Global Positioning System Pseudorange Research Articles

Performance of Multi-GNSS in the Asia-Pacific Region: Signal Quality, Broadcast Ephemeris and Precise Point Positioning (PPP)

Since BeiDou Navigation Satellite System (BDS) and Japan’s Quasi-Zenith Satellite System (QZSS) have more visible satellites in the Asia-Pacific region, and navigation satellites of Global Positioning System (GPS), Galileo satellite navigation system (Galileo), and GLONASS satellite navigation system (GLONASS) are uniformly distributed globally, the service level of multi-mode Global Navigation Satellite System (GNSS) in the Asia-Pacific region should represent the best service capability. Based on the observation data of 10 Multi-GNSS Experiment (MGEX) stations, broadcast ephemeris and precision ephemeris from 13 to 19 October 2021, this paper comprehensively evaluated the service capability of multi-GNSS in the Asia-Pacific region from three aspects of observation data quality, broadcast ephemeris performance, and precision positioning level. The results show that: (1) the carrier-to-noise-density ratio (C/N0) quality of the GPS and Galileo is the best, followed by BDS and GLONASS, and QZSS is the worst. GPS, BDS-2, GLONASS, and QZSS pseudorange multipath values range from 0 to 0.6 m, while Galileo system and BDS-3 pseudorange multipath values range from 0 to 0.8 m. (2) In terms of broadcast ephemeris accuracy, BDS-3 broadcast ephemeris has the best orbit, and the three-dimensional (3D) Root Mean Square (RMS) is 0.21 m; BDS-2 was the worst, with a 3D RMS of 1.99 m. The broadcast ephemeris orbits of GPS, Galileo, QZSS, and GLONASS have 3D RMS of 0.60 m, 0.62 m, 0.83 m, and 1.27 m, respectively. For broadcast ephemeris clock offset: Galileo has the best performance, 0.61 ns, GLONASS is the worst, standard deviation (STD) is 3.10 ns, GPS, QZSS, BDS-3 and BDS-2 are 0.65 ns, 0.75 ns, and 1.72 ns, respectively. For signal-in-space ranging errors (SISRE), the SISRE results of GPS and Galileo systems are the best, fluctuating in the range of 0 m–2 m, followed by QZSS, BDS-3, Galileo, and BDS-2. (3) GPS, BDS, GLONASS, Galileo, GPS/QZSS, and BDS/QZSS were used for positioning experiments. In static PPP, the convergence time and positioning accuracy of GPS show the best performance. The positioning accuracy of GPS/QZSS and BDS/QZSS is improved compared with that of GPS and BDS. In terms of kinematic PPP, the convergence time and positioning accuracy of GPS/QZSS and BDS/QZSS are improved compared with that of GPS and BDS. In addition to GLONASS and Galileo systems, the other combinations outperformed 3 cm, 3 cm, and 5 cm in the east, north, and up directions.

Study of the GPS inter-frequency calibration of timing receivers

When calibrating Global Positioning System (GPS) stations dedicated to timing, the hardware delays of P1 and P2, the P(Y)-codes on frequencies L1 and L2, are determined separately. In the international atomic time (TAI) network the GPS stations of the time laboratories are calibrated relatively against reference stations. This paper aims at determining the consistency between the P1 and P2 hardware delays (called dP1 and dP2) of these reference stations, and to look at the stability of the inter-signal hardware delays dP1–dP2 of all the stations in the network. The method consists of determining the dP1–dP2 directly from the GPS pseudorange measurements corrected for the frequency-dependent antenna phase center and the frequency-dependent ionosphere corrections, and then to compare these computed dP1–dP2 to the calibrated values.Our results show that the differences between the computed and calibrated dP1–dP2 are well inside the expected combined uncertainty of the two quantities. Furthermore, the consistency between the calibrated time transfer solution obtained from either single-frequency P1 or dual-frequency P3 for reference laboratories is shown to be about 1.0 ns, well inside the 2.1 ns uB uncertainty of a time transfer link based on GPS P3 or Precise Point Positioning. This demonstrates the good consistency between the P1 and P2 hardware delays of the reference stations used for calibration in the TAI network.The long-term stability of the inter-signal hardware delays is also analysed from the computed dP1–dP2. It is shown that only variations larger than 2 ns can be detected for a particular station, while variations of 200 ps can be detected when differentiating the results between two stations. Finally, we also show that in the differential calibration process as used in the TAI network, using the same antenna phase center or using different positions for L1 and L2 signals gives maximum differences of 200 ps on the hardware delays of the separate codes P1 and P2; however, the final impact on the P3 combination is less than 10 ps.

