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.

Structure and performance analysis of fusion positioning system with a single 5G station and a single GNSS satellite

NaGlobal vigation Satellite System(GNSS)positioning technology is widely used for its high precision,global,and all-weather service.However,in complex environments such as urban canyons,GNSS performance is often degraded due to signal occlusion and even fails to achieve positioning due to the insufficient visible satellites.Because of the characteristics of large band-width,low latency,and high Base Station(BS)density,the fifth-Generation mobile communication(5G)technology has gradually become a trend for positioning in cities while offering traditional communication service.To supply the communication demands of the User Equipment(UE),only one BS is usually considered to establish a connection with the UE during the BS construction.However,the positioning accuracy with a single BS in urban canyons will be significantly reduced.To further improve the positioning accuracy in such extreme scenarios,this paper proposes a simplified 5G/GNSS fusion positioning system architecture using observations from only a 5G BS and a GNSS satellite.In this system,the GNSS receiver is mounted on the 5G BS,and the measurements provided by the receiver are used to form the differential code and complete the position estimation.The positioning mathematical models of the system based on the original code and differential code are derived.Then,the impacts of the measurements noise and the time synchronization error on the positioning accuracy are analyzed theoretically.Finally,the positioning performance is investigated by a set of simulation experiments.Numerical results show that under the existing 5G measurement noise and 2 m’s code measurement noise,the improvement of the differential code based fusion positioning compared with the 5G-only positioning is more than 32%,which is also about 6%higher than the original code based fusion positioning.Besides,this improvement is not affected by the time synchronization error between the BS and the GNSS satellite.

Reference satellite selection method for GNSS high-precision relative positioning

Selecting the optimal reference satellite is an important component of high-precision relat/ve positioning because the reference satellite directly influences the strength of the normal equation. The reference satellite selection methods based on elevation and positional dilution of precision （PDOP） value were compared. Results show that all the above methods cannot select the optimal reference satellite. We introduce condition number of the design matrix in the reference satellite selection method to improve structure of the normal equation, because condition number can indicate the ill condition of the normal equation. The experimental results show that the new method can improve positioning accuracy and reliability in precise relative positioning.

Performance of GNSS positioning in PPP mode using MADOCA precise products

The Global Navigation Satellite System (GNSS) is widely utilized for accurate positioning.One commonly applied method to obtain precise coordinate estimates is by implementing the relative positioning in network mode.However,this approach can be complex and challenging.Fortunately,The Japan Aerospace Exploration Agency (JAXA) offers freely available satellite orbit and clock correction products called Multi-GNSS Advanced Demonstration Tool for Orbit and Clock Analysis (MADOCA),which can enhance positioning accuracy through the precise point positioning (PPP) method.This study focuses on evaluating PPP static mode positioning using MADOCA products and comparing the results with the highly precise relative positioning method.By analyzing a network of 20 GNSS stations in Indonesia,we found that the PPP method using MADOCA products provided favorable positioning estimates.The median discrepancies and the corresponding median absolute deviation (MAD) for easting,northing,and up components were estimated as 9±18 mm,10±9 mm,and 3±40 mm,respectively.These results indicate that PPP with MADOCA products can be a reliable alternative for establishing Indonesia's horizontal control networks,particularly for orders 0,1,2,and 3,and for a broad spectrum of geoscience monitoring activities.However,considerations such as epoch transformations and seismic activities should be taken into account for accurate positioning applications that comply with the definition of the national reference framework.

GNSS spoofing detection for single antenna receivers via CNR variation monitoring

In this paper,a method for spoofing detection based on the variation of the signal’s carrier-to-noise ratio(CNR)is proposed.This method leverages the directionality of the antenna to induce varying gain changes in the signals across different incident directions,resulting in distinct CNR variations for each signal.A model is developed to calculate the variation value of the signal CNR based on the antenna gain pattern.This model enables the differentiation of the variation values of the CNR for authentic satellite signals and spoofing signals,thereby facilitating spoofing detection.The proposed method is capable of detecting spoofing signals with power and CNR similar to those of authentic satellite signals.The accuracy of the signal CNR variation value calculation model and the effectiveness of the spoofing detection method are verified through a series of experiments.In addition,the proposed spoofing detection method works not only for a single spoofing source but also for distributed spoofing sources.

