GNSS Multireceiver Vector Tracking

This paper presents a new cycle slip detection and repair method using Total Electron Content Rate (TECR) information derived from individual satellite dual-frequency data of a single Global Positioning System (GPS) receiver while pseudorange measurements are subject to arbitrarily large range errors. Sudden Increase of Pseudorange Error (SIPE), similar to cycle slips in nature, is quite common in various data acquisition scenarios. The basic principle of this method is to take advantage of the fact that the ionospheric TECR does not exceed certain threshold, which is set as 0.35 TECU/s in this study. Analytic expressions to evaluate the effect of SIPE on cycle slip detections have been developed. The search spaces for cycle slip candidate pairs are defined, given a predefined (sufficiently large) SIPE value. Two cycle slip validation rules are proposed to validate the cycle slip candidates. Over 99.9% of candidates can be rejected with the application of two validation rules. The theoretically maximal number of remaining cycle slip candidate pairs (NRCP) can be exactly calculated based on the magnitude of SIPE, TECR threshold, and the data sampling interval. After applying validation rules, the correct cycle slip pairs can be identified using a modified low-order polynomial fitting method. This method is tested on 13 high rate (1-Hz) dual-frequency datasets recorded by both ground-based static and satellite-borne high dynamic GPS receivers under various levels of ionospheric activities. Simulated cycle slips in 12 different possible cases and varying SIPE magnitudes are introduced into the data sets. In each test scheme, averagely 600–750 pairs of cycle slips are simulated. The SIPE magnitudes are set to vary from 50.0 m to 1000.0 m. Test results show that all the cycle slips in all the test schemes and all the datasets have been successfully detected and fixed even with a maximum SIPE of 1000.0 m in pseudoranges. A distinct advantage of this method is that it works in real-time with individual satellite’s data from a single dual-frequency receiver, even if the carrier phases have virtually any size of cycle slips and the pseudoranges have virtually arbitrarily large errors.

Global Positioning System (GPS) data for phase delay differential between Ll and L2 frequencies are analyzed by a model in which the combined effect of hardware and phase ambiguity terms is represented by a constant for each receiver‐satellite path and the ionospheric contribution is represented by the RIBG model (ray trace through the combined ICED (ionospheric conductivity and electron density), Bent, and Gallagher ionospheric models). RIBG contains a detailed global empirical climatological ionospheric model of the electron density versus height profile (EDP) from 80 km up to the plasmapause, which is combined with a full three‐dimensional ray trace propagation model. Discrete inverse theory (DIT) is used to fit the driving parameters of RIBG to about 2 hours worth of data from a single GPS receiver at various geographical locations. Validity is demonstrated by the ability of the GPS‐updated RIBG model to predict independent measurements of (1) vertical total electron content (TEC) over the ocean out to substantial distances from a GPS receiver, often in excess of 2000 km at midlatitudes, and (2) the electron density versus height profile (EDP). Performance variation with magnetic latitude is noted. Flexibility in RIBG to adjust different driving parameters for different parts of the EDP, in order to obtain a best fit of GPS data, benefits the EDP prediction. Implications of this approach for GPS navigation and other radio system applications are discussed.

Besides their intended use in radio navigation, global positioning system (GPS) satellite signals provide convenient radio beacons for ionospheric studies. Among other propagation phenomena, the ionosphere affects GPS signal propagation through amplitude scintillations that develop after radio waves propagation through ionospheric electron density irregularities. This paper outlines the design, testing, and results of a specialized GPS receiver to monitorL-band scintillations. The scintillation monitor system consists of a commercial GPS receiver development kit with its software designed to log signal strength and carrier phase from up to 12 channels at one sample per second rate. Other prime features of the monitor include the data compression transmission and processing. Here is the fact that they are inexpensive and compact and therefore can be readily proliferated.

