Global Positioning System Location Research Articles

A seasonal pulse of ungulate neonates influences space use by carnivores in a multi-predator, multi-prey system.

The behavioral mechanisms by which predators encounter prey are poorly resolved. In particular, the extent to which predators engage in active search for prey versus incidentally encountering them has not been well studied in many systems and particularly not for neonate prey during the birth pulse. Parturition of many large herbivores occurs during a short and predictable temporal window in which young are highly vulnerable to predation. Our study aims to determine how a suite of carnivores responds to the seasonal pulse of newborn ungulates using contemporaneous global positioning system (GPS) locations of four species of predators and two species of prey. We used step‐selection functions to assess whether coyotes, cougars, black bears, and bobcats encountered parturient adult female ungulates more often than expected by chance in a low‐density population of mule deer and a high‐density population of elk. We then assessed whether the carnivore species that encountered parturient prey more often than expected by chance did so by shifting their habitat use toward areas with a high probability of encountering neonates. None of the four carnivore species encountered GPS‐collared parturient mule deer more often than expected by chance. By contrast, we determined that cougar and male bear movements positioned them in the proximity of GPS‐collared parturient elk more often than expected by chance which may provide evidence of searching behavior. Although both male bears and cougars exhibited behavior consistent with active search for neonates, only male bears used elk parturition habitat in a way that dynamically tracked the phenology of the elk birth pulse suggesting that maximizing encounters with juvenile elk was a motivation when selecting resources. Our results suggest that there is high interspecific and intersexual variability in foraging strategies among large mammalian predators and their prey.

Black‐tailed deer seasonal habitat selection: accounting for missing global positioning system fixes

AbstractQuantitative models of black‐tailed deer (Odocoileus hemionus columbianus) habitat selection do not exist for Pacific Northwest landscapes but are needed to make predictions of how deer respond to timber harvest. We developed models to estimate habitat selection by black‐tailed deer within seasonal home ranges in the west‐central Cascade Mountains, Washington, USA, from 2008–2019. Even with moderately high global positioning system (GPS) fix success within summer and winter (both averages ≥0.87), we were concerned about landscape or vegetation characteristics causing fix success failure that would bias estimates of habitat selection. Year of GPS‐collar production, deer activity, and diel period (night, day, crepuscular) were associated with fix success. The odds of acquiring a fix were 2.53 times greater when the deer were inactive compared to active, and this difference was greater for those deer with higher average percent canopy cover within their home range. These relationships only explained a portion of the variation in the data and did not negate concerns about the effects of missing locations when estimating habitat selection, so we estimated deer habitat selection within summer and winter using an integrated step selection function (iSSF) and a probability of detection integrated step selection function (PDiSSF). The iSSF ignored missing fixes; the PDiSSF accounted for GPS fix failure due to the landscape and vegetation conditions. Covariates in the final summer PDiSSF included step length, an index of forage biomass, distance to cover‐forage edge, and distance to road. The winter model was similar but did not include forage biomass. We modeled the probability of detection in the PDiSSF as a function of canopy cover in both seasonal models. The standard iSSF resulted in estimates of stronger selection for areas with higher biomass, presumably because fix success was higher in these more open areas. Predictions of habitat selection from the final PDiSSF summer model evaluated well with independent data from a nearby study area. Evaluation of the final winter model was less promising. Ignoring missing GPS locations, even with an average fix success as high as 87%, would have led to different predictions of habitat selection by black‐tailed deer. We recommend that researchers consider the effect of habitat‐induced bias in fix success on the accuracy of estimates of habitat selection and consider using the PDiSSF to remove bias related to missing fixes.

Female and male Leach's Storm Petrels (Hydrobates leucorhous) pursue different foraging strategies during the incubation period.

