PRISM :: Browsing by Author "O'Keefe, Kyle"

Browsing by Author "O'Keefe, Kyle"

Now showing 1 - 20 of 49

Open Access
3-D Cadastral Boundary Relationship Classification Algorithms using Conformal Geometric Algebra
(2021-04-26) Pullano, Dillon; Barry, Michael; Wang, Xin; O'Keefe, Kyle; Detchev, Ivan; Barry, Michael; Wang, Xin; Rangelova, Elena
As urban centers continue to grow and develop, there is an increasing need for institutions to be able to digitally model and perform relationship analysis on 3-D cadastral boundary data. 3-D boundary analysis can be performed through visual inspection of survey plan drawings, but this often requires professional expertise such as a land surveyor or lawyer. This study examined the development, testing, and application of methodological processes and algorithms that were designed to classify various geometrical and topological relationships between the boundary components of two 3-D cadastral units to solve cadastral boundary problems. It applied established mathematical theory using Conformal Geometric Algebra objects and operational techniques, in combination with various 3-D point-point distance evaluations and geometric concepts to the classification of relationships between 3-D cadastral boundaries. A literature search suggests that the theory and methodology as it was applied in this study have not been used to classify topological relationships between 3-D cadastral boundaries elsewhere. Six sets of data flow processing algorithms were developed to determine the relationship classifications between boundary component pair sets that exist between two 3-D cadastral units. The classification processes were first validated using seven simulated experimental testing datasets, each consisting of two cube-like units. The classification processes were then applied to a cadastral dataset that was derived from a condominium survey plan registered in Alberta, Canada. This showed how the methods developed here can be applied to solving a practical 3-D cadastral boundary problem example in the land surveying field, specifically towards validating a shared boundary between two adjacent condominium units as is intended on the plan before survey plan registration. Results from the experimental datasets support the methods that were proposed to classify 53 distinct types of topological relationships between 3-D boundary component pair sets. While this type of boundary relationship analysis can be done through visual inspection of survey plans, the methods developed here are more mathematically rigorous. These processes could be leveraged by land surveyors and land administration professionals when analyzing 3-D survey plan boundaries.
Open Access
3D Building Model-Assisted Snapshot GNSS Positioning Method
(2017) Kumar, Rakesh; Petovello, Mark; Petovello, Mark; Lachapelle, Gérard; O'Keefe, Kyle; Fapojuwo, Abraham
Global Navigation Satellite Systems (GNSS) have proven to be a viable and reliable solution in interference-free environments and in presence of Line-of-Sight (LOS) signals only. However, in urban canyons, multipath signals directly affect the pseudorange measurements resulting in degraded positioning performance of traditional GNSS receivers. Moreover, traditional GNSS receivers cannot distinguish between non-LOS (NLOS) and LOS signals, resulting in even worse performance if the receiver tracks NLOS-only signal. Hence, NLOS and multipath signals remains a dominant source of error in satellite-based navigation. Most of the existing research has focused on identifying and rejecting NLOS measurements. However, little research has used NLOS signals constructively. In this regard, this research uses snapshots of GNSS data in order to estimate position, utilizing all NLOS signals constructively with the help of a 3D Building Model (3DBM). Using a 3DBM and a ray-tracing algorithm, the number of reception paths and the corresponding path delays of reflected signals is predicted across a grid of candidate positions. These predictions are then used to compute least-squares fit to the GNSS receiver’s correlator outputs and the position with smallest residuals is selected as the position estimate. This approach is termed Signal Delay Matching (SDM) and yields a solution that is nearly unaffected by traditional GNSS error sources, and has capability of providing a position solution using a single satellite only. The use of snapshots of data mean the receiver need not perform tracking operations, thus making it easier to implement and power efficient. The feasibility and performance of the algorithm was tested using data collected in downtown Calgary, Canada, where buildings reach heights of over 200 m. Contrary to traditional approaches, results for the proposed method show that positioning error decreases as sky-visibility decreases. For sky-visibility below 20%, the median error was found to be just over 3 m. Compared to two pseudorange-based receivers, the proposed method yields RMS errors improvements of 22% to 48% in the horizontal plane.
