基于DSP和FPGA的GPS伪随机码并行快速捕获方案设计

讨论了高动态下GPS伪随机码并行搜索的基本原理,以及自适应门限确定方法与搜索过程中应注意的问题。提出了一种基于高速DSP和FPGA的全数字解扩接收机方案,阐述了工作流程,并给出了系统的结构框图,经测试验证实现了伪随机码并行快速捕获的功能。     

转发式干扰下GPS定位精度的仿真分析

根据GPS转发式干扰的原理,建立了转发式干扰对GPS定位精度影响的数学模型.讨论了两种转发式干扰模式对定位的影响.最后通过计算机仿真分析得出了GPS转发式干扰对GPS定位精度影响的相关结论.     

基于GPS载波相位的微卫星姿态算法研究

GPS姿态系统是利用GPS载波相位测量来确定载体的航向和姿态角。本文对微卫星的GPS姿态系统进行了研究。重点解决短基线的GPS状态算法，讨论了姿态价格函数的了小化方法。测试结果表明，所提的算法对小于1m的基线是有效的。     

一种新型综合性靶场安全系统及其检验测试结果

本文首先简要介绍战略导弹发射场和航天发射场靶场安全系统的作用、特点、主要技术要求,接着介绍按美国空军航天司令部要求,由空军研究所开发的基于GPS弹道测量技术,外测、遥测、遥控综合为一体的机动型靶场安全系统——BMRST的构成及其经多种检验测试的结果。     

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。     

Evaluation of the IRI-2016 and NeQuick electron content specification by COSMIC GPS radio occultation,ground-based GPS and Jason-2 joint altimeter/GPS observations

We examined performance of two empirical profile-based ionospheric models, namely IRI-2016 and NeQuick-2, in electron content (EC) and total electron content (TEC) representation for different seasons and levels of solar activity. We derived and analyzed EC estimates in several representative altitudinal intervals for the ionosphere and the plasmasphere from the COSMIC GPS radio occultation, ground-based GPS and Jason-2 joint altimeter/GPS observations. It allows us to estimate a quantitative impact of the ionospheric electron density profiles formulation in several altitudinal intervals and to examine the source of the model-data discrepancies of the EC specification from the bottom-side ionosphere towards the GPS orbit altitudes. The most pronounced model-data differences were found at the low latitude region as related to the equatorial ionization anomaly appearance. Both the IRI-2016 and NeQuick-2 models tend to overestimate the daytime ionospheric EC and TEC at low latitudes during all seasons of low solar activity. On the contrary, during high solar activity the model results underestimated the EC/TEC observations at low latitudes. We found that both models underestimated the EC for the topside ionosphere and plasmasphere regions for all levels of solar activity. For low solar activity, the underestimated EC from the topside ionosphere and plasmasphere can compensate the overestimation of the ionospheric EC and, consequently, can slightly decrease the resulted model overestimation of the ground-based TEC. For high solar activity, the underestimated EC from the topside ionosphere and plasmasphere leads to a strengthening of the model underestimation of the ground-based TEC values. We demonstrated that the major source of the model-data discrepancies in the EC/TEC domain comes from the topside ionosphere/plasmasphere system.     

Thermosphere densities derived from Swarm GPS observations

After the detection of many anomalies in the Swarm accelerometer data, an alternative method has been developed to determine thermospheric densities for the three-satellite mission. Using a precise orbit determination approach, non-gravitational and aerodynamic-only accelerations are estimated from the high-quality Swarm GPS data. The GPS-derived non-gravitational accelerations serve as a baseline for the correction of the Swarm-C along-track accelerometer data. The aerodynamic accelerations are converted directly into thermospheric densities for all Swarm satellites, albeit at a much lower temporal resolution than the accelerometers would have been able to deliver. The resulting density and acceleration data sets are part of the European Space Agency Level 2 Swarm products.To improve the Swarm densities, two modifications have recently been added to our original processing scheme. They consist of a more refined handling of radiation pressure accelerations and the use of a high-fidelity satellite geometry and improved aerodynamic model. These modifications lead to a better agreement between estimated Swarm densities and NRLMSISE-00 model densities. The GPS-derived Swarm densities show variations due to solar and geomagnetic activity, as well as seasonal, latitudinal and diurnal variations. For low solar activity, however, the aerodynamic signal experienced by the Swarm satellites is very small, and therefore it is more difficult to accurately resolve latitudinal density variability using GPS data, especially for the higher-flying Swarm-B satellite. Therefore, mean orbit densities are also included in the Swarm density product.     

