GPS Technology for Semi-Aquatic Turtle Research

Global Positioning System (GPS) units in telemetry collars provide an unbiased and precise estimate of animal locations. Under ideal conditions at least 50% of locations are expected to be within 40 m in uncorrected mode GPS, and within 5 m in differential mode GPS. When the collar was placed under open sky, most locations were 3-dimensional locations that could be differentially corrected. Under hardwood canopies with leaves on, the frequency of 3-dimensional locations decreased, the frequencies of failed location attempts and 2-dimensional locations increased, and the precision of GPS locations decreased. We compared the precision of each GPS mode by calculating uncorrected mode and differential mode locations from the same pseudo-range and ephemeris data. We varied the number of satellites used in the location solution to simulate the effect of decreased satellite acquisition due to canopy cover on precision of locations. Precision of locations increased if signals from >4 satellites were used to calculate the location in uncorrected mode and in differential mode. We found that 2-dimensional locations were almost as precise as 3-dimensional positions if the altitude of the GPS unit was known. If the altitude used to calculate a 2-dimensional location was within 50 m of the actual collar altitude, the precision of 2-dimensional differential mode locations was better than 3-dimensional uncorrected mode locations. If the error in altitude was 100 or 150 m, then 50% of 2-dimensional differential mode locations were within 70 m and 95% were within 185 m of the true location. We used GPS locations from collars placed in different cover types and on free-ranging moose (Alces alces) to determine the effect of season, time of day, rainfall, and cover type on GPS performance. On free-ranging moose the collar GPS unit found ≥4 satellites on 52% of location attempts, >50% of locations were 3-dimensional, and >24% of locations were 2-dimensional. Precise tracking of individual animals in all weather throughout the year is possible with GPS telemetry.

this study developed and tested algorithms to identify outdoor walking trips from portable global positioning system (GPS) units in free-living conditions. the study included a calibration and a validation phase. For the calibration phase, we determined the best algorithm from 35 person-days of data. Measures of agreement regarding the daily number and duration of diary-reported and GPS-identified trips were used. In the validation phase, the best algorithm was applied to an additional and separate 136 person-days of diary and GPS data. the preferred algorithm in the calibration phase resulted in 90% of trips identified from the GPS data being found in the diary, whereas 81% of trips reported in the diary being found in the GPS data. The preferred algorithm used 1) a maximum 3-min gap between points to define a trip, 2) at least 5 min or more of continuous GPS points, 3) a speed range between 2 and 8.0 km·h, 4) at least 30 m of displacement between the start and end points of a trip, and 5) merged walking trips when the time gap between trips was less than 3 min. With the validation data, substantial agreement between the GPS and the diary was achieved, with 86% of trips identified from the GPS data found in the diary and 77% of trips reported in the diary found in the GPS data. the algorithm identified free-living walking trips of more than 5 min in duration. The ability to identify outdoor walking trips from GPS data can be improved by reducing recording intervals used in the GPS units and monitoring participant compliance. Further research is desirable to determine whether concurrent wearing of an accelerometer may improve the ability to detect walking more accurately.

This paper presents an adaptive learning method for data fusion in autonomous\ndriving vehicles. The localization is based on the integration of Inertial\nMeasurement Unit (IMU) with two Real-Time Kinematic (RTK) Global Positioning\nSystem (GPS) units in an adaptive Kalman filter (KF). The observability\nanalysis reveals that $i$) integration of a single GPS with IMU does not\nconstitute an observable system; $ii$) integration of two GPS units with IMU\nresults in a locally observable system provided that the line connecting two\nGPS antennas is not parallel with the vector of the measured acceleration,\ni.e., the sum of inertial and gravitational accelerations. The latter case\nmakes it possible to compensate for the error in the estimated orientation due\nto gyro drift and its bias without needing additional instruments for absolute\norientation measurements, e.g., a magnetic compass. Moreover, in order to cope\nwith the fact that GPS systems sometimes lose their signal and receive\ninaccurate position data, the self-tuning filter estimates the covariance\nmatrix associated with the GPS measurement noise. This allows the KF to\nincorporate GPS measurements in the data fusion process heavily only when the\ninformation received by GPS becomes reliably available.\n

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.

