数字域谱估计的GNSS系统信号带宽测试方法

针对传统的单载波扫频法不适于GNSS（全球导航卫星系统）信号生成通道的带宽测量的问题,提出了采用数字信号处理的信号带宽方法.对实际导航信号进行高速采样,在数字域对采样的导航信号和本地数字生成的理想导航信号进行频谱估计和计算,从而得到GNSS信号带宽.分别使用周期图法和Welch法谱估计,对提出的测试方法进行仿真.仿真结果表明,采用Welch法进行理想信号和实际信号谱估计,对谱估计后的结果进行计算,可以完成GNSS信号带宽精密测量,在Welch法估计参数设置合理的情况下,GNSS信号带宽估计的准确度可以达到99.9％以上.     

雷达灵敏度测量中的视频信号积累方法

首先分析了视频信号积累在雷达中的作用和工作原理,然后详细阐述了数字化实现信号积累的方法,最后介绍了信号积累在雷达接收机灵敏度测量中的应用,较好的解决了接收机灵敏度测量中的不稳定问题.     

Stochastic modelling considering ionospheric scintillation effects on GNSS relative and point positioning

Global Navigation Satellite Systems (GNSS), in particular the Global Positioning System (GPS), have been widely used for high accuracy geodetic positioning. The Least Squares functional models related to the GNSS observables have been more extensively studied than the corresponding stochastic models, given that the development of the latter is significantly more complex. As a result, a simplified stochastic model is often used in GNSS positioning, which assumes that all the GNSS observables are statistically independent and of the same quality, i.e. a similar variance is assigned indiscriminately to all of the measurements. However, the definition of the stochastic model may be approached from a more detailed perspective, considering specific effects affecting each observable individually, as for example the effects of ionospheric scintillation. These effects relate to phase and amplitude fluctuations in the satellites signals that occur due to diffraction on electron density irregularities in the ionosphere and are particularly relevant at equatorial and high latitude regions, especially during periods of high solar activity. As a consequence, degraded measurement quality and poorer positioning accuracy may result.     

Near-real time monitoring of the TEC fluctuations over the northern hemisphere using GNSS permanent networks

Since the early 1990s, global positioning system measurements have been used to study of the state and rapid changes of the Total Electron Content in the ionosphere. Currently, the increasing number of permanent stations makes it possible to generate maps of the irregularities in the ionosphere for specified regions with sub-daily resolution. The main goal of this work was to apply global navigation satellite system observations to obtain information about ionospheric variability around the North Geomagnetic Pole. In order to detect the ionospheric disturbances, 30-s observation data was used. The Rate of Total Electron Content Index was applied as a measure of the variability in the ionosphere. The first analyses were executed using more than 100 permanent stations. The results show two kinds of products: 2-hour maps in spherical geomagnetic coordinates and daily maps presenting the occurrence of the strong Total Electron Content fluctuations as a magnetic local time function, for the most disturbed days of April 2010. Apart from the main product of the algorithm, the Rate of Total Electron Content time series for individual satellite tracks was presented. The results demonstrated very good sensitivity of the obtained maps, which can detect even quite weak disturbances. The presented algorithm developed at the Geodynamic Research Laboratory of the University of Warmia and Mazury, in cooperation with Institute of Terrestrial Magnetism, Ionosphere and Radiowave Propagation, will be applied in the near future to create near-real time service of the conditions in the ionosphere based on the Global Navigation Satellite Systems observations.     

直扩测控系统抗多址能力分析与验证

为了防止多址干扰造成接收机出现误捕和假锁,改善直接序列扩频测控系统抗多址干扰性能,在Gold码特性和扩频接收机性能分析的基础上,结合最大似然原理,对采用扩频体制测控系统的抗干扰能力进行了分析。为契合工程应用,采用仿真遍历结合理论分析的方式,对Gold码的互相关抑制能力理论值进行了工程修正。在分析捕获阶段的抗干扰捕获门限后,还分析了载噪比估计结果在正常锁定和假锁两种状态下的差异,给出了接收机对假锁状态的判决方法和门限。根据分析和仿真的结果,给出了系统设计约束条件和优化的接收机设计流程,作为测控系统和接收机设计的参考。     

北斗多模多频导航SoC芯片技术研究

介绍了一款北斗多模多频导航SoC芯片—“OTrack-128”,该芯片实现了多模多频兼容导航定位,采用完全国产化的卫星导航核心芯片,在定位精度、动态性能等关键指标上达到了国际先进水平,最后给出了基于该芯片的各类主要应用技术指标。     