Reproduction in procellariiform birds is characterized by a single egg clutch, slow development, a long breeding season and obligate biparental care. Female Leach's Storm Petrels Hydrobates leucorhous, nearly monomorphic members of this order, produce eggs that are between 20 and 25% of adult body weight. We tested whether female foraging behaviour differs from male foraging behaviour during the ~ 44-day incubation period across seven breeding colonies in the Northwest Atlantic. Over six breeding seasons, we used a combination of Global Positioning System and Global Location Sensor devices to measure characteristics of individual foraging trips during the incubation period. Females travelled significantly greater distances and went farther from the breeding colony than did males on individual foraging trips. For both sexes, the longer the foraging trip, the greater the distance. Independent of trip duration, females travelled farther, and spent a greater proportion of their foraging trips prospecting widely as defined by behavioural categories derived from a Hidden Markov Model. For both sexes, trip duration decreased with date. Sex differences in these foraging metrics were apparently not a consequence of morphological differences or spatial segregation. Our data are consistent with the idea that female foraging strategies differed from male foraging strategies during incubation in ways that would be expected if females were still compensating for egg formation.

In-Motion Coarse Alignment Method Based on Position Loci and Optimal-REQUEST for SINS

In this paper, an improved in-motion coarse alignment method is proposed for a strapdown inertial navigation system (SINS) using position loci obtained from the Global Positioning System (GPS). The difference from the popular coarse alignment methods is that the proposed algorithm uses GPS position loci information to form the vector observation, and does not need velocity information, which expands the application range of in-motion coarse alignment. In addition, this paper utilizes the Optimal-REQUEST algorithm to reduce the influence of random errors contained in the vector observation. The Optimal-REQUEST algorithm is an adaptive iterative updating algorithm, which can adaptively adjust the gain of the filter according to the loss function. Simulation results confirmed that the proposed algorithm can suppress the impact of random errors effectively. The pitch, roll and yaw angles calculated by the proposed algorithm were improved by 51.95%, 53.80% and 63.03% compared with the comparison algorithms.

A New Strategy to Enhance the Security of GPS Location by PGP Algorithm in Smart Containers

Dynamic navigation devices like Global Positioning Systems (GPSs) are deployed for various purposes in different areas and these devices are usually the central point of interest of various groups like hackers to exploit the data sent and received by GPS systems. The GPS data is usually manipulated using spoofing attacks. This paper proposes a robust solution to the spoofing attacks carried out to manipulate, control and modify the location sharing of smart containers. The primary focus of this paper is securing the GPS information shared by the smart containers. The location shared by the smart containers is secured by encrypting it with Pretty Good Privacy (PGP) algorithm to avoid spoofing attacks in particular. The encrypted GPS location is sent across any communication channel. The receiver side will decrypt the encrypted GPS location at the receiving end. Hence, using this method of PGP encryption will ensure the safe and secure sharing of GPS location by the smart containers. As a result, GPS security has been improved by 80%.

No evidence of uptake or propagation of reindeer CWD prions in environmentally exposed sheep

BackgroundChronic wasting disease (CWD) is a prion disease of cervids first reported in North America in the 1960s. In Europe, CWD was first diagnosed in 2016 in a wild reindeer in Norway. Detection of two more cases in the same mountain area led to the complete culling of this partially confined reindeer population of about 2400 animals. A total of 19 CWD positive animals were identified. The affected area is extensively used for the grazing of sheep during summers. There are many mineral licks intended for sheep in the area, but these have also been used by reindeer. This overlap in area use raised concerns for cross-species prion transmission between reindeer and sheep. In this study, we have used global positioning system (GPS) data from sheep and reindeer, including tracking one of the CWD positive reindeer, to investigate spatial and time-relevant overlaps between these two species. Since prions can accumulate in lymphoid follicles following oral uptake, samples of gut-associated lymphoid tissue (GALT) from 425 lambs and 78 adult sheep, which had grazed in the region during the relevant timeframe, were analyzed for the presence of prions. The recto-anal mucosa associated lymphoid tissue (RAMALT) from all the animals were examined by histology, immunohistochemistry (IHC) and enzyme-linked immunosorbent assay (ELISA), and the ileal Peyer's patch (IPP) from a subsample of 37 lambs were examined by histology and IHC, for the detection of prions.ResultsGPS data showed an overlap in area use between the infected reindeer herd and the sheep. In addition, the GPS positions of an infected reindeer and some of the sampled sheep showed temporospatial overlap. No prions were detected in the GALT of the investigated sheep even though the mean lymphoid follicle number in RAMALT and IPP samples were high.ConclusionThe absence of prions in the GALT of sheep that have shared pasture with CWD-infected reindeer, may suggest that transmission of this novel CWD strain to sheep does not easily occur under the conditions found in these mountains. We document that the lymphoid follicle rich RAMALT could be a useful tool to screen for prions in sheep.

