Accuracy Of Global Positioning System Research Articles

Detecting offsets in GPS time series: First results from the detection of offsets in GPS experiment

The accuracy of Global Positioning System (GPS) time series is degraded by the presence of offsets. To assess the effectiveness of methods that detect and remove these offsets, we designed and managed the Detection of Offsets in GPS Experiment. We simulated time series that mimicked realistic GPS data consisting of a velocity component, offsets, white and flicker noises (1/f spectrum noises) composed in an additive model. The data set was made available to the GPS analysis community without revealing the offsets, and several groups conducted blind tests with a range of detection approaches. The results show that, at present, manual methods (where offsets are hand picked) almost always give better results than automated or semi‒automated methods (two automated methods give quite similar velocity bias as the best manual solutions). For instance, the fifth percentile range (5% to 95%) in velocity bias for automated approaches is equal to 4.2 mm/year (most commonly ±0.4 mm/yr from the truth), whereas it is equal to 1.8 mm/yr for the manual solutions (most commonly 0.2 mm/yr from the truth). The magnitude of offsets detectable by manual solutions is smaller than for automated solutions, with the smallest detectable offset for the best manual and automatic solutions equal to 5 mm and 8 mm, respectively. Assuming the simulated time series noise levels are representative of real GPS time series, robust geophysical interpretation of individual site velocities lower than 0.2–0.4 mm/yr is therefore certainly not robust, although a limit of nearer 1 mm/yr would be a more conservative choice. Further work to improve offset detection in GPS coordinates time series is required before we can routinely interpret sub‒mm/yr velocities for single GPS stations.

Identifying and Tracking Major Events Using Geo-Social Networks

In recent years, several technological advancements have changed the lives of millions throughout the globe. These include broadband Internet wireless access, advanced mobile platforms and smartphones including accurate global positioning system capabilities, and the introduction of social networks. The fusion of these technological advances led to the massive adoption of mobile platform-operated social networking applications and unleashed new real-time and on-site social information. The ability to generate content anywhere and anytime leads to a detectable projection of real-life events on geo-social networks (GSN). For example, in preparation for a rally, the geo-social activity may precede the actual event, allowing predictive capabilities. Alternatively, in a natural event such as a wildfire, early content generated in the proximity of the event may allow early identification of the event and the assessment of its physical boundaries. In this article, we propose to use the massive and rapidly accumulating information communicated within GSN to identify and track major events and present a proof of concept. We discuss means and methods to retrieve relevant information from the networks, through a set of adequate spatial, temporal, and textual filters. Our preliminary empirical results corroborate our assumptions and show that major events may have detectable “abnormal” impact on GSN activities, which allows prompt identification and real-time tracking. Our approach is expected to pave the way to the development of real-time systems and algorithms for early identification and geographical tracking of major events.

Application of Global Positioning System Measuring Technology in Safety Monitoring of Highway Slope

The displacement is an important indicator of safety evaluation for highway slope. The highest measurement accuracy of global positioning system (GPS) achieves millimeter, and the sampling frequency can reach 20Hz. The displacement can be solved real-time, and the GPS measuring receiver adapts to the complex and harsh working environment. The paper summarizes the current technology level of GPS application in highway slope monitoring and introduces a low-cost monitoring technology that one receiver assemble multi-antenna to measure several points’ displacement. Based on the application of GPS technology using in highway slope safety monitoring system, this paper set the FuYin Highway as the engineering project and demonstrate how to apple the GPS technology in displacement monitoring and security evaluation.