Accurate, reliable, and robust global positioning system (GPS) localization is desirable for many navigation applications. Unfortunately, it is challenging for a single GPS receiver to always provide accurate positioning solutions. In urban environments, intermittent signal availability leads to degraded GPS signal tracking and position estimation of the single GPS receiver. In addition, equipment malfunction of the single GPS receiver results in inaccurate navigation solutions. This paper presents a deeply coupled multireceiver vector tracking (MRVT) architecture that improves the reliability and robustness of GPS signal tracking and position estimation. MRVT jointly tracks GPS signals received by multiple GPS receivers, mitigating GPS signal tracking disruptions, improving the reliability of GPS localization in periods of intermittent signal availability. In addition, the MRVT receiver is more robust to equipment malfunctions than the single GPS receiver. We implemented an MRVT receiver using commercial radio frequency front ends and our PyGNSS software. We experimentally validated the reliability of our MRVT receiver in periods of intermittent GPS availability experienced in downtown San Francisco. Our MRVT receiver exhibited consistent GPS signal tracking and position estimation as compared to vector tracking. In addition, we experimentally validated the robustness of our MRVT receiver to the failure of a single GPS receiver.

In this paper, an Adaptive Neuro-Fuzzy Inference System (ANFIS) is proposed for low-cost navigation of ground vehicles. The ANFIS structure is proposed for fusing the measurements of the Global Positioning System (GPS) and inertial measurement unit (IMU). Low-cost GPS receivers provide the position and velocity of the vehicle at a lower rate than the IMU sampled vehicle dynamics. Additionally, the GPS measurements might be missed/delayed due to receiver's inability to lock on the signal or due to obstruction from neighboring vehicle's or infrastructures. Therefore, the variable delay between the IMU and GPS signals is selected as an additional input to the ANFIS architecture. The performance of the proposed ANFIS architecture is demonstrated through experimental results. The instrumentation system used in this experiment consists of a microcontroller system, a GPS receiver, and an IMU.

Due to range-wide population declines, wood turtles (Glyptemys insculpta) are under review for federal listing under the United States Endangered Species Act. Understanding how habitat associations and environmental conditions influence population dynamics and spatiotemporal activity patterns is fundamental for designing effective management strategies. Previous work on wood turtle abundance-habitat relationships focused on broad-scale habitat relationships in northeastern North America. However, regional differences in climate, habitat conditions, and land use patterns limit their applicability to much of the wood turtle’s Upper Midwest distribution. Much of our understanding of wood turtle activity patterns is based on radiotelemetry studies, which are biased towards daytime hours and typically have relatively low temporal resolution. There is a general understanding of wood turtle activity patterns during the spring, but patterns become unclear and inconsistent after the nesting period. Many studies report that wood turtles become primarily terrestrial during the summer months, but few studies have investigated nighttime habitat use during the summer months. Thus, further research is required to better understand wood turtle population dynamics and spatiotemporal activity patterns in the Upper Midwest region. In Chapter 1, I provide information on the ecology and behavior of wood turtles, their current conservation status, and threats affecting populations. I discuss the importance of ii vegetation structure in wildlife studies, emphasizing how it affects microclimate. I also provide background information on Light Detection and Ranging (LiDAR) technology and its application to quantifying vegetation structure. Lastly, I state the goals of this thesis research and give a summary of the chapters. In Chapter 2, we conducted wood turtle population surveys across northern Wisconsin and northeastern Minnesota and gathered numerous aquatic and terrestrial habitat data, including measures of 3-dimensional vegetation structure derived from LiDAR. We created a hierarchical N-mixture model to estimate adult abundance and used a multistage model selection approach to rank habitat covariates. We found aquatic and terrestrial habitat characteristics to be strong predictors of abundance, particularly stream velocity, stream width, mean return height, and vertical coefficient of variation (CV) of height. The most supported model suggested that abundance was high at sites containing comparatively narrow streams with moderate velocities, low mean return heights, and extremes in vertical CV of height. In Chapter 3, we characterized the daily movement patterns of wood turtles between aquatic and terrestrial habitats throughout the active period in northeastern Minnesota. We modeled the influence of temporal, demographic, and environmental covariates using generalized linear mixed