Open Access
A Below-Rooftop Dense Urban Wireless Channel Model Based on Empirical Measurements
(2015-12-22) Wasson, Michael William; Messier, Geoffrey; Fapojuwo, Abraham; O'Keefe, Kyle
This thesis presents a wireless propagation channel model for the below-rooftop dense urban environment based on empirical measurements conducted in the downtown core of Calgary, Alberta. The measurements characterize a 2x1 multiple input single output channel in the 2.47 GHz band. Two communication scenarios were examined: a picocell mobile scenario consisting of a stationary base station and mobile handsets, and a point-to-point fixed-position wireless communication system consisting of two immobile wireless nodes mounted on utility poles above pedestrian traffic. Measurements were conducted with two antenna types: an omnidirectional dipole, and a polarized directional antenna. Low path-loss values measured with both omnidirectional and directional antennas suggest that buildings lining the downtown streets behave like a waveguide. Directional antennas experience substantially less small scale fading, but are more susceptible to shadowing obstructions. Directional antenna rejection measurements suggest that systems employing space-division multiplexing will experience little interference.
Open Access
A New Cooperative PPP-RTK System with Enhanced Reliability in Challenging Environments
(2023-07) Lyu, Zhitao; Gao, Yang; Wang, Ruisheng; O'Keefe, Kyle; Gao, Yang
Compared to the traditional PPP-RTK methods, cooperative PPP-RTK methods provide expandable service coverage and eliminate the need for a conventional expensive data processing center and the establishment and maintenance of a permanently deployed network of dense GNSS reference stations. However, current cooperative PPP-RTK methods suffer from some major limitations. First, they require a long initialization period before the augmentation service can be made available from the reference stations, which decreases their usability in practical applications. Second, the inter-reference station baseline ambiguity resolution (AR) and regional atmospheric model, as presented in current state-of-art PPP-RTK and network RTK (NRTK) methods, are not utilized to improve the accuracy and service coverage of the network augmentation. Third, the positioning performance of current PPP-RTK methods would be significantly degraded in challenging environments due to multipath effects, non-line-of-sight (NLOS) errors, poor satellite visibility and geometry caused by severe signal blockages. Finally, current position domain or ambiguity domain partial ambiguity resolution (PAR) methods suffer from high false alarm and miss detection, particularly in challenging environments with poor satellite geometry and observations contaminated by NLOS effect, gross errors, biases, and high observation noise. This thesis proposed a new cooperative PPP-RTK positioning system, which offers significant improvements to provide fast-initialization, scalable coverage, and decentralized real-time kinematic precise positioning with enhanced reliability in challenging environments. The system is composed of three major components. The first component is a new cooperative PPP-RTK framework in which a scalable chain of cooperative static or moving reference stations, generates single reference station-derived or reference station network-derived state-space-representation (SSR) corrections for fast ambiguity resolution at surrounding user stations with no need for a conventional expensive data processing center. The second component is a new multi-feature support vector machine (SVM) signal classifier based weight scheme for GNSS measurements to improve the kinematic GNSS positioning accuracy in urban environments. The weight scheme is based on the identification of important features in GNSS data in urban environments and intelligent classification of line-of-sight (LOS) and NLOS signals. The third component is a new PAR method based on machine learning, which employs the combination of two support vector machine (SVM) to effectively identify and exclude bias sources from PAR without relying on satellite geometry. The prototype of the new PPP-RTK system is developed and substantially tested using publically available real-time SSR products from International GNSS Service (IGS) Real-Time Service (RTS).