GNSS spoofing detection based on uncultivated wolf pack algorithm

In order to solve the problem that the global navigation satellite system（GNSS） receivers can hardly detect the GNSS spoofing when they are deceived by a spoofer,a model-based approach for the identification of the GNSS spoofing is proposed.First,a Hammerstein model is applied to model the spoofer/GNSS transmitter and the wireless channel.Then,a novel method based on the uncultivated wolf pack algorithm（UWPA） is proposed to estimate the model parameters.Taking the estimated model parameters as a feature vector,the identification of the spoofing is realized by comparing the Euclidean distance between the feature vectors.Simulations verify the effectiveness and the robustness of the proposed method.The results show that,compared with the other identification algorithms,such as least square（LS）,the iterative method and the bat-inspired algorithm（BA）,although the UWPA has a little more time-eomplexity than the LS and the BA algorithm,it has better estimation precision of the model parameters and higher identification rate of the GNSS spoofing,even for relative low signal-to-noise ratios.

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.

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.

Meteorological applications of precipitable water vapor measurements retrieved by the national GNSS network of China

In this study, the Global Navigation Satellite System （GNSS） network of China is discussed, which can be used to monitor atmospheric precipitable water vapor （PWV）. By the end of 2013, the network had 952 GNSS sites, including 260 belonging to the Crustal Movement Observation Network of China （CMONOC） and 692 belonging to the China Meteorological Administration GNSS network （CMAGN）. Additionally, GNSS observation collecting and data processing procedures are presented and PWV data quality control methods are investigated. PWV levels as determined by GNSS and radiosonde are compared. The results show that GNSS estimates are generally in good agreement with measurements of radio- sondes and water vapor radiometers （WVR）. The PWV retrieved by the national GNSS network is used in weather forecasting, assimilation of data into numerical weather prediction models, the validation of PWV estimates by radiosonde, and plum rain monitoring. The network is also used to monitor the total ionospheric electron content.

Adaptive beamforming and phase bias compensation for GNSS receiver

Adaptive antenna arrays have been used to mitigate the interference on global navigation satellite system（GNSS） receivers. The performance of interference mitigation depends on the beamforming algorithms adopted by the antenna array. However,the adaptive beamforming will change the array pattern in realtime, which has the potential to introduce phase center biases into the antenna array. For precise applications, these phase biases must be mitigated or compensated because they will bring errors in code phase and carrier phase measurements. A novel adaptive beamforming algorithm is proposed firstly, then the phase bias induced by the proposed algorithm is estimated, and finally a compensation strategy is addressed. Simulations demonstrate that the proposed beamforming algorithm suppresses effectively the strong interference and improves significantly the capturing performance of GNSS signals. Simultaneously, the bias compensation method avoids the loss of the carrier phase lock and reduces the phase measurement errors for GNSS receivers.

Multi-channel signal parameters joint optimization for GNSS terminals

Traditional global navigation satellite system(GNSS)terminals for satellite navigation adopt independent channels to track the signals from different satellites, which results in a lack of information interaction between the channels. Inspired by the vector tracking idea, and drawing lessons from the principle that in the position domain the Taylor expanded pseudorange observations can be used for positioning via the least squares method, this paper proposes a novel least squares-based multi-channel parameter joint estimation(MPJE) method in the signal domain, which not only retains the advantages of channel fusion, but also maintains the flexibility and diversity of the localization algorithm. With achieving optimal carrier to noise ratio as the goal, the proposed method obtains the required code loop and carrier loop parameters for signal tracking in the domain of whole channels. Experimental results indicate that this method fully achieves the assistant fusion advantages of frequency lock loop(FLL), phase lock loop(PLL)and delay lock loop(DLL), making good use of the robustness and dynamic properties of the FLL and the measurement accuracy of the DLL, and is helpful for achieving stable and accurate signal tracking under weak signals and high dynamic stress environments.

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%.

Combined filter method for weakening GNSS multipath error

A filter method that combines ensemble empirical modal decomposition(EEMD)and wavelet analysis methods was proposed to separate and correct the global navigation satellite system(GNSS)multipath error more effectively.In this method,the GNSS signal is first decomposed into several intrinsic mode functions(IMFs)and a residual through EEMD.Then,the IMFs and residual are classified into noise terms,mixed terms,and useful terms according to a combined classification criterion.Finally,the mixed term denoised by wavelet and the useful term are reconstructed to obtain the multipath error and thus enable an error correction model to be built.The measurement data provided by the Curtin GNSS Research Center were used for processing and analysis.Results show that the proposed method can separate multipath error from GNSS data to a great extent,thereby effectively addressing the defects of EEMD and wavelet methods on multipath error weakening.The error correction model established with the separated multipath error has a higher accuracy and provides a certain reference value for research on related signal processing.