The global positioning system (GPS) has become the most extensively used positioning and navigation tool in the world. Applications of GPS abound in surveying, mapping, transportation, agriculture, military planning, GIS, and the geosciences. However, the positional and elevation accuracy of any given GPS location is prone to error, due to a number of factors. The applications of Global Positioning System (GPS) positioning is more and more popular, especially the intelligent navigation system which relies on GPS and Dead Reckoning technology is developing quickly for future huge market in China. In this paper a practical combined positioning model of GPS/DR/MM is put forward, which integrates GPS, Gyro, Vehicle Speed Sensor (VSS) and digital navigation maps to provide accurate and real-time position for intelligent navigation system. This model is designed for automotive navigation system making use of Kalman filter to improve position and map matching veracity by means of filtering raw GPS and DR signals, and then map-matching technology is used to provide map coordinates for map displaying. In practical examples, for illustrating the validity of the model, several experiments and their results of integrated GPS/DR positioning in intelligent navigation system will be shown for the conclusion that Kalman Filter based GPS/DR integrating position approach is necessary, feasible and efficient for intelligent navigation application. Certainly, this combined positioning model, similar to other model, can not resolve all situation issues. Finally, some suggestions are given for further improving integrated GPS/DR/MM application.

The development of global positioning systems (GPS) has cleared the way for a better understanding of the globe and the systems surrounding the earth. The GPS signals that are sent out and received by GPS receivers are affected by severe space weather (in the ionosphere) as well as atmospheric weather and lithospheric disturbances. These disturbances not only result in inaccuracies in GPS location but also make it difficult to make the necessary corrections to those faults. The study of these perturbations is helpful in gaining an understanding of the phenomenal changes that occur in the ionosphere as a result of the Sun and its solar effects, which include solar flares, sunspot numbers, solar winds, geomagnetic fields, and natural disasters such as earthquakes and thunderstorms, among other things. In this study, an effort is made to highlight the distinctions between geomagnetic calm days and disturbed days that occurred in January 2022. The research is carried out by using parametric approaches to the GPS vertical total electron content (VTEC) at Hyderabad (17.4°N, 78.5°E), which is a station with a low height. An examination of the power spectral densities (PSDs) of both the tranquil and the disturbed conditions is carried out. The improvement in VTEC data was noted on two days in January 2022 that had low geomagnetic activity; these days were the 6th and 13th. On the sixth of January 2022, enhancements can be seen at the normalised frequencies of 0.4966 and 0.7683, with a power spectral density (PSD) of -10.14dB and -12.94dB, respectively. On the thirteenth of January 2022, enhancements can be seen at the normalised frequencies of 0.5005 and 0.956, with PSDs of -9.264dB and -8.392dB. When compared to the preceding records, it can be seen very clearly that the PSDs of both geomagnetically tranquil and disturbed days are rather comparable to one another.

Coastal sea level measurements using a single geodetic GPS receiver

The traditional approach to both earthquake and Global Positioning System (GPS) location problems in a homogeneous half-space produces a nonlinear relationship between a set of known positions, seismic stations or GPS satellites, and an unknown point, an earthquake hypocenter or GPS receiver. Linearization, followed by an iterative inversion, is typically used to solve both problems. Although sources and receivers are swapped in the earthquake and GPS location problems, the obser- vation equation is the same for both, due to the principle of reciprocity. Consequently, the mechanical part of the solution of the equations is the same and single-step closed- form solutions for the GPS location problem, such as the Bancroft algorithm, can also be used to solve for earthquake hypocenters in a homogeneous half-space. This article applies the Bancroft algorithm to synthetic and real data for the Charlevoix seismic zone and compares the location of ∼1200 events estimated with both the Bancroft algorithm and HYPOINVERSE. The Bancroft algorithm shows quantifiable improve- ments in accuracy compared with traditional methods. We also show how tools com- monly used by the GPS community, such as the geometric dilution of precision, can be used to better estimate the precision of the results obtained by a seismic network.