Influence of Latrine Proximity and Type on Tubewell Water Quality and Diarrheal Disease in Bangladesh

Diarrheal diseases are endemic in Bangladesh, where sanitation is poor, and untreated drinking water extracted from shallow (<43 m) tubewells could partially contribute to disease propagation. This study measures the effects of local population–environment context on tubewell water quality and diarrheal disease incidence. The study site includes six villages in Matlab, Bangladesh, with approximately 12,000 residents. Study data include monthly Escherichia coli concentrations for 100 wells, monthly diarrheal events for all children under five, and a detailed water and sanitation infrastructure database created through a submeter accuracy Global Positioning System survey. We developed sanitation metrics to measure the relationship between tubewell water fecal contamination and estimates of human fecal loadings at varying scales. The relationship between childhood diarrhea and E. coli in drinking water was measured for households that obtained drinking water from survey wells. Results show that tubewells surrounded by unsanitary latrines, latrine-polluted ponds, and higher population densities were more frequently contaminated with fecal coliforms. The analysis also showed that poor sanitation infrastructure might affect childhood diarrheal disease via tubewell contamination. Our findings shed light on the importance of integrating population and environment data to identify circumstances in which shallow well water quality is compromised and children are put at risk of contracting diarrheal diseases. Sanitation interventions should highlight the spatial separation of latrines and drinking water wells to limit contamination.

The optimization of GPS positioning using response surface methodology

The Global Positioning System (GPS) has become a popular sensing system for positioning because it is free and always available and can be used in all weathers. However, the accuracy of GPS is dependent on the measurement factors selected by the surveyor. Therefore, the purpose of this research is to determine the optimal factors of the GPS positioning process. The selected process variables were measurement time and duration, recording interval, and mask angle. To determine the optimum conditions of these factors, a three-level Box–Behnken design was utilized. The results indicated that the optimum conditions of the experimental factors are 13 h as measurement time, 21.77 min as the measurement duration, 22.43 s as the range interval, and 8° as the mask angle.

Effect of GPS Feedback on Lactate Threshold Pacing in Intercollegiate Distance Runners

In their roles as coaches, the authors have observed that first-year collegiate distance runners often have difficulty running at prescribed training paces during lactate threshold (LT) training runs. Previous research has validated the accuracy of global positioning system (GPS) devices in providing distance and velocity feedback during running. The purpose of this study was to determine the efficacy of using the Garmin Forerunner 305 GPS watch (Garmin) to reduce deviations from prescribed training paces during LT runs with first-year collegiate runners. Participants were two groups of varsity cross country runners who completed a three-week LT training intervention either with (n = 5) or without (n = 6) a Garmin device. Prescribed training paces were based off an initial time-trial. In both the pre- and post-test runs, in which all runners ran without a Garmin device, differences were calculated between the prescribed pace and actual pace. The comparisons revealed a significant difference between the training groups in the post-test. Those runners who trained with the Garmin device had a significant decrease in pacing variability. This suggests that GPS pacing feedback appears to be an effective tool at improving LT pacing in first-year collegiate distance runners.

ECOPS: Energy-Efficient Collaborative Opportunistic Positioning for Heterogeneous Mobile Devices

The fast growing popularity of smartphones and tablets enables us to use various intelligent mobile applications. As many of those applications require position information, smart mobile devices provide positioning methods such as Global Positioning System (GPS), WiFi-based positioning system (WPS), or Cell-ID-based positioning service. However, those positioning methods have different characteristics of energy-efficiency, accuracy, and service availability. In this paper, we present an Energy-Efficient Collaborative and Opportunistic Positioning System (ECOPS) for heterogeneous mobile devices. ECOPS facilitates a collaborative environment where many mobile devices can opportunistically receive position information over energy-efficient and prevalent WiFi, broadcasted from a few other devices in the communication range. The position-broadcasting devices in ECOPS have sufficient battery power and up-to-date location information obtained from accurate but energy-inefficient GPS. A position receiver in ECOPS estimates its location using a combination of methods including received signal strength indicators and 2D trilateration. Our field experiments show that ECOPS significantly reduces the total energy consumption of devices while achieving an acceptable level of location accuracy. ECOPS can be especially useful for unique resource scarce, infrastructureless, and mission critical scenarios such as battlefields, border patrol, mountaineering expeditions, and disaster area assistance.

