energy distributions. Results of the present work verify that detrending with specific optimum cutoff frequencies rather than the fixed and universally applicable one renders the validity and credibility of characterizing ionospheric scintillations as the part of GNSS observation fluctuations purely induced by ionosphere electron density irregularities whose scale sizes are comparable with or smaller than the Fresnel scale.     

Development of a GNSS water vapour tomography system using algebraic reconstruction techniques

A GNSS water vapour tomography system developed to reconstruct spatially resolved humidity fields in the troposphere is described. The tomography system was designed to process the slant path delays of about 270 German GNSS stations in near real-time with a temporal resolution of 30 min, a horizontal resolution of 40 km and a vertical resolution of 500 m or better. After a short introduction to the GPS slant delay processing the framework of the GNSS tomography is described in detail. Different implementations of the iterative algebraic reconstruction techniques (ART) used to invert the linear inverse problem are discussed. It was found that the multiplicative techniques (MART) provide the best results with least processing time, i.e., a tomographic reconstruction of about 26,000 slant delays on a 8280 cell grid can be obtained in less than 10 min. Different iterative reconstruction techniques are compared with respect to their convergence behaviour and some numerical parameters. The inversion can be considerably stabilized by using additional non-GNSS observations and implementing various constraints. Different strategies for initialising the tomography and utilizing extra information are discussed. At last an example of a reconstructed field of the wet refractivity is presented and compared to the corresponding distribution of the integrated water vapour, an analysis of a numerical weather model (COSMO-DE) and some radiosonde profiles.     

基于射频的导航卫星星间链路信息传输与仿真研究

星间链路是导航卫星实现精密定轨和自主导航的关键技术之一。导航卫星通过星间链路完成伪距测量和数据交换,维持系统稳定运行的时空基准,保证系统持续提供精准导航服务。根据全球导航卫星系统的建设情况和发展趋势,首先介绍星间观测和信息传输频段,并从天线特征、多址控制方式和网络拓扑结构等角度分析了射频链路的工作体制。最后,针对实际导航卫星星座,应用OPNET平台建立导航信息传输仿真模型,通过分析信息传输效率,验证了基于射频链路导航信息传输的可行性和有效性,对全球导航卫星系统的星间链路研究具有一定的参考价值。     

Characterisation of residual ionospheric errors in bending angles using GNSS RO end-to-end simulations

Global Navigation Satellite System (GNSS) radio occultation (RO) is an innovative meteorological remote sensing technique for measuring atmospheric parameters such as refractivity, temperature, water vapour and pressure for the improvement of numerical weather prediction (NWP) and global climate monitoring (GCM). GNSS RO has many unique characteristics including global coverage, long-term stability of observations, as well as high accuracy and high vertical resolution of the derived atmospheric profiles. One of the main error sources in GNSS RO observations that significantly affect the accuracy of the derived atmospheric parameters in the stratosphere is the ionospheric error. In order to mitigate the effect of this error, the linear ionospheric correction approach for dual-frequency GNSS RO observations is commonly used. However, the residual ionospheric errors (RIEs) can be still significant, especially when large ionospheric disturbances occur and prevail such as during the periods of active space weather. In this study, the RIEs were investigated under different local time, propagation direction and solar activity conditions and their effects on RO bending angles are characterised using end-to-end simulations. A three-step simulation study was designed to investigate the characteristics of the RIEs through comparing the bending angles with and without the effects of the RIEs. This research forms an important step forward in improving the accuracy of the atmospheric profiles derived from the GNSS RO technique.     

Iridium/ORBCOMM机会信号融合定位技术

在全球导航卫星系统(GNSS)不可用情况下，低地球轨道(LEO)卫星机会信号(SOP)定位技术是一种有效的导航定位解决方案。单LEO星座机会信号定位技术面临星座构型不足或可见卫星偏少等问题，多LEO星座机会信号融合定位技术可有效解决该问题。通过分析瞬时多普勒定位原理，建立了Iridium/ORBCOMM机会信号融合定位模型，引入基于Helmert方差估计的加权最小二乘算法进一步提高定位精度。实测数据表明:基于Helmert方差估计的Iridium/ORBCOMM机会信号融合定位精度优于70 m，验证了多LEO星座机会信号融合定位的可行性和有效性。      

Exploration and analysis of the factors influencing GNSS PWV for nowcasting applications

Precipitable water vapor (PWV) can be assimilated into a numerical weather model (NWM) to improve the prediction accuracy of numerical weather prediction. In this study, taking GNSS data for the Beijing Fangshan station (BJFS) as an example, based on the method of Pearson correlation coefficient combined with quantitative analysis, GNSS datasets are used to study the relationships between GNSS-derived PWV (GNSS PWV__Met) and its influencing factors, including the internal influencing factors zenith troposphere delay (ZTD), zenith hydrostatic delay (ZHD), zenith wet delay (ZWD), and surface temperature (T_s), and the external influencing factor haze (mainly PM_2.5). Firstly, based on the strong correlation between PWV__Met and ZTD hourly sequences from the International GNSS Service Network’s BJFS station for DOYS 182–212, 2015, the results of experiment prove that the reliability of GNSS ZTD is used to forecast PWV_Met in short-term forecasting. Secondly, based on hourly data of BJFS in 2016, the correlation between PWV__Met and ZTD, ZWD, ZHD, pressure (P) and T_s is analyzed, and then, with the rate of ZTD variation as the main factor, ZTD variation as auxiliary factor, the prediction success rate is 88.24% from hourly data of precipitation event for DOYs 183–213 in Beijing. The experiment indicates that ZTD can help forecast short-term precipitation. Thirdly, based on data from three hazy periods with relatively stable weather conditions, no heavy rainfall, and relatively continuous data in the past three years, the correlation between GNSS PWV_Met/ZTD and PM_2.5 hourly series is analyzed. The results of the experiments suggests that GNSS ZTD should be considered to assist in haze monitoring. So in the absence of radiosonde stations and meteorological elements, ZTDs on retrieval of GNSS stations have more application value in short-term forecast.     