A Novel Approach for Improved Vehicular Positioning Using Cooperative Map Matching and Dynamic Base Station DGPS Concept

In this paper, a novel approach for improving vehicular positioning is presented. This method is based on the cooperation of the vehicles by communicating their measured information about their position. This method consists of two steps. In the first step, we introduce our cooperative map matching method. This map matching method uses the V2V communication in a vehicular ad hoc network (VANET) to exchange global positioning system (GPS) information between vehicles. Having a precise road map, vehicles can apply the road constraints of other vehicles in their own map matching process and acquire a significant improvement in their positioning. After that, we have proposed the concept of a dynamic base station DGPS (DDGPS), which is used by vehicles in the second step to generate and broadcast the GPS pseudorange corrections that can be used by newly arrived vehicles to improve their positioning. The DDGPS is a decentralized cooperative method that aims to improve the GPS positioning by estimating and compensating the common error in GPS pseudorange measurements. It can be seen as an extension of DGPS where the base stations are not necessarily static with an exact known position. In the DDGPS method, the pseudorange corrections are estimated based on the receiver's belief on its positioning and its uncertainty and then broadcasted to other GPS receivers. The performance of the proposed algorithm has been verified with simulations in several realistic scenarios.

Neural Technologies for Precise Timing in Electric Power Systems with a Single-Frequency GPS Receiver

The global positioning system (GPS), with its ability to provide time synchronization with accuracy to 200 ns over the wide area, provides an ideal tool for performing time tagging in electric power systems. The observed GPS pseudo-range varies from the true range because of range measurement errors. GPS errors sources are ionospheric delays, atmospheric delays, troposphericelays, multi-path effects and dilution of precision etc., affecting the GPS signals as they travel from satellite to user on Earth. In this paper neural models has been presented are for more accurate GPS timing in electric power systems with a single-frequency GPS receiver. The proposed methods use back-propagation (BP), extended Kalman filter (EKF) and particle swarm optimization (PSO) training algorithms, which achieves the optimal training criterion. We use actual data to evaluate the performance of the proposed methods. An experimental test setup is designed and implemented for this purpose. Results using the three methods are discussed. The experimental results obtained from a coarse acquisition (C/A)-code single-frequency GPS receiver are provided to confirm the efficacy of the approaches to give high accurate timing. The GPS timing RMS error using neural network based on PSO learning algorithm reduces to less than 105 and 36 ns, before and after SA, respectively.

Accuracy Analysis of Positioning Method for Fusion GPS Pseudo-Range and Continuous Wave Radar

Continuous wave (CW) radar and global positioning system (GPS) is the main equipment of trajectory measurement in range. Based on range test background, propose a method to fuse GPS pseudo-range and CW radar range to provide complete trajectory positioning parameters, effectively reduce the impact of the systematic error of the measuring element to improve positioning precision of aircraft orbit solving. Through research on the measurement principle and the practice calculated data is given in this paper. Finally, several famous practical examples and simulation results are presented to illustrate our method efficiently.

A new seismogeodetic approach applied to GPS and accelerometer observations of the 2012 Brawley seismic swarm: Implications for earthquake early warning

The 26 August 2012 Brawley seismic swarm of hundreds of events ranging from M1.4 to M5.5 in the Salton Trough, California provides a unique data set to investigate a new seismogeodetic approach that combines Global Positioning System (GPS) and accelerometer observations to estimate displacement and velocity waveforms. First in simulated real‐time mode, we analyzed 1–5 Hz GPS data collected by 17 stations fully encircling the swarm zone at near‐source distances up to about 40 km using precise point positioning with ambiguity resolution (PPP‐AR). We used a reference network of North American GPS stations well outside the region of deformation to estimate fractional‐cycle biases and satellite clock parameters, which were then combined with ultrarapid orbits from the International GNSS Service to estimate positions during the Brawley seismic swarm. Next, we estimated seismogeodetic displacements and velocities from GPS phase and pseudorange observations and 100–200 Hz accelerations collected at three pairs of GPS and seismic stations in close proximity using a new tightly coupled Kalman filter approach as an extension of the PPP‐AR process. We can clearly discern body waves in the velocity waveforms, including P‐wave arrivals not detectable with the GPS‐only approach for earthquake magnitudes as low as Mw 4.6 and significant static offsets for magnitudes as low as Mw 5.4. Our study shows that GPS networks upgraded with strong motion accelerometers can provide new information for improved understanding of the earthquake rupture process and be of critical value in creating a robust early warning system for any earthquake of societal significance.