Integrating stations from the North America Gravity Database into a local GPS-based land gravity survey

Abstract The ability to augment local gravity surveys with additional gravity stations from easily accessible national databases can greatly increase the areal coverage and spatial resolution of a survey. It is, however, necessary to integrate such data seamlessly with the local survey. One challenge to overcome in integrating data from national databases is that these data are typically of unknown quality. This study presents a procedure for the evaluation and seamless integration of gravity data of unknown quality from a national database with data from a local Global Positioning System (GPS)-based survey. The starting components include the latitude, longitude, elevation and observed gravity at each station location. Interpolated surfaces of the complete Bouguer anomaly are used as a means of quality control and comparison. The result is an integrated dataset of varying quality with many stations having GPS accuracy and other reliable stations of unknown origin, yielding a wider coverage and greater spatial resolution than either survey alone.

Experimental Study on Accuracy of GPS Positioning

Geophysical measurement relies on the positioning accuracy of GPS (global positioning system). Usually the positioning accuracy is area dependent. This paper uses a commercially available GPS receiver to verify its positioning accuracy with practical measurement in a small area. With a measurement setup in an open ground, the results show that even for the fixed point, the GPS measured positioning error of about 0.234 meter could be observed for a period of time. Of 12 GPS measured distance errors, only one is about 5.7 meters, all others are within the range of 3-5 meters of GPS receiver specification.

Lists, Spatial Practice and Assistive Technologies for the Blind

Lists, Spatial Practice and Assistive Technologies for the Blind

Variable selection in regression models used to analyse Global Positioning System accuracy in forest environments

Reliable information on the geographic location of individual points using GPS (Global Positioning System) receivers requires an unobstructed line of sight from the points to a minimum of four satellites. This is often difficult to achieve in forest environments, as trunks, branches and leaves can block the GPS signal. Forest canopy can be characterized by means of dasymetric parameters such as tree density and biomass volume, but it is important to know which parameters in particular have a bearing on the accuracy of GPS measurements. We analyzed the relative influence of forest canopy and GPS-signal-related variables on the accuracy of the GPS observations using a methodology based on linear regression models and bootstrapping and compared the results to those for a classical variable-selection method based on hypothesis testing. The results reveal that our methodology reduces the number of significant variables by approximately 50% and that both forestry and GPS-signal-related variables are significant.

Evaluation of the Effect of Radio Frequency Interference on Global Positioning System (GPS) Accuracy via GPS Simulation

In this study, Global positioning system (GPS) simulation is employed to study the effect of radio frequency interference (RFI) on the accuracy of two handheld GPS receivers; Garmin GPSmap 60CSx (evaluated GPS receiver) and Garmin GPSmap 60CS (reference GPS receiver). Both GPS receivers employ the GPS L1 coarse acquisition (C/A) signal. It was found that with increasing interference signal power level, probable error values of the GPS receivers increase due to decreasing carrier-to-noise density (C/N0) levels for GPS satellites tracked by the receivers. Varying probable error patterns are observed for readings taken at different locations and times. This was due to the GPS satellite constellation being dynamic, causing varying GPS satellite geometry over location and time, resulting in GPS accuracy being location/time dependent. In general, the highest probable error values were observed for readings with the highest position dilution of precision (PDOP) values, and vice versa. Defence Science Journal, 2012, 62(5), pp.338-347 , DOI:http://dx.doi.org/10.14429/dsj.62.1606

Outdoor stereo camera system for the generation of real-world benchmark data sets

We describe a high-performance stereo camera system to capture image sequences with high temporal and spatial resolution for the evaluation of various image processing tasks. The system was primarily designed for complex outdoor and traffic scenes that frequently occur in the automotive industry, but is also suited for other applications. For this task the system is equipped with a very accurate inertial measurement unit and global positioning system, which provides exact camera movement and position data. The system is already in active use and has produced several terabytes of challenging image sequences which are partly available for download.

A low-cost GPS GSM/GPRS telemetry system: performance in stationary field tests and preliminary data on wild otters (Lutra lutra).