DEVELOPMENT OF A BUS TRACKING AND MONITORING DEVICE USING ARDUINO NODE MICROCONTROLLER

Since the opening of Universiti Teknologi MARA Shah Alam Campus (UiTM-SAC), the university has accommodated its students by providing free bus transportation around the campus. The buses are operated based on a specific time schedule. However, students often have to wait a long time for buses because the buses do not usually arrive on schedule. In addition, the bus schedule is manually controlled by an officer, which takes time, and the data can easily be lost. Hence, the goal of this research is to develop a bus tracking and monitoring system for the UiTM-SAC. Arduino node microcontroller unit and global positioning system (GPS) sensors were used to send and receive GPS location information. The data retrieved from these sensors were displayed on an organic light-emitting diode and stored in a web-based software spreadsheet. For the experimental test, only one bus was used for collecting and analysing data. Data were immediately presented on the user interface. The results indicate that the system was able to track and monitor the bus by providing the bus’s latitude, longitude and speed. The results also revealed some key factors that affect the time required for a bus to complete a route based on users’ demands at that time. The difference in demand was 76.2%, as most students use the UiTM bus service in the morning than in the evening. In conclusion, by using the proposed bus campus tracking and monitoring system, users can easily find the exact location of buses running at the UiTM-SAC

Linking microhabitat selection, range size, reproductive state, and behavioral state in greater sage‐grouse

AbstractA female's reproductive status influences her behavior which affects habitat selection and range size; however, reproduction and behavior are generally unaccounted for in habitat selection studies. Range size, daily activity, and habitat selection between reproductive states have rarely been investigated in a connected manner. We focused on brood‐rearing and broodless (i.e., females without young) greater sage‐grouse (Centrocercus urophasianus). Our objectives were as follows: 1) identify differences between reproductive state (females with broods 0–2 weeks, broods 3–5 weeks, and broodless females) and behavioral state (foraging, day roosting, and night roosting) in microhabitat selection, 2) evaluate daily activity for brood‐rearing and broodless females, and 3) contrast daily and seasonal range sizes for each reproductive state. We collected Global Positioning System location and accelerometer data every 5 min from female sage‐grouse in Carbon County, Montana, and Park County, Wyoming, USA, in 2018–2019. We sampled microhabitat for 36 females at 276 bird‐use and random plots, estimated ranges for 38 females, and measured activity for 43 females. Females with broods 0–2 weeks selected against visual obstruction and for perennial grasses at night roosts, females with broods 3–5 weeks selected for visual obstruction when foraging and against visual obstruction and annual grasses but for sagebrush cover at night roosts; however, broodless females showed no selection. Patterns of daily activity differed between females with broods 0–2 weeks and broodless females; females with broods 3–5 weeks showed an intermediate pattern. Females with broods 0–2 weeks had the smallest daily (0.027 km2) and seasonal (0.21 km2) ranges compared with females with broods 3–5 weeks (daily = 0.038 km2, seasonal = 0.36 km2) and broodless females (daily = 0.035 km2, seasonal = 0.44 km2). Our results indicated the importance of considering reproductive and behavioral state and accounting for habitats and space required by all individuals in conservation and management decisions.