A smart city’s main purpose is to provide intelligent responses to different problems of the rapid urban population growth. For instance, integrating fleet management solutions into intelligent transportation systems (ITS) can efficiently resolve transportation problems relying on each vehicle information. Usually, the position estimate is ensured by the integration of the Global Positioning System (GPS) and Inertial Navigation Systems (INS). For multisensor data fusion, the Extended Kalman Filter (EKF) is generally applied using the sensor’s measures and the GPS position as a helper. However, the INS are expensive and require more complex computing which induces restrictions on their implementation. Furthermore, the EKF performance depends on the vehicle dynamic variations and may quickly diverge because of environmental changes. In this paper, we present a robust low cost approach using EKF and Support Vector Machines (SVM) to reliably estimate the vehicle position by limiting the EKF drawbacks. The sensors used are a GPS augmented by a low cost wireless sensor network. When GPS signals are available, we train SVM on different dynamics and outage times to learn the position errors so we can correct the future EKF predictions during GPS signal outages. We obtain empirically an improvement of up to 94% over the simple EKF predictions in case of GPS failures.

The geomagnetic storm caused numerous disturbances of the ionosphere, particularly, plasma irregularities, which can affect the accuracy of Global Positioning System (GPS) positioning. This study quantifies the impacts of the ionospheric disturbance on GPS precise point positioning (PPP) solutions during extreme space weather events by taking advantage of 260 GPS stations in China. The results show that the average positioning error in China increased significantly during the ionospheric disturbance on 08 Sep 2017. By comparing the kinematic GPS‐PPP (3‐D) error distribution map and the ROTI index map, it is found that the ionospheric irregularities are one of the main reasons for degrading the GPS positioning accuracy. The statistical analysis results show that when the ionospheric scintillation index S4 is greater than 0.4, the average kinematic GPS‐PPP error calculated by the station is higher than 0.8 m.

The use of a specialized Global Positioning System (GPS) to conduct high-speed surveys of roadway alignment, grade, and cross-slope characteristics is discussed. The system uses a single GPS receiver that has 24 channels monitoring four separate antennas (six channels each). The collection of attitude (heading, pitch, and roll) is made possible through the relative orientation of the antennas. By mounting the system on a road surveillance vehicle, accurate grades, superelevation, and crown measurements can be made without differentially correcting the GPS data. However, to gather precise positional data that correspond to the roadway measurements, differential correction with a GPS base station at a fixed known point is required. The design and use of this attitude GPS unit are addressed. Accuracy specifications for static testing are provided along with techniques to maximize this accuracy. Kinematic data collection is depicted for a local road and a freeway off-ramp. The use of digital terrain modeling technology provides a promising graphic database representation of the roadway characteristics.

Global positioning system (GPS) telemetry units are now small enough to be deployed on terrestrial and semi-aquatic turtles. Many of these GPS units use snapshot technology which collects raw satellite and timestamp data during brief periods of data recording to minimize size. We evaluated locations from snapshot GPS units in stationary tests and on wood turtles (Glyptemys insculpta) in northeastern Minnesota. Stationary GPS units were placed in wood turtle habitat to evaluate location accuracy, fix success rate, and directional bias. The GPS fix success rate and accuracy were reduced in closed canopy conditions and when the stationary GPS unit was placed under a log to simulate wood turtle hiding behavior. We removed GPS location outliers and used a moving average calculation to reduce mean location error in stationary tests from 27 m (SD = 38) to 10 m (SD = 8). We then deployed GPS units and temperature loggers on wood turtles and collected 122,657 GPS locations and 242,781 temperature readings from 26 turtles from May to September 2015 and 2016. Location outliers accounted for 12% of locations when the GPS receiver was on a turtle. We classified each wood turtle location based on the GPS location and by comparing temperature profiles from river, sun, and shaded locations to the temperature logger on the turtle. We estimated that wood turtles were on land 68% (SD = 12) of the time from May to September. The fix success rate for land locations was 38% (SD = 9), indicating that wood turtles often use habitats with obstructed views of the sky. Mean net daily movement was 55 m (SD = 192). Our results demonstrate that snapshot GPS units and temperature loggers provide fine-scale GPS data useful in describing spatial ecology and habitat use of semi-aquatic turtles.

