Evaluation of global navigation satellite system spoofing efficacy

The spoofing capability of Global Navigation Satellite System(GNSS)represents an important confrontational capability for navigation security,and the success of planned missions may depend on the effective evaluation of spoofing capability.However,current evaluation systems face challenges arising from the irrationality of previous weighting methods,inapplicability of the conventional multi-attribute decision-making method and uncertainty existing in evaluation.To solve these difficulties,considering the validity of the obtained results,an evaluation method based on the game aggregated weight model and a joint approach involving the grey relational analysis and technique for order preference by similarity to an ideal solution(GRA-TOPSIS)are firstly proposed to determine the optimal scheme.Static and dynamic evaluation results under different schemes are then obtained via a fuzzy comprehensive assessment and an improved dynamic game method,to prioritize the deceptive efficacy of the equipment accurately and make pointed improvement for its core performance.The use of judging indicators,including Spearman rank correlation coefficient and so on,combined with obtained evaluation results,demonstrates the superiority of the proposed method and the optimal scheme by the horizontal comparison of different methods and vertical comparison of evaluation results.Finally,the results of field measurements and simulation tests show that the proposed method can better overcome the difficulties of existing methods and realize the effective evaluation.

Collecting volunteered geographic information from the Global Navigation Satellite System(GNSS):experiences from the CAMALIOT project

Raw observations(carrier-phase and code observations)from the Global Navigation Satellite System(GNSS)can now be accessed from Android mobile phones(Version 7.0 onwards).This paves the way for GNSS data to be utilized for low-cost precise positioning or in ionospheric or tropospheric applications.This paper presents results from data collection campaigns using the CAMALIOT mobile app.In the frst campaign,116.3 billion measurements from 11,828 mobile devices were collected from all continents.Although participation decreased during the second campaign,data are still being collected globally.In this contribution,we demonstrate the potential of volunteered geographic information(VGl)from mobile phones to fill data gaps in geodetic station networks that collect GNSS data,e.g.in Brazil,but also how the data can provide a denser set of observations than current networks in countries across Europe.We also show that mobile phones capable of dual-frequency reception,which is an emerging technology that can provide a richer source of GNSS data,are contributing in a substantial way.Finally,we present the results from a survey of participants to indicate that participation is diverse in terms of backgrounds and geography,where the dominant motivation for participation is to contribute to scientific research.

LEO Enhanced Global Navigation Satellite System(LeGNSS):progress,opportunities,and challenges

With the completion of Chinese BeiDou Navigation Satellite System(BDS),the world has begun to enjoy the Positioning,Navigation,and Timing(PNT)services of four Global Navigation Satellite Systems(GNSS).In order to improve the GNSS performance and expand its applications,Low Earth Orbit(LEO)Enhanced Global Navigation Satellite System(LeGNSS)is being vigorously advocated.Combined with high-,medium-,and low-earth orbit satellites,it can improve GNSS performance in terms of orbit determination,Precise Point Positioning(PPP)convergence time,etc.This paper comprehensively reviews the current status of LeGNSS,focusing on analyzing its advantages and challenges for precise orbit and clock determination,PPP convergence,earth rotation parameter estimation,and global ionosphere modeling.Thanks to the fast geometric change brought by LEO satellites,LeGNSS is expected to fundamentally solve the problem of the long convergence time of PPP without any augmentation.The convergence time can be shortened within 1 minute if appropriate LEO constellations are deployed.However,there are still some issues to overcome,such as the optimization of LEO constellation as well as the real time LEO precise orbit and clock determination.