Proposal for a new localisation method using tightly coupled integration based on a precise estimation of trajectory from GPS Doppler

Driver assistance systems require the function of precise localisation. However, the accuracy of standard global positioning system (GPS) is inadequate for this. In this paper, a new method for precise localisation using the tightly coupled integration of inertial navigation system (INS) and raw GPS data is investigated. GPS Doppler corresponds to the relative velocity between the satellite and the receiver. Our new method enables us to make a robust and accurate estimation of the vehicle trajectory based on INS and GPS Doppler. Furthermore, the total optimisation by combining GPS pseudorange data with the accurate trajectory enables us to estimate the position of the vehicle precisely.

The Autocovariance Least-Squares Technique for GPS Measurement Noise Estimation

In this paper, the autocovariance least-squares (ALS) technique is proposed to estimate the Global Positioning System (GPS) pseudorange measurement noise-covariance matrix. The large GPS measurement noise magnitude can be attributed to signal interference, jamming , or other factors, such as signal multipath. The proposed method makes use of the dynamics of the system measured by an inertial measurement unit (IMU) and the propagated residual of a GPS/IMU estimation filter to form a bank of statistics used to estimate the GPS measurement noise covariance. The method is used along an ultratightly coupled GPS/IMU filter to first estimate the measurement noise covariance matrix and then use this covariance matrix to obtain a high-accuracy and high-integrity state estimate. Simulated scenarios of different levels of noise magnitude are applied, and the proposed method is used to estimate the GPS pseudorange noise-covariance matrix.

Efeitos de segunda e terceira ordem da ionosfera no posicionamento GNSS no Brasil

O Sistema de Posicionamento Global (GPS) transmite seus sinais em duas freqüências, o que permite eliminar matematicamente os efeitos de primeira ordem da ionosfera através da combinação linear ionosphere free. Porém, restam os efeitos de segunda e terceira ordem, os quais podem provocar erros da ordem de centímetros nas medidas GPS. Esses efeitos, geralmente, são negligenciados no processamento dos dados GPS. Os efeitos ionosféricos de primeira, segunda e terceira ordem são diretamente proporcionais ao TEC presente na ionosfera, porém, no caso dos efeitos de segunda e terceira ordem, comparecem também o campo magnético da Terra e a máxima densidade de elétrons, respectivamente. Nesse artigo, os efeitos de segunda e terceira ordem da ionosfera são investigados, sendo que foram levados em consideração no processamento de dados GPS na região brasileira para fins de posicionamento. Serão apresentados os modelos matemáticos associados a esses efeitos, as transformações envolvendo o campo magnético da Terra e a utilização do TEC advindo dos Mapas Globais da Ionosfera ou calculados a partir das observações GPS de pseudodistância. O processamento dos dados GPS foi realizado considerando o método relativo estático e cinemático e o posicionamento por ponto preciso (PPP). Os efeitos de segunda e terceira ordem foram analisados considerando períodos de alta e baixa atividade ionosférica. Os resultados mostraram que a não consideração desses efeitos no posicionamento por ponto preciso e no posicionamento relativo para linhas de base longas pode introduzir variações da ordem de poucos milímetros nas coordenadas das estações, além de variações diurnas em altitude da ordem de centímetros.

Space Weather and the Global Positioning System

Space Weather and the Global Positioning System

The Autocovariance Least Squares Technique for GPS Interference/Jamming Detection

In this paper, the Autocovariance Least Squares (ALS) technique is proposed for detecting the Global Positioning System (GPS) measurements’ interference or jamming. The interference is modeled by a moderate increase in the measurements noise covariance matrix while jamming is modeled by a larger increase in the measurements noise covariance matrix. The method makes use of the dynamics of the system measured by an inertial measurement unit (IMU) and the propagated residual of an ultra-tightly coupled GPS/IMU Extended Kalman filter (EKF) to form a bank of statistics used to estimate the GPS measurement-noise covariance. Simulated scenarios of different levels of noise magnitude are applied and the proposed method is used to estimate the GPS pseudorange noise covariance matrix. Results are presented at the end of the paper to show the accuracy of the proposed algorithm. The algorithm presented in this paper is vital for high-integrity operation of autonomous navigation systems.