外差式侦察接收机对频率捷变信号进行侦察的可行性

根据频率捷变信号的特点,分析了几种侦察体制下接收频率捷变信号需要的中频带宽、扫描步进频宽和截获时间,给出了对频率捷变信号侦察的可行性方案。     

GPS/INS超紧组合载波跟踪环路最优带宽在线设计

在全球定位系统和惯性导航系统组成的超紧耦合系统中,卫星信号的跟踪性能直接取决于载波跟踪环路的带宽。为提高最优带宽的计算精度,在对惯导辅助下载波跟踪环路跟踪特性进行分析的基础上,详细推导了载波多普勒频率估计误差、多普勒频率变化率估计误差的计算方式,建立了惯导辅助下的环路跟踪误差模型;在实时估计跟踪载噪比的基础上,应用离散牛顿二阶梯度法迭代解算最优带宽,并进行实时调整。仿真结果表明,所设计最优带宽迭代解算方法的计算精度能够在11次迭代内达到99.6%,以此作为环路的带宽,能够在弱信号、辅助信息精度较低的情况下有效提高环路的跟踪精度。     

Using TensorFlow-based Neural Network to estimate GNSS single frequency ionospheric delay (IONONet)

In the last 20?years, and in particular in the last decade, the availability of propagation data for GNSS has increased substantially. In this sense, the ionosphere has been sounded with a large number of receivers that provide an enormous amount of ionospheric data. Moreover, the maturity of the models has also been increased in the same period of time. As an example, IGS has ionospheric maps from GNSS data back to 1998, which would allow for the correlation of these data with other quantities relevant for the user and space weather (such as Solar Flux and Kp). These large datasets would account for almost half a billion points to be analyzed. With the advent and explosion of Big Data algorithms to analyze large databases and find correlations with different kinds of data, and the availability of open source code libraries (for example, the TensorFlow libraries from Google that are used in this paper), the possibility of merging these two worlds has been widely opened. In this paper, a proof of concept for a single frequency correction algorithm based in GNSS GIM vTEC and Fully Connected Neural Networks is provided. Different Neural Network architectures have been tested, including shallow (one hidden layer) and deep (up to five hidden layers) Neural Network models. The error in training data of such models ranges from 50% to 1% depending on the architecture used. Moreover, it is shown that by adjusting a Neural Network with data from 2005 to 2009 but tested with data from 2016 to 2017, Neural Network models could be suitable for the forecast of vTEC for single frequency users. The results indicate that this kind of model can be used in combination with the Galileo Signal-in-Space (SiS) NeQuick G parameters. This combination provides a broadcast model with equivalent performances to NeQuick G and better than GPS ICA for the years 2016 and 2017, showing a 3D position Root Mean Squared (RMS) error of approximately 2?m.     

Establishment of atmospheric weighted mean temperature model in the polar regions

Due to the special geographical location and extreme climate environment, the polar regions (Antarctic and Arctic) have an important impact on global climate change. Atmospheric weighted mean temperature (Tm) is a crucial parameter in the retrieval of precipitable water vapor (PWV) from the zenith wet delay (ZWD) of ground-based Global Navigation Satellite System (GNSS) signal propagation. In this paper, the correlation between weighted mean temperature and surface temperature (Ts) is studied firstly. It is shown that the correlation coefficients between Tm and Ts are 0.93 in the Antarctic and 0.94 in the Arctic. The linear regression Tm model and quadratic function Tm model of the Antarctic and the Arctic are established respectively using the radiosonde profiles of 12 stations in the Antarctic and 58 stations in the Arctic from 2008 to 2015. The accuracies of the linear regression Tm model, the quadratic function Tm model and GPT2w Tm model which is a state-of-the-art global Tm model are verified using the radiosonde profiles from 2016 to 2018 in the Antarctic and Arctic. Root Mean Square (RMS) errors of the linear regression Tm model, the quadratic function Tm model and GPT2w Tm model in the Antarctic are 3.07 K, 2.87 K and 4.32 K respectively, and those in the Arctic are 3.53 K, 3.38 K and 4.82 K, which indicates that the quadratic function Tm model has a higher accuracy compared to linear regression Tm model, and the accuracies of the two regional Tm models are better than that of GPT2w Tm model in the polar regions. In order to better evaluate the accuracy of Tm in the PWV retrieval, the PWV values of radiosondes are used for comparisons as the reference value. The RMS errors of PWV derived from the two Tm models are similar for 1.28 mm in the Antarctic and 1 mm in the Arctic respectively. In addition, the spatial and temporal variation characteristics of Tm are analyzed in the polar regions by spectral analysis of Tm data using fast Fourier transform. The results show that the Tm has obvious seasonality and annual periodicity in the polar regions, and the maximum difference between warm season and cold season is about 63 K. After comparing and analyzing the influences of latitude, longitude and elevation on the Tm in the polar regions, it is found that latitude and elevation have a greater influence on the Tm than the longitude. As the latitude and elevation increase, the Tm decreases, and vice versa in the polar regions.