An essential part of satellite communication is the orientation of the antenna, which can be difficult to ascertain on mobile platforms such as ships. While equipment to measure orientation accurately at sea exists, current solutions are expensive. This paper describes work toward an antenna orientation system using low-cost Global Position System (GPS) receivers. We investigated two methods: one using the spatial difference between multiple GPS units at the vertices of a polygon, and the other using the differences over time measured using a single GPS unit. We tested the antenna orientation system with the Omnispace F2 satellite at the US Electrodynamics, Inc. (USEI) teleport in Brewster, WA. Although non-correlated systematic errors in the GPS receivers made the multiple-GPS system impractical, the time-differential method was able to maintain a satellite lock for the majority of a simple test course. The reliability of this solution may be further improved using a gain-based correction algorithm.

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.

This paper presents an alternate recursive state estimator of moving horizon estimation as compared to the conventional state estimator of Kalman filtering. The state estimator estimates the position set, velocity set and attitude data of the dynamic aerial vehicle. In the first scenario, the available data for processing are the measurement set from accelerometers assembly, gyroscope triad, and global positioning system (GPS) from the low cost inertial measuring unit (IMU). The GPS position and GPS velocity measurements are the aiding source as well the comparison reference of the computed solution of the dynamic aerial vehicle (DAV). In the second scenario receding window discrete time state estimator, extended for non-linear vehicle navigation application is implemented using the deterministic cost function of least squares, for integrated filtering. The receding data window approach uses the past measurements samples over the horizon as the tuning parameter of the moving horizon state estimator. The moving horizon state estimator is evaluated offline in the numerical experiment including the flight testing data collected. The flight test on a small aerial vehicle with all the sensors, GPS receiver, power systems instrumented onboard is considered for this paper. Matlab platform is used to simulate the noise environment and implementing the algorithms. This paper designed algorithm results reveals that proposed moving horizon estimator is faster in convergence in the presence of large initialization errors, linearization errors and outliers as compared to the reference filter i.e. EKF tested online and offline.

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.