Open Access
Accuracy Assessment and Enhancement of TOF-based UWB RTLS and Improvement on Auto-positioning
(2021-04-06) JIN, TIAN; Sadeghpour, Farnaz; Jergeas, George; Dann, Markus; O'Keefe, Kyle
Studies in the past decades have shown Real Time Location Systems (RTLS) have great potential in reducing possible injuries and enhancing productivity. Ultra-Wide Band (UWB), among all the RTLS, has demonstrated the best suitability for construction site conditions due to its higher accuracy, lower dependency on the Line-Of-Site, less signal attenuation and multipath effect. The objective of this study is to investigate and enhance the feasibility of a TOF-based UWB RTLS on construction site applications. The three subobjectives are:1.To assess the performance of the TOF-based UWB under LOS. 2.To develop a new auto-positioning approach: (1) with high accuracy; (2) without BLE or WLAN requirements; (3) without configuration angle and height requirements; (4) without complex input requirements; and (5) has the capability to compute 3D (X, Y, and Z) locations of the anchors. 3.To assess and enhance the accuracy of the TOF-based UWB RTLS under NLOS in construction sites.Through the feasibility assessments conducted in this study, the TOF-based UWB RTLS is verified with high reliability for the performance of the tags, high static and dynamic accuracy, low time latency, and low multiple tags effect. The proposed auto-positioning methodology improved the accuracy by more than 70% and overcame the application barriers of the inherent auto-positioning. The accuracy assessment under NLOS confirmed that large bias rather than noise is induced when multi-path effect exists. Moreover, the proposed residual analysis approach improved the location estimation accuracy by more than 60%.
Open Access
Assessment of Different Sensor Configurations for Collaborative Driving in Urban Environments
(Hindawi, 2013-01-07) Petovello, Mark G.; Basnayake, Chaminda; O'Keefe, Kyle; Wei, Phil
Vehicle-to-vehicle relative navigation of a network of vehicles travelling in an urban canyon is assessed using least-squares and Kalman filtering covariance simulation techniques. Between-vehicle differential GPS is compared with differential GPS augmented with between-vehicle ultrawideband range and bearing measurements. The three measurement types are combined using both least-squares and Kalman filtering to estimate the horizontal positions of a network of vehicles travelling in the same direction on a road in a simulated urban canyon. The number of vehicles participating in the network is varied between two and nine while the severity of the urban canyon was varied from 15-to 65-degree elevation mask angles. The effect of each vehicle’s azimuth being known a priori, or unknown is assessed. The resulting relative positions in the network of vehicles are then analysed in terms of horizontal accuracy and statistical reliability of the solution. The addition of both range and bearing measurements provides protection levels on the order of 2 m at almost all times where DGPS alone only rarely has observation redundancy and often exhibits estimated accuracies worse than 200 m. Reliability is further improved when the vehicle azimuth is assumed to be known a priori.
Open Access
Automated Floor Plan and Building Model Creation for Cultural Heritage Buildings from Laser Scanner Data
(2021-06-21) Pexman, Katherine; Lichti, Derek D.; Dawson, Peter; O'Keefe, Kyle; Detchev, Ivan
This research project developed and implemented an automated modelling system to create 2D floor plans and 3D building models of heritage sites. Without building plans, it is more difficult for an historic building to receive historic designation and restoration funding. Under current practice, the creation of such physical documentation is expensive and time-consuming. Physical documentation can include as-built architectural plans, elevations, profiles and photographs, whereas historic documentation includes important documents, artefacts, and historic photographs or archives. Important heritage sites whose building plans have been lost or destroyed or become inaccurate through renovations are often left abandoned or not kept up properly because they are unable to receive the necessary support. The current modelling process involves the utilization of CAD software and a trained modeller to digitally draw a 2D floor plan, or a more complex 3D building model, overlain upon the point cloud data collected by a laser scanner. As currently applied, point cloud modelling requires inefficient manual manipulation, editing and rendering of large datasets within a CAD environment to produce floor plans and building models. This research project used statistical methods such as principal components analysis (PCA) and M-estimator sample consensus (MSAC) to automatically detect building features from a point cloud captured through a 3D terrestrial laser scan (TLS) of the building site. Two novel methods were developed in this work to help in the automation of floor plan and building model creation. The first was a novel methodology for the automated separation of storeys within a multi-level, multi-storey building. The second was a novel methodology for the automated detection of doors and windows within a point cloud using a wall-defined search space. These new methods were implemented as components in an end-to-end modelling strategy for the creation of floor plans and building models, the final output of which is written in a CAD-accessible file format. The modelling strategy showed an overall accuracy of 92.75% for the tested datasets, demonstrating the ability of the developed program to accurately produce both 2D floor plans and 3D building models of multi-level building storeys with door and window features. The development of this automated process will allow a non-geomatics expert to create floor plans and/or building models of sites with significantly less manual effort and reduced cost. This will increase the ability of heritage sites to receive historic designation, allowing them to be better preserved over time.