Map Matching for the public transport network in Xalapa City / Map Matching para a rede de transportes públicos na Cidade de Xalapa

In Xalapa, Veracruz, Mexico, there was not a correct description of the more than 100 public transport bus routes that existed, for which a collective event was held to collect Global Positioning System locations. The trajectories obtained were not adjusted to the layout of the city's public road network, due to measurement errors caused by the variety of devices used for tracking. To recover the correct trajectories, a Map Matching algorithm was used based on the optimization of paths in graphs whose nodes belong to the public roads of the city. This work presents the description of the data collection methodology and the construction of the graphs for the implementation of the algorithm that finally recovered the real routes.

Dependence of epoch-wise two-way nested ANOVA estimates of variances of unmodeled effects present in relative GPS positioning on satellite elevation cutoff angle and PDOP mask

Impact of satellite elevation cutoff angle and position dilution of precision (PDOP) mask change on epoch-wise variance components of unmodeled effects that accompany relative Global Positioning System (GPS) positioning is presented herein. Data used for this study refer to the winter and summer periods of the years with minimal (2008) and maximal (2013) solar activity. These data were collected every 30 s in static mode, at two permanent GPS stations located in Montenegro, establishing a medium-distance (116-km-long) baseline with a height difference of approximately 760 m between its endpoints. The study showed that changing satellite elevation cutoff angle, with a fixed PDOP mask, affects epoch-wise two-way nested ANOVA estimates of variances related to the ‘far-field’ multipath (considered as the nested factor herein) and the combined unmodeled effect of tropospheric and ionospheric refraction (considered as the nesting factor herein). However, changing of PDOP mask, with a fixed satellite elevation cutoff angle, doesn't affect epoch-wise two-way nested ANOVA estimate of variance of the combined unmodeled effect of tropospheric and ionospheric refraction, but, generally, affects the estimate of variance of the ‘far-field’ multipath (possibly mixed with a part of a ‘shorter-term’ ionospheric refraction), which is especially pronounced for the summer period. It should also be noted that there is a significant influence of satellite elevation cutoff angle change on both epoch-wise horizontal and vertical position accuracy, only for the summer period, especially in the presence of maximal solar activity, while there is no significant impact of PDOP mask change on epoch-wise positional accuracy.

Connected Preceding Vehicle Identification for Enabling Cooperative Automated Driving in Mixed Traffic

To enable the safe and fast formation of connected automated vehicle (CAV) platoons in real-world traffic, a preceding vehicle identification system for mixed traffic (PVIS-mixed) is proposed. PVIS-mixed utilizes the vehicle’s radar measurements and global positioning system (GPS) measurements reported by surrounding connected vehicles to find the communication identity of the preceding vehicle. The design of PVIS-mixed is based on three goals: a low probability of making a wrong identification, a low probability of missing the connected preceding vehicle, and short time consumption of the identification procedure. The proposed PVIS-mixed is evaluated in highway traffic simulated by real vehicle trajectory data from the Next Generation Simulation (NGSIM) program. Evaluation results showed that the performance of PVIS-mixed is not related to the adoption rate of connected vehicles, and 1 m is found to be the required relative positioning accuracy to make 99th percentile time consumption <10 s. It was observed that the multipath bias of GPS positioning could affect the usability of CAV platooning. The possible solutions are then discussed as future work.

Deep Learning-Enabled Fusion to Bridge GPS Outages for INS/GPS Integrated Navigation

The low cost inertial navigation system (INS) suffers from bias and measurement noise, which would result in poor navigation accuracy during global positioning system (GPS) outages. Aiming to bridge GPS outages duration and enhance the navigation performance, a deep learning network architecture named GPS/INS neural network (GI-NN) is proposed in this paper to assist the INS. The GI-NN combines a convolutional neural network and a gated recurrent unit neural network to extract spatial features from inertial measurement unit (IMU) signals and track their temporal characteristics. The relationship among the attitude, specific force, angular rate and the GPS position increment is modelled, while the current and previous IMU data are used to estimate the dynamics of the vehicle by GI-NN. Numerical simulations, real field tests and public data tests are performed to evaluate the effectiveness of the proposed algorithm. Compared with the traditional machine learning algorithms, the results illustrate that the proposed method can provide more accurate and reliable navigation solutions in GPS denied environments.