Scene image recognition with knowledge transfer for drone navigation

In this paper,we study scene image recognition with knowledge transfer for drone navigation.We divide navigation scenes into three macro-classes,namely outdoor special scenes(OSSs),the space from indoors to outdoors or from outdoors to indoors transitional scenes(TSs),and others.However,there are difficulties in how to recognize the TSs,to this end,we employ deep convolutional neural network(CNN)based on knowledge transfer,techniques for image augmentation,and fine tuning to solve the issue.Moreover,there is still a novelty detection prob-lem in the classifier,and we use global navigation satellite sys-tems(GNSS)to solve it in the prediction stage.Experiment results show our method,with a pre-trained model and fine tun-ing,can achieve 91.3196%top-1 accuracy on Scenes21 dataset,paving the way for drones to learn to understand the scenes around them autonomously.

Spatio Temporal Tourism Tracking System Based on Adaptive Convolutional Neural Network

Technological developments create a lot of impacts in the tourism industry.Emerging big data technologies and programs generate opportunities to enhance the strategy and results for transport security.However,there is a difference between technological advances and their integration into the methods of tourism study.The rising popularity of Freycinet National Park led to a master plan that would not address cultural and environmental issues.This study addresses the gap by using a synthesized application(app)for demographic surveys and Global Navigation Satellite System(GNSS)technology to implement research processes.This article focuses on managing visitors within the famous Freycinet National Park.Extremely comprehensive structured data were analyzed in three phases,(1)identifying groups of visitors who are more likely to use the walking trails,(2)those who are more and less likely to visit during/peak crowding times,and(3)finally creating an integrated Spatio-temporal dependency model via a machine-based learning system for real-time activity.This research examines innovative techniques that can offer energy resources to managers and tourism agencies,especially in detecting,measuring,and potentially relieving crowding and over-tourism.

Study on GNSS satellite signal simulator

Satellite signal simulator for global navigation satellite system(GNSS)can evaluate the accuracy of capturing,tracing and positioning of GNSS receiver.It has significant use-value in the military and civil fields.The system adopts the overall design scheme of digital signal processor(DSP)and field-programmable gate array(FPGA).It consists of four modules:industrial control computer simulation software,mid-frequency signal generator,digital-to-analog(D/A)module and radio frequency(RF)module.In this paper,we test the dynamic performance of simulator using the dynamic scenes testing method,and the signal generated by the designed simulator is primarily validated.

REVISITING THE DOPPLER FILTER OF LEO SATELLITE GNSS RECEIVERS FOR PRECISE VELOCITY ESTIMATION

The theoretical aspects of the precise velocity determination of Low Earth Orbit (LEO) satellites'on board Global Navigation Satellite Systems (GNSS) receivers are derived. It shows that the receiver's Phase Lock Loop (PLL) is required to feature extremely small group delay within its low frequency band, which is in contrast to existing work that proposed wide band linear phase filters. Following this theory, a Finite Impulse Response (FIR) filter is proposed. To corroborate, the proposed FIR filter and an Infinite Impulse Response (IIR) filter lately proposed in literals are implemented in a LEO satellite onboard GNSS receiver. Tests are conducted using a third party commercial GPS signal generator. The results show that the GNSS receiver with the proposed FIR achieves 11 mm/s R.M.S precision, while the GNSS receiver with the IIR filter has a filter-caused velocity error that can not be ignored for space borne GNSS receivers.

GPS观测得的2023年2月土耳其双震前后的地壳形变

2023年2月6日土耳其发生7.8级双震,相隔仅9小时、相距近,都是近直立断层走滑型地震,是利用GPS观测研究地震前后地壳形变稀有震例。利用美国网站得到131个GPS站欧亚(板块)参考框架位移数据,分析了2次地震前后的地壳形变。同震水平位移是分析大地震前兆地壳运动的关键现象。GPS分别观测得的2次地震同震位移,特征显著:水平位移最大达4.4 m;向西、向东和向南水平位移3个分区明显,与区域内3个板块构造运动密切相关;而垂直位移较小,无明显分区。2次地震前震中附近的水平位移分别出现(第一次地震)峰值和(第二次地震)闭锁2种类型,但无明显的垂直位移积累。与其他震例一样,在震前两种类型的水平位移区域,同震水平位移是震前位移在时间或空间上的(弹性)回跳,表明大地震有前兆形变。2次地震重合的孕震区内,有对2次地震同震水平位移影响相近的区域。GPS观测明确显示,地壳水平运动是2次大地震的成因。尽管观测不足和未能预报2次地震,但仍突显GNSS可在地震监测、预警和地震预测中发挥作用的优势。