BackgroundDespite the increasing worldwide use of global positioning system (GPS) telemetry in wildlife research, it has never been tested on any freshwater diving animal or in the peculiar conditions of the riparian habitat, despite this latter being one of the most important habitat types for many animal taxa. Moreover, in most cases, the GPS devices used have been commercial and expensive, limiting their use in low-budget projects.Methodology/Principal FindingsWe have developed a low-cost, easily constructed GPS GSM/GPRS (Global System for Mobile Communications/General Packet Radio Service) and examined its performance in stationary tests, by assessing the influence of different habitat types, including the riparian, as well as water submersion and certain climatic and environmental variables on GPS fix-success rate and accuracy. We then tested the GPS on wild diving animals, applying it, for the first time, to an otter species (Lutra lutra). The rate of locations acquired during the stationary tests reached 63.2%, with an average location error of 8.94 m (SD = 8.55). GPS performance in riparian habitats was principally affected by water submersion and secondarily by GPS inclination and position within the riverbed. Temporal and spatial correlations of location estimates accounted for some variation in the data sets. GPS-tagged otters also provided accurate locations and an even higher GPS fix-success rate (68.2%).Conclusions/SignificanceOur results suggest that GPS telemetry is reliably applicable to riparian and even diving freshwater animals. They also highlight the need, in GPS wildlife studies, for performing site-specific pilot studies on GPS functioning as well as for taking into account eventual spatial and temporal correlation of location estimates. The limited price, small dimensions, and high performance of the device presented here make it a useful and cost-effective tool for studies on otters and other aquatic or terrestrial medium-to-large-sized animals.

Integrated Navigation of Mobile Robot Based on Neural Network and Fault Detection

When global positioning system (GPS) signal outages, the integrated navigation accuracy of GPS and strap-down inertial navigation system (SINS) will decline with time, and even navigation system cannot work. To avoid this, a new design is introduced. When GPS works normally, square root filter estimates the errors of position, velocity and attitude and compensates the outputs of SINS. When GPS is out of order, back propagation neural network (BPNN) will take the place of GPS to calculate the error parameters, thus the accuracy of navigation will enhance. And in this paper, the unit of fault detection is added to detect whether GPS signal outages or not. The simulation results show the effectiveness of this method

Techniques to improve the GPS precision

The accuracy of a standard market receiver GPS (Global Positioning System) is near 10-15 meters the 95% of the times. To reach a sub-metric level of accuracy some techniques must be used [1]. This article describes some of these procedures to improve the positioning accuracy by using a low-cost GPS in a differential relative positioning way. The proposed techniques are some variations of Kalman, fuzzy logic and information selection.

Performance of High-Rate Kinematic GPS During Strong Shaking: Observations from Shake Table Tests and the 2010 Chile Earthquake

Performance of High-Rate Kinematic GPS During Strong Shaking: Observations from Shake Table Tests and the 2010 Chile EarthquakeOver the last decade, the 1-sample-per-second kinematic Global Positioning System (GPS) has been used as a displacement sensor in earthquake observations and for structural health monitoring. Many researchers in both seismology and engineering have expressed the desire for higher-sample-rate (10-sample-per-second or higher) GPS data to acquire high-frequency displacement information. We performed several shake table tests of GPS observation on 29 April, 2009 for the purpose of evaluating the performance of high-rate kinematic GPS. We found that the accuracy of high-rate kinematic GPS depended on antenna movement, but was independent of receiver sampling rate. The errors in kinematic GPS measurements during the periods of strong shaking were systematically larger than those during the static periods. Furthermore, we found that these large errors were coincident with large accelerations and jerks in the motions experienced by the GPS receivers and antennas. Observations from the 2010 earthquake in Maule, Chile (M 8.8) indicated that strong ground motions can degrade the accuracy of high-rate kinematic GPS measurements. Significant jerks and/or accelerations can cause GPS units to temporarily lose tracking on satellite signals and lead to gaps in GPS-recorded seismograms.