Hot-spots of HIV infection in Cameroon: a spatial analysis based on Demographic and Health Surveys data

BackgroundThe Human Immunodeficiency Virus(HIV) infection prevalence in Cameroon has decreased from 5.28% in 2004 to 2.8% in 2018. However, this decrease in prevalence does not show disparities especially in terms of spatial or geographical pattern. Efficient control and fight against HIV infection may require targeting hotspot areas. This study aims at presenting a cartography of HIV infection situation in Cameroon using the 2004, 2011 and 2018 Demographic and Health Survey data, and investigating whether there exist spatial patterns of the disease, may help to detect hot-spots.MethodsHIV biomarkers data and Global Positioning System (GPS) location data were obtained from the Cameroon 2004, 2011, and 2018 Demographic and Health Survey (DHS) after an approved request from the MEASURES Demographic and Health Survey Program. HIV prevalence was estimated for each sampled area. The Moran’s I (MI) test was used to assess spatial autocorrelation. Spatial interpolation was further performed to estimate the prevalence in all surface points. Hot-spots were identified based on Getis–Ord (Gi*) spatial statistics. Data analyses were done in the R software(version 4.1.2), while Arcgis Pro software tools’ were used for all spatial analyses.ResultsGenerally, spatial autocorrelation of HIV infection in Cameroon was observed across the three time periods of 2004 (MI=0.84, p-value < 0.001), 2011 (MI=0.80, p-value < 0.001) and 2018 (MI=0.87, p-value < 0.001). Subdivisions in which one could find persistent hot-spots for at least two periods including the last period 2018 included: Mbéré, Lom et Djerem, Kadey, Boumba et Ngoko, Haute Sanaga, Nyong et Mfoumou, Nyong et So’o Haut Nyong, Dja et Lobo, Mvila, Vallée du Ntem, Océan, Nyong et Kellé, Sanaga Maritime, Menchum, Dounga Mantung, Boyo, Mezam and Momo. However, Faro et Déo emerged only in 2018 as a subdivision with HIV infection hot-spots.ConclusionDespite the decrease in HIV epidemiology in Cameroon, this study has shown that there are spatial patterns for HIV infection in Cameroon and possible hot-spots have been identified. In its effort to eliminate HIV infection by 2030 in Cameroon, the public health policies may consider these detected HIV hot-spots, while maintaining effective control in other parts of the country.

Estimation of GPS transmitter antenna phase center offsets by integrating space-based GPS observations

The deviations of the microwave signal transmitting point of Global Navigation Satellite Systems (GNSS) satellites with respect to the corresponding center-of-mass were and still are significant bias sources for GNSS-based terrestrial reference frames (TRF). Satellite phase center offsets (PCOs) and variations (PVs) are usually derived from GNSS observations from the tracking network of the International GNSS Service (IGS). Because of the strong correlation between the scale of the TRF and the satellite PCOs in the z-direction (z-PCOs), a no-net-scale (NNT) condition relative to, for instance, the International Terrestrial Reference Frame (ITRF) is commonly applied. One approach for estimating transmitter phase centers without constraining the scale is to consider space-based GNSS observations. Within this study, we estimate the satellite PCOs of the Global Positioning System (GPS) based on zero-difference ionosphere-free observations from six low Earth orbiters (LEOs) and ground networks with different numbers of stations. The six LEOs are different in their orbits, GPS receiver equipment, and tracking characteristics. We jointly estimate orbits, station coordinates, and GPS satellite PCOs in an integrated processing. The horizontal offsets are shown to significantly benefit from the LEOs onboard observations by reducing the correlation between these offsets and the GPS satellite orbit and attitude. Without applying a no-net-scale condition to the ground network, the GPS z-PCOs are estimated. By adding six LEOs, the correlation coefficients between the GPS z-PCOs and the scale is reduced significantly (about from 0.85 to 0.3), consequently, the precision of estimation is improved. When including the six LEOs, the GPS z-PCOs estimated without applying NNS are very stable. The estimated GPS z-PCOs have a −231 mm difference in average to the values in igs14_2134.atx and the corresponding scale to IGS14 reference frame is +1.89 part per billion. The estimated GPS z-PCOs agree with previous studies based on Swarm satellites and Galileo. The improvement due to different numbers of LEOs and the impact of LEO z-PCO errors on the estimation are discussed.