Evaluation of surface temperature and pressure derived from MERRA-2 and ERA5 reanalysis datasets and their applications in hourly GNSS precipitable water vapor retrieval over China

Temperature and pressure play key roles in Global Navigation Satellite System(GNSS) precipitable water vapor(PWV) retrieval. The National Aeronautics and Space Administration(NASA) and European Center for Medium-Range Weather Forecasts(ECMWF) have released their latest reanalysis product: the modern-era retrospective analysis for research and applications, version 2(MERRA-2) and the fifthgeneration ECMWF reanalysis(ERA5), respectively. Based on the reanalysis data, we evaluate and analyze the accuracy of the surface temperature and pressure products in China using the the measured temperature and pressure data from 609 ground meteorological stations in 2017 as reference values.Then the accuracy of the two datasets and their performances in estimating GNSS PWV are analyzed. The PWV derived from the pressure and temperature products of ERA5 and MERRA-2 has high accuracy. The annual average biases of pressure and temperature for ERA5 are-0.07 hPa and 0.45 K, with the root mean square error(RMSE) of 0.95 hPa and 2.04 K, respectively. The annual average biases of pressure and temperature for MERRA-2 are-0.01 hPa and 0.38 K, with the RMSE of 1.08 h Pa and 2.66 K, respectively.The accuracy of ERA5 is slightly higher than that of MERRA-2. The two reanalysis data show negative biases in most regions of China, with the highest to lowest accuracy in the following order: the south,north, northwest, and Tibet Plateau. Comparing the GNSS PWV calculated using MERRA-2(GNSS MERRA-2 PWV) and ERA5(GNSS ERA5 PWV) with the radiosonde-derived PWV from 48 co-located GNSS stations and the measured PWV of the co-location radiosonde stations, it is found that the accuracy of GNSS ERA5 PWV is better than that of GNSS MERRA-2 PWV. These results show the different applicability of surface temperature and pressure products from MERRA-2 and ERA5 data, indicating that both have important applications in meteorological research and GNSS water vapor monitoring in China.

Improved Adaptive Iterated Extended Kalman Filter for GNSS/INS/UWB-Integrated Fixed-Point Positioning

To provide stable and accurate position information of control points in a complex coastal environment,an adaptive iterated extended Kalman filter(AIEKF)for fixed-point positioning integrating global navigation satellite system,inertial navigation system,and ultra wide band(UWB)is proposed.In thismethod,the switched global navigation satellite system(GNSS)and UWB measurement are used as the measurement of the proposed filter.For the data fusion filter,the expectation-maximization(EM)based IEKF is used as the forward filter,then,the Rauch-Tung-Striebel smoother for IEKF filter’s result smoothing.Tests illustrate that the proposed AIEKF is able to provide an accurate estimation.

A fine acquisition algorithm based on fast three-time FRFT for dynamic and weak GNSS signals

As high-dynamics and weak-signal are of two primary concerns of navigation using Global Navigation Satellite System(GNSS)signals,an acquisition algorithm based on threetime fractional Fourier transform(FRFT)is presented to simplify the calculation effectively.Firstly,the correlation results similar to linear frequency modulated(LFM)signals are derived on the basis of the high dynamic GNSS signal model.Then,the principle of obtaining the optimum rotation angle is analyzed,which is measured by FRFT projection lengths with two selected rotation angles.Finally,Doppler shift,Doppler rate,and code phase are accurately estimated in a real-time and low signal to noise ratio(SNR)wireless communication system.The theoretical analysis and simulation results show that the fast FRFT algorithm can accurately estimate the high dynamic parameters by converting the traditional two-dimensional search process to only three times FRFT.While the acquisition performance is basically the same,the computational complexity and running time are greatly reduced,which is more conductive to practical application.