This paper presents a model to predict the GDOP value (Geometric Dilution of Precision) and the probability of its occurrence at a point in space and time using airborne LiDAR (Light Detection and Ranging) data and the ultra-rapid product (URP) available from the International GPS Service. LiDAR data help to classify the terrain around a GPS (Global Positioning System) receiver into categories such as ground, opaque objects, translucent objects and transparent regions as per their response to the transmission of GPS signal. Through field experiments it is established that URP can be used satisfactorily to determine GDOP. Further experiments have shown that the translucent objects (mainly trees here) lower the GDOP quality as they obstruct the GPS signal. LiDAR data density on trees is used as a measure of the translucency of trees to the GPS signal. Through GPS observations taken in field a relationship has been established between LiDAR data density on trees and the probability that a satellite which is behind the tree is visible at the GPS receiver. A model is presented which, for all possible combinations of visible satellites, computes the GDOP value along with the probability of occurrence of this GDOP. A few results are presented to show the performance of the model developed and its possible application in location based queries.

While GPS (Global Positioning System) navigation and GPS based autonomous car driving techniques are mature, the security of GPS signal has not been a primary system concern. In fact, it has been shown that an ordinary GPS can be easily spoofed by a low-cost, open-source based software defined radio (SDR) system such as bladeRF and HackRF [3, 4] which can cause serious complications to the navigation system of the car especially for self-driving cars which are driven based on the information from sensors, cameras, and GPS. In this work, we design a new GPS authentication system called lightweight authentication GPS (AuthGPS) to authenticate GPS signal against GPS spoofing and LTE base station broadcast message spoofing. In the past, there have been many successful attempts on GPS spoofing which resulted in shifting the destination of the car to the spoofer's desired location. In a case where the car is connected to the Internet via LTE network, the navigation system can find out if the GPS is spoofed by acquiring the correct GPS satellite information from LTE base stations' location information. However, a skillful attacker can spoof the LTE base station signals [7] as well using another SDR which will produce spoofed LTE base station information. Hence giving wrong information about GPSinformation according to the will of the attacker. Currently, there are defense methods against the GPS spoofing [6]. One of them is signal-processing-based methods. By monitoring unusual or unreasonable signal changes at GPS receivers, GPS spoofing attack can be detected. Received Power Monitoring (RPM) looks at all the received amplitude and automatic gain control (AGC) setpoint [1]. The receiver will sense drastic power jump if a spoofing attack occurs. However, an overly powerful spoofing attack with noise is not detectable in the case of this mechanism. Another way to detect spoofing is the symmetric-key encryption mechanism of GPS signals. According to previous research [2], encrypted precision code for anti-spoofing referred to as P(Y) code, might not be able to be spoofed. A spoofing attack can be detected by calculating cross-correlation between spoofed coarse/acquisition code, referred to as C/A code, and P(Y) code. Unfortunately, this P(Y) code is only for military purpose while the C/A code can be publicly accessible. This method requires knowledge of specific key which is not revealed to the public to decrypt P(Y) code. Monitoring the direction of arrival of the signals can be one of the methods [6]. A GPS receiver measures the direction-of-arrival vector with more than 3 antennas. Even though this signal-geometrybased system with multiple antennas makes GPS robust, an attacker can spoof signals from multiple directions, which is more difficult to detect the spoofing. The idea here is to develop a system that can discriminate the spoofed signal without complex computation or heavy message exchange. An important component of AuthGPS is a verification of valid GPS satellite information via LTE base stations' location information. We propose 6-digit one-time password-based authentication system in this paper.