A method of estimating GPS instrumental biases with a convolution algorithm

This paper presents a method of deriving the instrumental differential code biases (DCBs) of GPS satellites and dual frequency receivers. Considering that the total electron content (TEC) varies smoothly over a small area, one ionospheric pierce point (IPP) and four more nearby IPPs were selected to build an equation with a convolution algorithm. In addition, unknown DCB parameters were arranged into a set of equations with GPS observations in a day unit by assuming that DCBs do not vary within a day. Then, the DCBs of satellites and receivers were determined by solving the equation set with the least-squares fitting technique. The performance of this method is examined by applying it to 361?days in 2014 using the observation data from 1311 GPS Earth Observation Network (GEONET) receivers. The result was crosswise-compared with the DCB estimated by the mesh method and the IONEX products from the Center for Orbit Determination in Europe (CODE). The DCB values derived by this method agree with those of the mesh method and the CODE products, with biases of 0.091?ns and 0.321?ns, respectively. The convolution method's accuracy and stability were quite good and showed improvements over the mesh method.     

Real-time clock comparison and monitoring with multi-GNSS precise point positioning: GPS,GLONASS and Galileo

The precise point positioning (PPP) technique is widely used in time and frequency applications. Because of the real-time service (RTS) project of the International GNSS Service, we can use the PPP technique for real-time clock comparison and monitoring. As a participant in the RTS, the Centre National d’Etudes Spatiales (CNES) implements the PPPWIZARD (Precise Point Positioning with Integer and Zero-difference Ambiguity Resolution Demonstrator) project to validate carrier phase ambiguity resolution. Unlike the Integer-PPP (IPPP) of the CNES, fixing ambiguities in the post-processing mode, the PPPWIZARD operates in the real-time mode, which is also called real-time IPPP (RT-IPPP). This paper focuses on applying the RT-IPPP for real-time clock comparison and monitoring. We review the principle of real-time clock comparison and monitoring, and introduce the methodology of the RT-IPPP technique. The observations of GPS, GLONASS and Galileo were processed for the experiments. Five processing modes were provided in the experiment to analyze the benefits of ambiguity resolution and multi-GNSS. In the clock comparison experiment, the average reduction ratios of standard deviations with respect to the G PPP mode range from 9.7% to 35.0%. In the clock monitoring experiment, G PPP mode can detect clock jumps whose magnitudes are larger than 0.9 ns. The RT-IPPP technique with GRE PPP AR (G) mode allows for the detection of any clock jumps larger than 0.6 ns. For frequency monitoring, G PPP mode allows detection of frequency changes larger than 1.1 × 10⁻¹⁴. When the RT-IPPP technique is applied, monitoring with GRE PPP AR (G) mode can detect frequency changes larger than 6.1 × 10⁻¹⁵.     

Comparison of GPS derived TEC with the TEC predicted by IRI 2012 model in the southern Equatorial Ionization Anomaly crest within the Eastern Africa region

We have compared the TEC obtained from the IRI-2012 model with the GPS derived TEC data recorded within southern crest of the EIA in the Eastern Africa region using the monthly means of the 5 international quiet days for equinoxes and solstices months for the period of 2012 – 2013. GPS-derived TEC data have been obtained from the Africa array and IGS network of ground based dual-frequency GPS receivers from four stations (Kigali (1.95°S, 30.09°E; Geom. Lat. 11.63°S), Malindi (2.99°S, 40.19°E; Geom. Lat. 12.42°S), Mbarara (0.60°S, 30.74°E; Geom. Lat. 10.22°S) and Nairobi (1.22°S, 36.89°E; Geom. Lat. 10.69°S)) located within the EIA crest in this region. All the three options for topside Ne of IRI-2012 model and ABT-2009 for bottomside thickness have been used to compute the IRI TEC. Also URSI coefficients were considered in this study. These results are compared with the TEC estimated from GPS measurements. Correlation Coefficients between the two sets of data, the Root-Mean Square Errors (RMSE) of the IRI-TEC from the GPS-TEC, and the percentage RMSE of the IRI-TEC from the GPS-TEC have been computed. Our general results show that IRI-2012 model with all three options overestimates the GPS-TEC for all seasons and at all stations, and IRI-2001 overestimates GPS-TEC more compared with other options. IRI-Neq and IRI-01-corr are closely matching in most of the time. The observation also shows that, GPS TEC are underestimated by TEC from IRI model during noon hours, especially during equinoctial months. Further, GPS-TEC values and IRI-TEC values using all the three topside Ne options show very good correlation (above 0.8). On the other hand, the TEC using IRI-Neq and IRI-01- corr had smaller deviations from the GPS-TEC compared to the IRI-2001.