Rapid development methodology of agricultural robot navigation system working in GNSS-denied environment

Robotic autonomous operating systems in global n40avigation satellite system(GNSS)-denied agricultural environments(green houses,feeding farms,and under canopy)have recently become a research hotspot.3D light detection and ranging(LiDAR)locates the robot depending on environment and has become a popular perception sensor to navigate agricultural robots.A rapid development methodology of a 3D LiDAR-based navigation system for agricultural robots is proposed in this study,which includes:(i)individual plant clustering and its location estimation method(improved Euclidean clustering algorithm);(ii)robot path planning and tracking control method(Lyapunov direct method);(iii)construction of a robot-LiDAR-plant unified virtual simulation environment(combination use of Gazebo and SolidWorks);and(vi)evaluating the accuracy of the navigation system(triple evaluation:virtual simulation test,physical simulation test,and field test).Applying the proposed methodology,a navigation system for a grape field operation robot has been developed.The virtual simulation test,physical simulation test with GNSS as ground truth,and field test with path tracer showed that the robot could travel along the planned path quickly and smoothly.The maximum and mean absolute errors of path tracking are 2.72 cm,1.02 cm;3.12 cm,1.31 cm,respectively,which meet the accuracy requirements of field operations,establishing the effectiveness of the proposed methodology.The proposed methodology has good scalability and can be implemented in a wide variety of field robot,which is promising to shorten the development cycle of agricultural robot navigation system working in GNSS-denied environment.

A spawning particle filter for defocused moving target detection in GNSS-based passive radar

Global Navigation Satellite System(GNSS)-based passive radar(GBPR)has been widely used in remote sensing applications.However,for moving target detection(MTD),the quadratic phase error(QPE)introduced by the non-cooperative target motion is usually difficult to be compensated,as the low power level of the GBPR echo signal renders the estimation of the Doppler rate less effective.Consequently,the moving target in GBPR image is usually defocused,which aggravates the difficulty of target detection even further.In this paper,a spawning particle filter(SPF)is proposed for defocused MTD.Firstly,the measurement model and the likelihood ratio function(LRF)of the defocused point-like target image are deduced.Then,a spawning particle set is generated for subsequent target detection,with reference to traditional particles in particle filter(PF)as their parent.After that,based on the PF estimator,the SPF algorithm and its sequential Monte Carlo(SMC)implementation are proposed with a novel amplitude estimation method to decrease the target state dimension.Finally,the effectiveness of the proposed SPF is demonstrated by numerical simulations and pre-liminary experimental results,showing that the target range and Doppler can be estimated accurately.

Status of UnDifferenced and Uncombined GNSS Data Processing Activities in China

With the continued development of multiple Global Navigation Satellite Systems(GNSS)and the emergence of various frequencies,UnDifferenced and UnCombined(UDUC)data processing has become an increasingly attractive option.In this contribution,we provide an overview of the current status of UDUC GNSS data processing activities in China.These activities encompass the formulation of Precise Point Positioning(PPP)models and PPP-Real-Time Kinematic(PPP-RTK)models for processing single-station and multi-station GNSS data,respectively.Regarding single-station data processing,we discuss the advancements in PPP models,particularly the extension from a single system to multiple systems,and from dual frequencies to single and multiple frequencies.Additionally,we introduce the modified PPP model,which accounts for the time variation of receiver code biases,a departure from the conventional PPP model that typically assumes these biases to be time-constant.In the realm of multi-station PPP-RTK data processing,we introduce the ionosphere-weighted PPP-RTK model,which enhances the model strength by considering the spatial correlation of ionospheric delays.We also review the phase-only PPP-RTK model,designed to mitigate the impact of unmodelled code-related errors.Furthermore,we explore GLONASS PPP-RTK,achieved through the application of the integer-estimable model.For large-scale network data processing,we introduce the all-in-view PPP-RTK model,which alleviates the strict common-view requirement at all receivers.Moreover,we present the decentralized PPP-RTK data processing strategy,designed to improve computational efficiency.Overall,this work highlights the various advancements in UDUC GNSS data processing,providing insights into the state-of-the-art techniques employed in China to achieve precise GNSS applications.