Calibration of GNSS positioning receivers

Nowadays global navigation satellite system(GNSS)receivers are the primary tool not only for precision surveying but also for geodesy,geophysics and many other industrial applications worldwide.The only way to assure the accuracy,universality and longevity of GNSS measurements is by calibration of its receivers.The parameters affecting the calibration accuracy of a single GNSS receiver are discussed in this paper.And a geodetic basepoint is established according to previous empirical studies to serve as a reference for calibration.Additionally,the traceability to the systeme international(SI)unit of such kind of calibrations is discussed.Stability of the base point is also verified through long-term measurements over three years.Eventually,a calibration of a sample single GNSS receiver is performed and the uncertainty budget is derived.

Re-scaling and adaptive stochastic resonance as a tool for weak GNSS signal acquisition

Weak global navigation satellite system（GNSS） signal acquisition has been a limitation for high sensitivity GPS receivers. This paper modifies the traditional acquisition algorithms and proposes a new weak GNSS signal acquisition method using re-scaling and adaptive stochastic resonance（SR）. The adoption of classical SR is limited to low-frequency and periodic signals. Given that GNSS signal frequency is high and that the periodic feature of the GNSS signal is affected by the Doppler frequency shift, classical SR methods cannot be directly used to acquire GNSS signals. Therefore, the re-scaling technique is used in our study to expand its usage to high-frequency signals and adaptive control technique is used to gradually determine the Doppler shift effect in GNSS signal buried in strong noises. The effectiveness of our proposed method was verified by the simulations on GPS L1 signals. The simulation results indicate that the new algorithm based on SR can reach-181 d BW sensitivity with a very short data length of 1 ms.

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.

Mathematical model for computing precise local tie vectors for CMONOC co-located GNSS/VLBI/SLR stations

The seven co-located sites of the Crustal Movement Observation Network of China（CMONOC） in Shanghai, Wuhan, Kunming, Beijing, Xi＇an, Changchun, and Urumqi are equipped with Global Navigation Satellite System（GNSS）, very long baseline interferometry（VLBI）, and satellite laser ranging（SLR） equipment. Co-location surveying of these sites was performed in 2012 and the accuracies of the solved tie vectors are approximately 5 mm.This paper proposes a mathematical model that handles the least squares adjustment of the 3D control network and calculates the tie vectors in one step, using all the available constraints in the adjustment. Using the new mathematical model, local tie vectors can be more precisely determined and their covariance more reasonably estimated.

Airborne GNSS-Receiver Threat Detection in No-Fading Environments

Jamming and spoofing detection of global navigation satellite systems(GNSS)is of great importance.Civil and military aerial platforms use GNSS as main navigation systems and these systems are main target of threat attacks.In this paper a simple method based on different empirical probability density functions of successive received signal powers and goodness of fit tech-nique is proposed for airborne platforms such as unmanned aerial vehicle(UAV),in no fading envi-ronment.The two different paths between UAV-satellite and UAV-threat,experience different empirical probability density functions which can be used to distinguish between authentic and threat signals.Simulation results including detection and false alarm probabilities show good perfor-mance of proposed method as well as low computational burden.

The Performance Evaluation of the Integration of Inertial Navigation System and Global Navigation Satellite System with Analytic Constraints

The integration of GNSS （Global Navigation Satellite System） and INS （Inertial Navigation System） using IMU （Inertial Measurement Unit） is now widely used for MMS （Mobile Mapping System） and navigation applications to seamlessly determine position, velocity and attitude of the mobile platform. With low cost, small size, ligh weight and low power consumtion, the MEMS （Micro-Electro-Mechanical System） IMU and low cost GPS （Global Positioning System） receivers are now the trend in research and using for many applications. However, researchs in the literature indicated that the the performance of the low cost INS/GPS systems is still poor, particularly, in case of GNSS-noise environment. To overcome this problem, this research applies analytic contrains including non-holonomic constraint and zero velocity update in the data fusion engine such as Extended Kalman Filter to improve the performance of the system. The benefit of the proposed method will be demonstrated through experiments and data analysis.