When we examine the impacts of space weather on society, do we really understand the risks? Can past experiences reliably predict what will happen in the future? As the complexity of technology increases, there is the potential for it to become more fragile, allowing for a single point of failure to bring down the entire system. Take the Global Positioning System (GPS) as an example. GPS positioning, navigation, and timing have become an integral part of daily life, supporting transportation and communications systems vital to the aviation, merchant marine, cargo, cellular phone, surveying, and oil exploration industries. Everyday activities such as banking, mobile phone operations, and even the control of power grids are facilitated by the accurate timing provided by GPS. Understanding the risks of space weather to GPS and the many economic sectors reliant upon it, as well as how to build resilience, was the focus of a policy workshop organized by the American Meteorological Society (AMS) and held on 13–14 October 2010 in Washington, D. C. The workshop brought together a select group of policy makers, space weather scientists, and GPS experts and users. Arif Alikhan, assistant secretary for policy development in the U.S. Department of Homeland Security, kicked off the meeting by stressing that authorities should see GPS and resilience through an all-hazards lens rather than plan for each emergency scenario on a case-by-case basis. Whether a GPS signal error or disruption is caused by a solar storm, an intentional jammer, or some other source, government and industries need to plan to respond to the incident and restore capability as quickly as possible, although, Alikhan remarked, “The number of potential scenarios is infinite, and we have neither the time nor resources to plan against them.” Alikhan suggested that risk managers conceptualize the scope of critical assets in need of protecting through a resilience and risk analysis framework. He recommended that decision makers take an inventory of all functions provided for by their institutions“ use of GPS. Next, through risk-informed prioritization, planners can ascertain whether a backup is really needed for any services provided by GPS. “In this fiscal environment,” Alikhan said, “we will need to shrink the haystack, or size of the problem, in order to be effective.” Because the interdependencies of critical infrastructures are not fully appreciated by the public and private sectors, he stressed that a mix of governmental, commercial, and international stakeholders should develop plans and procedures to make systems more resilient. The remainder of the workshop was organized around discussions in three sessions: (1) identifying the vulnerability of GPS technologies and services to space weather, (2) identifying how this vulnerability affects users who depend on GPS, and (3) developing opportunities and policies for building resilience. In the first session, participants agreed that the vulnerability of GPS needs to be defined for different segments (e.g., satellites, signals, users). While some understanding of user needs exists, the definition of user requirements needs more clarification because space weather events will affect some technologies more than others. Also, a threat assessment would be valuable to best understand how severe the impacts might be and what mitigation options are available. With the recent news that Google™ is building self-driving robotic cars that depend on GPS, trying to capture possible future vulnerabilities is extremely challenging. During a debate on how much to stress the impact of a solar flare as massive as the 1859 Carrington event, many warned that while the public should be made aware of such a potential occurrence, it should not govern planning, since such a doomsday scenario is uncertain and expected to happen only very infrequently. When discussing in the second session how users of GPS are affected, participants discovered that communicating with GPS stakeholders and users is a challenge because many do not understand the impacts of adverse space weather. In particular, many of the service providers and end users of GPS were not in business during the previous solar maximum and therefore are not familiar with space weather hazards. To help remedy this, outreach approaches were discussed, and some participants argued that the space weather community should anticipate the needs of the users. Others instead urged the space weather community to deal only with the service providers—not end users—and ask them rather than tell them what they need. Despite this debate, there was broad agreement that space weather researchers should develop better measurements and predictions of the ionosphere. In addition, participants agreed that scintillation specifications and predictions would be useful to many users of GPS. Improved predictions would be possible by installing more dual-frequency stations and scintillation monitors, they noted. The workshop concluded with a discussion of policy options for building resilience. Participants debated what measures could be taken, such as developing new policies, investing in research and development, changing industry practices, and public and private sector collaboration. Scott Pace, director of George Washington University“s Space Policy Institute, stressed in his presentation that stakeholders and disaster planners should focus on three aspects: prediction, detection, and mitigation. Better space physics/heliophysics science is needed, and it was recommended that this be a top priority for the Solar and Space Physics decadal survey, which sets future nationwide research targets and is currently under review by the U.S. National Research Council. Findings and recommendations from the workshop will be published in a report by AMS. The results will be widely distributed to various stakeholders, including policy makers, GPS service providers, federal agencies, research communities, and international organizations. Genene Fisher is a senior policy fellow in the American Meteorological Society's Policy Program. E-mail: [email protected]

Information communication technology related vehicle services need to support location and the transmission of communication and traffic information between vehicles, or between vehicles and infrastructure. In particular, the technology for the measurement of the accurate location of a vehicle is dependent on location-determination technology like Global Positioning System, and this technology is very important for vehicle driving and location services. If, however, a vehicle is in a Global Positioning System radio-shadow area, neither a Global Positioning System nor a Differential Global Positioning System can accurately measure the corresponding location because of a high error rate caused by the shadowing intervention. Even an Inertial Measurement Unit could provide inaccurate location data due to sensor drift faults around corners and traffic-road speed dumps. Vehicles, therefore, need an absolute location to prevent the provision of inaccurate vehicle-location data that is due to radio-shadow areas and relational Inertial Measurement Unit positions. To achieve this, we assume that vehicle-to-infrastructure communication is possible between a vehicle and roadside unit in Vehicular Ad hoc Networks. We used iBeacon at the roadside unit and revised its Universally Unique Identifier so that it generates absolute Global Positioning System location data; that is, moving vehicles can receive absolute Global Positioning System data from the roadside unit-based iBeacon. We compared the proposed method with current Global Positioning System and Inertial Measurement Unit systems for the following two cases: one with a radio-shadow area and one without. We proved that the proposed method generates location data that are more accurate than those of the other methods.

Effects of physical correlations on long-distance GPS positioning and zenith tropospheric delay estimates

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.