Progress of Geodesy Related Ionosphere from Chinese Scientists in the Period of 2019—2023

The ionosphere is the ionized part of the upper atmosphere of the Earth,which plays an important role in atmospheric electricity and forms the inner edge of the magnetosphere.It influences radio propagation significantly,such as the Global Navigation Satellite System(GNSS).Meanwhile,the GNSS is also an essential technique for sensing the variation of ionosphere.During the years of 2019—2023,a large number of Chinese geodesy scientists devoted much efforts to the geodesy related ionosphere.Due to the very limited length,the achievements are carried out from the following six aspects,including:①The ionospheric correction models for BDS and BDSBAS;②Real-time global ionospheric monitoring and modeling;③The ionospheric 2D and 3D modeling based on GNSS and LEO satellites;④The ionospheric prediction based on artificial intelligence;⑤The monitoring and mitigation of ionospheric disturbances for GNSS users;⑥The ionospheric related data products and classical applications.

Study on key technologies of GNSS-based train state perception for traincentric railway signaling

The application of Global Navigation Satellite Systems(GNSSs)in the intelligent railway systems is rapidly developing all over the world.With the GNSs-based train positioning and moving state perception,the autonomy and flexibility of a novel train control system can be greatly enhanced over the existing solutions relying on the track-side facilities.Considering the safety critical features of the railway signaling applications,the GNSS stand-alone mode may not be sufficient to satisfy the practical requirements.In this paper,the key technologies for applying GNSS in novel train-centric railway signaling systems are investigated,including the multi-sensor data fusion,Virtual Balise(VB)capturing and messaging,train integrity monitoring and system performance evaluation.According to the practical characteristics of the novel train control system under the moving block mode,the details of the key technologies are introduced.Field demonstration results of a novel train control system using the presented technologies under the practical railway operation conditions are presented to illustrate the achievable performance feature of autonomous train state perception using BeiDou Navigation Satellite System(BDS)and related solutions.It reveals the great potentials of these key technologies in the next generation train control system and other GNSS-based railway implementations.

张渤地震带现今形变特征研究

张家口-渤海地震构造带是华北地震构造区中具有相当规模的北西(NW)向活动构造带。通过对断层两侧基线-时间序列、区域速度场、应变场等进行分析,发现张渤带断层两侧速度场具有较大的差异,为典型的左旋走滑断层。区域应变场主应变自西向东依次为拉张-挤压-拉张-挤压,主应变由西向东逐步增大,在天津宝坻到河北唐山一带,主应变最大,为20 nanostr/yr(nanostr/yr是应变率的单位,表示单位距离每年的变化率),天津蓟县-宝坻一带为拉张变形,在唐山一带为挤压变形。根据Zoback判断震源机制应力类型的方法对张渤地震带及邻区研究时段内19个近震震级(ML)4.0以上地震的震源机制进行分类,震源错动方式以正断和走滑为主;区域应变显示的应力状态与震源机制解的错动类型基本吻合,天津宝坻-河北唐山的主应变变化比较剧烈,同时震源机制的类型也发生变化,表明该地区的深部与浅部的变形一致。