Multi- GNSS reflectometry performance evaluation for coastal sea level monitoring: A case study in Antarctic Peninsula

Antarctica is a continent that crucial for studying climate change and its progression across time, as well as analyzing and forecasting local and global change. In this environment, due to the challenges caused by sea-level rise, storm surges, and tsunamis, sustainability is a critical concern, particularly for coastal regions. As a result, the long-term observations that will be conducted in Antarctica are critical for monitoring the adverse impacts of climate change. In recent years, many monitoring approaches, both space, and ground-based are performed to monitor sea/ice level trends in space-based scientific investigations conducted in and around the region. In the study, based on one year of observations from the Palmer GNSS Station, the GNSS Reflectometry technique was used to measure the sea level on the Antarctic Peninsula (PALM). GNSS Station observations were analyzed with a Lomb-Scargle periodogram to monitor sea-level changes, and results were validated with data from a co-located tide gauge (TG). The results show that the correlation between GNSS-R sea-level changes and tidal sea-level changes is found as 0.91.     

基于射频的导航卫星星间链路信息传输与仿真研究

星间链路是导航卫星实现精密定轨和自主导航的关键技术之一。导航卫星通过星间链路完成伪距测量和数据交换,维持系统稳定运行的时空基准,保证系统持续提供精准导航服务。根据全球导航卫星系统的建设情况和发展趋势,首先介绍星间观测和信息传输频段,并从天线特征、多址控制方式和网络拓扑结构等角度分析了射频链路的工作体制。最后,针对实际导航卫星星座,应用OPNET平台建立导航信息传输仿真模型,通过分析信息传输效率,验证了基于射频链路导航信息传输的可行性和有效性,对全球导航卫星系统的星间链路研究具有一定的参考价值。     

GNSS water vapour tomography – Expected improvements by combining GPS,GLONASS and Galileo observations

The German Research Centre for Geosciences (GFZ) operates a GNSS water vapour tomography system using about 350 German GNSS stations. The GNSS data processing at the GFZ works in near real-time and provides zenith total delays, integrated water vapour and slant delay data operationally. This large data set of more than 50,000 slant delays per hour is used to reconstruct spatially resolved humidity fields by means of tomographic techniques. It can be expected that additional observations from the future Galileo system provide more information with improved quality. A simulation study covering 12 h at 14 July 2009 was therefore started to estimate the impact of GPS, Galileo and GLONASS data on the GNSS tomography. It is shown that the spatial coverage of the atmosphere with slant paths is highly improved by combining observations from two or three satellite systems. Equally important for a reliable tomographic reconstruction is the distribution of slant path intersections as they are required to locate the integrated delay information. The number of intersection points can be increased by a factor of 4 or 8 if two or three systems are combined and their distribution will cover larger regions of the atmosphere. The combined data sets can be used to increase the spatiotemporal resolution of the reconstructed humidity fields up to 30 km horizontally, 300 m vertically and 15 min. The reconstruction quality could not be improved considerably using the currently available techniques.     

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.     

An improved cyclic multi model-eXtreme gradient boosting (CMM-XGBoost) forecasting algorithm on the GNSS vertical time series

The study of GNSS vertical coordinate time series forecasting is helpful for monitoring the crustal plate movement, dam or bridge deformation monitoring, and global or regional coordinate system maintenance. The eXtreme Gradient Boosting (XGBoost) algorithm is a machine learning algorithm that can evaluate features, and it has a great potential and stability for long-span time series forecasting. This study proposes a multi-model combined forecasting method based on the XGBoost algorithm. The method constitutes a new time series as features through the fitting and forecasting results of the forecasting model. The XGBoost model is then used for forecasting. In addition, this method can obtain higher precision forecasting results through circulation. To verify the performance of the forecasting method, 1095 epochs of data in the Up coordinate of 16 GNSS stations are selected for the forecasting test. Compared with the CNN-LSTM model, the experimental results of our forecasting method show that the mean absolute error (MAE) values are reduced by 30.23 %～52.50 % and the root mean square error (RMSE) values are reduced by 31.92 %～54.33 %. The forecasting results have higher accuracy and are highly correlated to the original time series, which can better forecast the vertical movement of the GNSS stations. Therefore, the forecasting method can be applied to the up component of the GNSS coordinate time series.     

GNSS信号模拟器通道群时延标定方法

传统的全球导航卫星系统(GNSS)信号模拟器通道群时延标定方法有相位翻转点法和相关峰法两种,两者均在零伪距或固定伪距的特殊仿真场景下进行测量,且在通道传输特性非理想的情况下测得的群时延均存在偏差.提出了基于闭环伪距测量的模拟器通道群时延标定方法,并设计实现了GNSS信号模拟器通道群时延标定系统.首先,采用高速直接射频采样存储系统对模拟器正常星座动态仿真场景下输出的导航信号和秒脉冲(1 PPS)信号同时进行记录.其次,使用软件接收机对信号进行捕获跟踪,利用三次样条插值判定1 PPS上升沿位置作为伪距观测历元时刻,对软件接收机的伪距观测量和模拟器仿真的伪距记录值做数据比对,得到模拟器的群时延标定值.最后,分别利用上述方法对两种商用模拟器的群时延进行了标定,实验结果表明,闭环伪距测量法有效可行,测量不确定度优于0.7 ns.