Study on Estimation of Traveling Trajectory Using the Recording Data in the Event Data Recorder

&lt;div class="section abstract"&gt;&lt;div class="htmlview paragraph"&gt;In order to investigate traffic accidents and determine their causes, first it is necessary to clarify the circumstances in which they occurred. The traveling trajectory of the vehicle(s) involved prior to the collision is an important part of such clarification. In this study, we conducted experiments on a vehicle with an event data recorder (EDR) and examined its pre-collision trajectory estimated from data recorded by EDR, aiming to obtain such trajectories based on quantitative data recorded by EDRs. In the experiment, the test vehicle with an EDR had also a high-precision measuring system onboard that determined the vehicle’s position by a global positioning system (GPS) and measured vehicle behavior. The vehicle was driven on a test course, with the EDR and the measuring system recording their data simultaneously. The vehicle speed and yaw rate data recorded by the EDR were integrated to get an estimated trajectory of the vehicle. The comparison of the EDR-based traveling trajectory with the GPS positioning results revealed generally similar results when the vehicle behavior changed slowly (rounding curves, etc.). When the vehicle behavior changed sharply (zipping through a slalom, etc.), the difference between the EDR-based traveling trajectory and the GPS positioning results was larger than when it changed slowly. When the vehicle behavior changed sharply, the EDR-based traveling trajectory could not be fully reproduced because the sampling frequency of the EDR-based vehicle speed and yaw rate was lower. The results of this experiment suggest that the traveling trajectory can be estimated from the EDR-based vehicle speed and yaw rate if the vehicle behavior changes slowly. The results also indicated that, to get the traveling trajectory while the vehicle behavior keeps changing rapidly, we need to make the EDR sampling frequency higher than the current ones.&lt;/div&gt;&lt;/div&gt;

Multi‐model application informs prey composition of mountain lions Puma concolor

Global positioning system (GPS) receivers allow researchers to collect location data that provide information about fine-scale animal movements. For large carnivores, these data are routinely processed to identify clusters of GPS locations which are investigated to validate feeding sites, estimate prey species composition and model the likelihood of predation events based on characteristics of GPS location data within clusters. Although developing predation models entails a high level of field effort, researchers are apprehensive in applying system-specific models to other systems both spatially and temporally. Our objectives were to apply and compare multiple predation models to predict and identify feeding events outside of the geographic areas where models were developed. Using our multi-model approach, we identified feeding sites and estimated kill rates and prey composition of mountain lions Puma concolor in southwest Wyoming, USA from 2017 to 2019. Our approach increased our field efficiency by reducing potential field site investigations by 63%. We provide results of estimated diet composition in our study area where mountain lion prey included relatively high proportions of pronghorn (12.3%) and smaller mammals, particularly coyotes (7.6%). We also provide a comparison of the predation models developed across unique ecoregions of North America, and how they performed when applied to our area. We believe a similar approach could be adopted for other large carnivore populations where multiple models have been developed to characterize feeding events.

Testing Patch, Helix and Vertical Dipole GPS Antennas with without Choke Ring Frame