Consistency of MGEX Orbit and Clock Products

The analysis centers of the Multi-GNSS Pilot Project of the International GNSS Service provide orbit and clock products for the global navigation satellite systems(GNSSs)Global Positioning System(GPS),GLONASS,Galileo,and BeiDou,as well as for the Japanese regional Quasi-Zenith Satellite System(QZSS).Due to improved solar radiation pressure modeling and other more sophisticated models,the consistency of these products has improved in recent years.The current orbit consistency between different analysis centers is on the level of a few centimeters for GPS,around one decimeter for GLONASS and Galileo,a few decimeters for BeiDou-2,and several decimeters for QZSS.The clock consistency is about 2 cm for GPS,5 cm for GLONASS and Galileo,and 10 cm for BeiDou-2.In terms of carrier phase modeling error for precise point positioning,the various products exhibit consistencies of 2–3 cm for GPS,6–14 cm for GLONASS,3–10 cm for Galileo,and 10–17 cm for BeiDou-2.

Improved adaptively robust estimation algorithm for GNSS spoofer considering continuous observation error

Once the spoofer has controlled the navigation sys-tem of unmanned aerial vehicle(UAV),it is hard to effectively control the error convergence to meet the threshold condition only by adjusting parameters of estimation if estimation of the spoofer on UAV has continuous observation error.Aiming at this problem,the influence of the spoofer’s state estimation error on spoofing effect and error convergence conditions is theoretically analyzed,and an improved adaptively robust estimation algo-rithm suitable for steady-state linear quadratic estimator is pro-posed.It enables the spoofer’s estimator to reliably estimate UAV status in real time,improves the robustness of the estima-tor in responding to observation errors,and accelerates the con-vergence time of error control.Simulation experiments show that the mean value of normalized innovation squared(NIS)is reduced by 88.5%,and the convergence time of NIS value is reduced by 76.3%,the convergence time of true trajectory error of UAV is reduced by 42.3%,the convergence time of estimated trajectory error of UAV is reduced by 67.4%,the convergence time of estimated trajectory error of the spoofer is reduced by 33.7%,and the convergence time of broadcast trajectory error of the spoofer is reduced by 54.8%when the improved algorithm is used.The improved algorithm can make UAV deviate from pre-set trajectory to spoofing trajectory more effectively and more subtly.

Performance evaluation of neural network TEC forecasting models over equatorial low-latitude Indian GNSS station

Global Positioning System(GPS)services could be improved through prediction of ionospheric delays for satellite-based radio signals.With respect to latitude,longitude,local time,season,solar cycle and geomagnetic activity the Total Electron Content(TEC)have significant variations in both time and space.These temporal and spatial TEC variations driven by interplanetary space weather conditions such as solar and geomagnetic activities can degrade the communication and navigation links of GPS.Hence,in this paper,performance of TEC forecasting models based on Neural Networks(NN)have been evaluated to forecast(1-h ahead)ionospheric TEC over equatorial low latitude Bengaluru e12:97+N;77:59+ET,Global Navigation Satellite System(GNSS)station,India.The VTEC data is collected for 2009 e2016(8 years)during current 24 th solar cycle.The input space for the NN models comprise the solar Extreme UV flux,F10.7 proxy,a geomagnetic planetary A index(AP)index,sunspot number(SSN),disturbance storm time(DST)index,solar wind speed(Vsw),solar wind proton density(Np),Interplanetary Magnetic Field(IMF Bz).The performance of NN based TEC forecast models and International Reference Ionosphere,IRI-2016 global TEC model has evaluated during testing period,2016.The NN based model driven by all the inputs,which is a NN unified model(NNunq)has shown better accuracy with Mean Absolute Error(MAE)of 3.15 TECU,Mean Square Deviation(MSD)of 16.8 and Mean Absolute Percentage Error(MAPE)of 19.8%and is 1 e25%more accurate than the other NN based TEC forecast models(NN1,NN2 and NN3)and IRI-2016 model.NNunq model has less Root Mean Square Error(RMSE)value 3.8 TECU and highest goodness-of-fit(R2)with 0.85.The experimental results imply that NNunq/NN1 model forecasts ionospheric TEC accurately across equatorial low-latitude GNSS station and IRI-2016 model performance is necessarily improved as its forecast accuracy is limited to 69 e70%.