Multi-Sensor Personal Navigator: System Design and Calibration

This paper presents the current design status and some preliminary calibration/performance analyses of the prototype of a multi-sensor personal navigator currently under development at The Ohio State University. The main purpose of this research project is to develop a theoretical foundation and algorithms which integrate the Global Positioning System (GPS), Micro-electro-mechanical inertial measurement unit (MEMS IMU), barometer and compass to provide seamless position information to support navigation and tracking of ground military and rescue personnel. The system is designed with an open-ended architecture, which would be able to incorporate additional navigation and imaging sensor data, extending the system's operations to the indoor environments. The current target accuracy of the system is at 3–5 m CEP (circular error probable). In the current prototype implementation, the following sensors are integrated in the tightly coupled Extended Kalman Filter (EKF): GPS carrier phase and pseudorange data, Crossbow MEMS IMU400C, PTB220A barometer, and KVH Azimuth 1000 digital compass. This paper focuses on the design architecture of the integrated system and the preliminary performance analysis, with a special emphasis on the navigation during the loss of GPS signal. A brief description of the individual sensors and their calibration is presented, together with the navigation performance of the system of sensors.

Availability, accuracy, reliability, and carrier-phase ambiguity resolution with Galileo and GPS

The positioning performance of the Galileo Global Navigation Satellite System (GNSS) operating in conjunction with the Global Positioning System (GPS) is assessed through simulation. Results of two simulations are presented. First, the positioning accuracy and statistical reliability of the systems is assessed using global constellation geometry simulations. Using GPS and Galileo together is shown to improve availability and accuracy. Statistical reliability, meaning the ability of the system to identify and control measurement blunders, is greatly increased due to the much larger number of redundant observations provided by using the two GNSS systems together. Results of a second simulation are presented demonstrating the advantages of using the two systems together for precise carrier phase differential positioning. Modernized GPS and Galileo pseudorange and carrier phase observations are simulated. A new carrier phase positioning algorithm is shown that uses three frequency carrier phase ambiguity resolution in conjunction with stochastic ionospheric modeling. The use of multiple carriers implies more redundancy as well as better observability for ionospheric estimation. This results in a more consistent estimation process and allows for very rapid and reliable ambiguity resolution over much longer baselines than are possible with the current GPS signals. Results of this simulation are presented in the ambiguity resolution domain and the position domain.

Application of Multipath Template Technique to Real-Time Ionospheric Delay Estimation Using Global Positioning System Measurements

When global positioning system (GPS) signals propagate through the ionosphere, they experience an extra time delay. The ionospheric delay can be estimated using L1/L2 GPS measurement. In order to mitigate the pseudorange multipath effect on real-time ionospheric delay estimation, the multiday multipath template technique has been developed. The algorithm permits the pseudorange multipath error for a specific day to be corrected using the generated multipath template. Data from National Chengchi University, in Taiwan was used to test the application of the multipath template to real-time ionospheric delay estimation. Test results indicate that: (1) The performance of the various 5 day multipath templates is better than that of other multiday multipath templates and (2) the multipath template technique is an effective method to mitigate the GPS pseudorange multipath and should be implemented at reference stations within local-area differential GPS, wide-area differential GPS, and wide-area augmentation system networks, GPS deformation monitoring networks, etc.

Ground-multipath mitigation via polarization steering of GPS signal

Multipath (MP) is the dominant error source in Global Positioning System (GPS) code-based position solutions requiring high accuracy. A technique is introduced here to mitigate error due to ground-reflected MP signals. The technique uses two orthogonal dipoles to capture the direct GPS signal and the ground-reflected GPS signal. Adjusting the amplitude and phase of the received voltage between the two dipoles can reduce the impact of MP error. Theoretical derivations of this technique are performed for a GPS signal upon reflection from dry soil, seawater, and fresh water. The theoretical results are verified with a real world experiment on the aforementioned surfaces. GPS pseudo-range (PR) and carrier-to-noise ratio (C/No) measurements for specific satellites are used to verify the predicted theoretical results.

Neural Networks in GPS Navigation

Neural networks have been proposed as nonlinear filters in a variety of applications that involve nonlinear processing of input signals; examples include blind signal separation, image registration, and blind deconvolution. The Global Positioning System (GPS) navigation equations are nonlinear (quadratic) in nature, and a direct closed form solution of the GPS navigation equations does not exist. This article presents a new approach to solving the GPS pseudorange equations using three-layer neural networks. A three-layer radial basis function (RBF) neural network is designed, which solves the non-linear GPS pseudorange equations directly as opposed to the linear least squares or extended Kalman filter approaches in traditional GPS receivers. For training the neural network, a carefully selected cost function is minimized using a variation of the classical conjugate gradient algorithm such that training time for the neural network is reasonable. Simulations have been performed at SiRF Technology Inc. that show stable behavior even under bad geometry conditions where the traditional recursive least squares and extended Kalman filter approaches show high sensitivity to measurement errors. Under good geometry conditions the neural network solution shows slightly improved noise performance compared to the expected performance of traditional leas squares solution. Simulations have been performed with additive white Gaussian noise and correlated noise models to evaluate the performance of the trained neural network. © 2000 John Wiley & Sons, Inc.