Abstract: The antenna is the connecting part between Global Positioning System (GPS) satellite and receiver, and it works on transferring the satellite signal propagation to the receiver with minimum interruption. This is beside the main role that GPS antenna can play for accurate and precise positioning. High quality GPS antennas have high gain, systematic radiation pattern, Right Hand Circular Polarization (RHCP), and low directivity. Multipath error is a principal error source connected with GPS positioning and it can be mitigated using better antenna design. GPS antennas tend to be provided with choke ring frame for protection from the reflected RHCP electromagnetic waves. In this paper, the performance of three different types of GPS antenna, namely: Microstrip Patch Antenna (MPA), Helix antenna (HA), and Vertical Dipole antenna (VDA), with and without choke ring frame, has been investigated using single frequency GPS receiver. The antennas have been examined under the same GPS environment, including satellites constellation, geometry, and surroundings, with different heights from the ground reflector surface for multipath evaluation. Short base-line kinematic differential code GPS (DGPS) technique has been used for removing and mitigating the main GPS error sources and focusing on multipath effect. Satellite residuals and the quality of the obtained positioning have been considered for evaluating the performance of each antenna. The results have reflected the ability of choke ring frames to improve the performance of the three GPS antennas with different rates in multipath areas, and illustrate the advantages and limitations of each antenna. Keywords: Micro-strip, Patch, Helix, Vertical Dipole, GPS, Choke Ring Antenna, Multipath.

The Advantages and Limitations of Low-Cost Single Frequency GPS/MEMS-Based INS Integration

Global Positioning System (GPS) provides a method for directly obtaining instantaneous position and velocity estimates using satellites-based passive range measurements. GPS is a whole day, all-weather, passive, satellite positioning system. Inertial Navigation System (INS) is a navigation aid system that uses a computer and Inertial Measurement Unite (IMU). IMU includes motion sensors and rotation sensors to continuously calculate relative position, orientation, and velocity. The integration of GPS/INS can help to overcome the limitations of the two systems providing integrated system better than either on a stand-alone basis. The integration of low-cost INS with dual frequency GPS has been widely studied and the same for the integration of tactical grid INS with low-cost GPS. However, during the last a few years, a number of low-cost GPS\low-cost INS integrated systems have been introduced and become popular in various engineering applications. However, reliable investigations into the advantages, limitations and quality of such integration level are still needed and more efforts are required, which will be the focus of this paper. The methodology followed in this paper for evaluating the integration of low-cost GPS/INS sensors depends on evaluating the two sensors individually and comparing the results with the integrated system. The results show that low-cost single frequency GPS receivers are able to provide a comparable accuracy level in both static and kinematic carrier phase differential GPS (DGPS). As for low-cost Micro-Electro-Mechanical System (MEMS)-based IMU, the accelerometers have provided instability comparing to gyros. The performance of gyros can be improved based on modelling the nearly-linear behaviour of the gyro drift. Tests show that the integration of low-cost GPS sensors with MEMS-based INS degrades the quality of gyro measurements and may not add any improvements to the quality of the individual GPS positioning.

GPS data Mining at Signalized Intersections for Congestion Charging.

Nowadays more private car trips have caused worse congestion due to the Covid-19 pandemic in many cities. Congestion charging is one of the taxes that is levied on vehicle owners to reduce urban traffic congestion. One of the most important reasons congestion charging is not accepted by the public is the high cost. Monitoring the state of traffic congestion in real time requires a lot of expensive installations. The purpose of this paper is to make congestion charging more accurate and acceptable using artificial intelligent algorithm. Massive real-time Global Positioning System (GPS) data provides new data for road congestion charging. The queuing length at intersections is an important measurement for the degree of traffic congestion, and it is also the basis for road congestion pricing. GPS positioning cannot provide sufficient position accuracy for lane identification of vehicles. In this study, a comprehensive model consisting of a real-time lane identification model and a real-time queue length estimation model is developed based on the traffic shockwave theory using GPS data. The comprehensive model can identify the lane where the queuing vehicle is located and estimate the real-time queue length of the lane. The proposed models were evaluated using field-collected data in Guangzhou, China. The testing results show that the proposed comprehensive model can identify lanes and estimate queue lengths with satisfactory accuracy. The model proposed in this paper provides real-time data for road dynamic pricing in a cost-effective way, which can promote the implementation of congestion charging in cities.

Assessing the Kinematic GPS Positioning Performance Under the Effect of Strong Ionospheric Disturbance Over China and Adjacent Areas During the Magnetic Storm

AbstractThe 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.