Purpose – The purpose of this paper is to discuss the applicability of Global Positioning System (GPS) ionospheric delay correction models. Ionospheric delay is the most influential error source in GPS positioning, and ionospheric refraction is difficult to be corrected by dual frequency measurement for the common single frequency GPS receivers. Generally, ionospheric models are employed to correct errors. In order to analyze the ionospheric influence to GPS signals and the accuracy and adaptability of GPS ionospheric error correction models a quantificational analysis for ionospheric error correction models is absolutely necessary.Design/methodology/approach – On the base of the mechanism of ionospheric error, the Klobuchar model that is widely used and actual measured correction model (including local and global ionospheric error correction models) are analyzed in detail. With the data about ionosphere obtained from GPS authority Crustal Dynamics Data Information System, the precision and adaptability o...

The car navigation service has opened through the global positioning system (GPS). People's lives have changed through car navigation services, and this service is indispensable nowadays. GPS provides reliable location accuracy in open space, but its location accuracy is degraded where multipath and other error factors are present. In particular, since GPS signals must be received in order to calculate the position, the navigation system cannot calculate the position in an indoor space such as underground parking lot, subway or tunnel where GPS signals are cut off. When car navigation is performed in an indoor parking lot where GPS signals are not transmitted, the user cannot calculate the current location, so the user has to go out by relying on the traffic sign because he does not know the current location. Also, when the user leave the parking lot, the car navigation system has problems. In an urban canyon, it is difficult to calculate accurate current position due to multipath. Because the route is calculated through the current location and route, the car navigation system provides the wrong route to the user. In addition, when entering a tunnel while using car navigation, the car navigation system calculates the position using the initial tunnel entry velocity estimated by the GPS. As the speed of the user increases or decreases, the position error also increases. Then the position suddenly changes when passing through the tunnel. And it is difficult to provide a proper guidance at the branch road or exit in the tunnel because of the positioning error. People are demanding a complete car navigation service, but the current navigation service provides the wrong route and position information to the user where the GPS signal quality is poor. In order to solve the above problem, in this paper, we have studied to improve the user's position accuracy by using LTE signal and mobile phone internal sensor. In general, observed time difference of arrival (OTDOA) technique is applied for the LTE based positioning. Because this method gives tens of meters of error, it is difficult to be used for the car navigation service. In our research, we estimate the position using the LTE signal strength. The difference from conventional fingerprinting method is that instead of using only current signal strength, the signal strength pattern accumulated while moving is utilized to estimate the user position. The signal strength increases as the user approach the access point (AP), and decreases as the user move away from the AP. Therefore, when a user moves and stores signal strength with respect to a specific AP, a pattern that could occur only in the corresponding region is saved. There are many similar candidates in the database when using only the current signal strength. However, when using a pattern, similar candidates exist only around the true position. And, when using several LTE signals, the positioning accuracy could be increased. Since the user receives multiple LTE signals, the pattern becomes surface. The surface is compared with the database, and the position with the highest correlation value is estimated as the current position. We call this method surface correlation (SC). In order to verify the performance of the proposed method, experiments were conducted in the Gangnam beltway tunnel in Seoul. The testbed consisted of three tunnel and total distance is almost 11.8 Km. In the tunnel, repeater and several antennas are installed to widen the area of the LTE signal. When an LTE signal is received by the vehicle, the largest signal strength is received every time when the vehicle passes the nearest antenna. As a result, for a specific LTE signal, when the vehicle has passed through the LTE signal region, a unique pattern with multiple peaks is generated. In order to estimate the position, we first estimate the position with the SC technique. Then, the estimated position is corrected by comparing the peak of the currently received pattern with the peak of the database. Through this method, the position was estimated with an error of less than 50meter in the tunnel. Conclusion In this research, the LTE signal strength based positioning technology is presented. Especially, this technology, SC, provides the positioning performance that could be used for the car navigation in the tunnel where GPS signal is blocked. We expected that user would be use the accurate car navigation service through this technology in the GPS challenging environment.