Positional accuracy control of extracted roads from VHR images using GPS kinematic survey: a proposal of methodology

This article describes a methodology developed for analysing the positional accuracy of extracted roads from very high resolution remote-sensing images by means of a Global Positioning System (GPS) kinematic survey (as control). Traditionally, this control has been performed by using a set of points located on the image, comparing their positions with those obtained from more accurate sources. In this work, we propose the use of lines for this purpose. These control elements are obtained by means of a more accurate kinematic GPS survey. Thus we analyse the main aspects of this methodology such as the population, size of sample, process (for obtaining the control set of lines), edition of lines, control methodologies based on lines, etc. We have applied the proposed methodology to a real example from an orthorectified Quickbird image. The results obtained show that the proposed methodology is more efficient than those based on isolated points.

A DSRC Doppler-Based Cooperative Positioning Enhancement for Vehicular Networks With GPS Availability

Position information, as a fundamental element for many of the modern vehicle-based logistic applications, is comprehensively provided by Global Navigation Satellite Systems (GNSS) such as the Global Positioning System (GPS). A variety of applications, including navigation and intelligent transpiration systems, require position data with certain accuracy. However, the shortcomings of GNSS, such as limited accuracy and availability, have been a motivation for recently emerging Cooperative Positioning (CP) methods based on vehicle–vehicle and vehicle–infrastructure communications. The majority of earlier CP methods assume the availability of distances between the participating nodes as a main parameter, using common techniques of radio ranging such as the Received Signal Strength (RSS), Time of Arrival (TOA), and Time Difference of Arrival (TDOA). However, the feasibility of these radio-ranging methods in the harsh environment of vehicular networks is questionable. Avoiding the radio-ranging challenges, in this paper, a new CP method is presented to improve the GPS estimates using internode range-rates based on the Doppler shift of the carrier of Dedicated Short-Range Communications (DSRC) signals, which is the nominated medium for vehicular communication. Depending on the speed of the participating vehicles and traffic intensity, improvement of up to 48% over the GPS accuracy is achieved. Because the Doppler effect is used, relative mobility of the nodes, which is generally a challenge for radio-ranging techniques, is a requirement for the proposed method, making it a more suitable solution for vehicular applications. Addressing the viability of the proposed technique, Doppler-based range-rating is verified in practice using DSRC transceivers. One section of highway is surveyed and modeled for simulation. In addition, GPS estimates are provided by feeding GPS signals, generated by a GPS signal generator, to a real GPS receiver.

Optimizing of ANFIS for estimating INS error during GPS outages

Global positioning system (GPS) has been extensively used for land vehicle navigation systems. However, GPS is incapable of providing permanent and reliable navigation solutions in the presence of signal evaporation or blockage. On the other hand, navigation systems, in particular, inertial navigation systems (INSs), have become important components in different military and civil applications due to the recent advent of micro-electro-mechanical systems (MEMS). Both INS and GPS systems are often paired together to provide a reliable navigation solution by integrating the long-term GPS accuracy with the short-term INS accuracy. This article presents an alternative method to integrate GPS and INS systems and provide a robust navigation solution. This alternative approach to Kalman filtering (KF) utilizes artificial intelligence based on adaptive neuro-fuzzy inference system (ANFIS) to fuse data from both systems and estimate position and velocity errors. The KF is usually criticized for working only under predefined models and for its observability problem of hidden state variables, sensor error models, immunity to noise, sensor dependency, and linearization dependency. The training and updating of ANFIS parameters is one of the main problems. Therefore, the challenges encountered implementing an ANFIS module in real time have been overcome using particle swarm optimization (PSO) to optimize the ANFIS learning parameters since PSO involves less complexity and has fast convergence. The proposed alternative method uses GPS with INS data and PSO to update the intelligent PANFIS navigator using GPS/INS error as a fitness function to be minimized. Three methods of optimization have been tested and compared to estimate the INS error. Finally, the performance of the proposed alternative method has been examined using real field test data of MEMS grade INS integrated with GPS for different GPS outage periods. The results obtained outperform KF, particularly during long GPS signal blockage.