A New GPS Data Processing Algorithm for the Positioning of Oceanographic Experiments

Abstract In this paper, the authors present a Global Positioning System (GPS) algorithm for medium accuracy (1-m rms) positioning of ocean buoys. The application addressed in this paper is that of the Fast Pegasus experiments that require the positioning of surface buoys used in collecting subsurface acoustic data for ocean current profiling. The current GPS system designed for the Fast Pegasus experiments requires a land-based single-frequency GPS receiver for differential GPS positioning. In contrast, the technique presented here is designed for the point positioning of a stand-alone single-frequency GPS receiver (which is in motion) and does not require the use of a land-based reference receiver. The precise point positioning algorithm developed here uses postprocessed GPS satellite ephemerides and clock corrections to compute the position of a single GPS receiver. A square root information filter/smoother uses the GPS pseudorange and carrier phase measurements to estimate the position and clock offset...

Accuracy assessment of GPS satellite orbits

Global Positioning System (GPS) orbit determination using data collected by the civilian tracking network CIGNET have been used in a variety of experiments, along with data collected from special campaigns to augment the global tracking data. These experiments have been used to investigate the fidelity of the satellite force and kinematic models with the goal of improving the GPS ephemeris accuracy. Software has been developed for the preprocessing of GPS pseudo-range and phase measurements, including procedures for cycle slip correction. A multi-satellite orbit determination program, MSODP, allows for satellite-dependent force models, including high-low satellite constellations. Assessments of orbit accuracies derived from measurements collected in campaigns with nearly global networks have been performed with a variety of techniques, including determination of baselines known from SLR or VLBI, the computation of long, multi-week arcs and the comparison of predicted ephemerides with determined ephemerides. These results have provided indications of inadequacies in the force models, especially with the nongravitational forces, particularly those aspects associated with eclipsing.

A demonstration of sub meter GPS orbit determination and high precision user positioning

High-accuracy orbits have been determined for satellites of the Global Positioning System (GPS), with submeter orbit accuracy demonstrated for two well-tracked satellites. Baselines of up to 2000 km in North America determined with the GPS orbits shows daily repeatability of 0.3-2 parts in 10/sup 8/ and agree with very long baseline interferometry (VLBI) solutions at the level of 1.5 parts in 10/sup 8/. Tests used to assess orbit accuracy include orbit repeatability from independent data sets, orbit prediction, ground baseline determination, and formal errors. One satellite tracked for eight hours each day shows RMS errors below 1 m even when predicted more than three days outside of a 1-week data arc. These results demonstrate the powerful relative positioning capability available from differential GPS tracking. Baselines have also been estimated between Florida and sites in the Caribbean region over 1000 km away, with daily repeatability of 1-4 parts in 10/sup 8/. The best orbit estimation strategies included data arcs of 1-2 weeks, process noise models for tropospheric fluctuations, combined processing of GPS carrier phase and pseudorange data, and estimation of GPS solar pressure coefficients.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

Global Positioning System Operational Control System Accuracies

In early 1985, an improved ground Operational Control System (OCS) will maintain the navigation service. Primary among the OCS improvements over past GPS navigation systems is a global network of ground antennas (to upload satellite navigation data) and tracking/monitor stations. In addition, a refined Kalman filter will continuously estimate the Global Positioning System (GPS) satellite ephemerides and clock phases and frequencies. Although the user-GPS interface remains unaltered, the accuracy of the GPS navigation service is expected to improve by a factor of three. Using real and simulated GPS pseudo range radiometric tracking data, The Aerospace Corporation has completed a detailed error analysis which shows that the satellite clock noise contributes more than 90 percent of the total satellite-to-user pseudo range error. If the number of OCS uploads is increased to three per day (as planned), then the accuracy of the navigation service is also expected to improve by nearly a factor of three because the clock-noise contribution to the range error increases linearly with time. Also, this analysis shows the consequence of satellite ephermeris uncertainties in the GPS navigation application.