Embargo
Clustering-Assisted Observation Domain Optimization for GNSS Multi-Fault Detection and Mitigation
(2024-07-15) Haque, Fahimul; Dehghanian, Vahid; Fapojuwo, Abraham; Dehghanian, Vahid; Fapojuwo, Abraham; Nielsen, Jorgen; O'Keefe, Kyle; Messier, Geoffrey; Alves, Paulo
With the rise of autonomous and semi-autonomous vehicles, effective fault detection and mitigation (FDM) methods have become essential in meeting the integrity requirements for precise and reliable Global Navigation Satellite System (GNSS)-based positioning. In scenarios involving multiple faulty observations, the existing GNSS-only statistical FDM methods are ineffective or impractical due to either theoretical model limitations or high computational costs. Additionally, supervised learning-based FDM approaches introduced in recent years do not meet the existing and emerging industry requirements due to dependence on large amounts of diverse training data, the accuracy of the offline labeling process, or high computational complexity. In this dissertation, a novel GNSS multi-fault detection and mitigation method is developed that achieves a balance between computational complexity and performance. The proposed method incorporates an Expectation Maximization (EM) framework to jointly estimate an approximate maximum likelihood of states and latent model parameters in the presence of observation outliers, i.e., faults. However, the EM algorithm is known for its high computational complexity. To reduce the computational complexity of EM, an importance sampling step based on unsupervised clustering is introduced. As demonstrated by the results and analysis herein, the proposed method outperforms the existing Least-squares Residuals-based single-fault method, achieving an average improvement of up to 48% in positioning accuracy. Additionally, the computational complexity of the proposed method is an order of magnitude lower than the state-of-the-art Solution Separation method. The improved performance and the lower computational complexity of the proposed method make it a suitable candidate for integration into modern standalone real-time GNSS applications.
Open Access
Combining Multichannel RSSI and Vision with Artificial Neural Networks to Improve BLE Trilateration
(MDPI, 2022-06-07) Naghdi, Sharareh; O'Keefe, Kyle
The demands for accurate positioning and navigation applications in complex indoor environments such as emergency call positioning, fire-fighting services, and rescue operations are increasing continuously. Indoor positioning approaches apply different types of sensors to increase the accuracy of the user’s position. Among these technologies, Bluetooth Low Energy (BLE) appeared as a popular alternative due to its low cost and energy efficiency. However, BLE faces challenges related to Received Signal Strength Indicator (RSSI) fluctuations caused by human body shadowing. This work presents a method to compensate RSSI values by applying Artificial Neural Network (ANN) algorithms to RSSI measurements from three BLE advertising channels and a wearable camera as an additional source of information for the presence or absence of human obstacles. The resulting improved RSSI values are then converted into ranges using path loss models, and trilateration is applied to obtain indoor localization. The proposed artificial system provides significantly better localization solutions than fingerprinting or trilateration using uncorrected RSSI values.
Open Access
Comparing Multicarrier Ambiguity Resolution Methods for Geometry-Based GPS and Galileo Relative Positioning and Their Application to Low Earth Orbiting Satellite Attitude Determination
(Hindawi Publishing Corporation, 2009-03-08) O'Keefe, Kyle; Petovello, Mark; Cao, Wei; Lachapelle, Gérard; Guyader, Eric
This paper presents an evaluation of several GNSS multicarrier ambiguity (MCAR) resolution techniques for the purpose of attitude determination of low earth orbiting satellites (LEOs). It is based on the outcomes of the study performed by the University of Calgary and financed by the European 6th Framework Programme for Research and Development as part of the research project PROGENY. The existing MCAR literature is reviewed and eight possible variations of the general MCAR processing scheme are identified based on two possible options for the mathematical model of the float solution, two options for the estimation technique used for the float solution, and finally two possible options for the ambiguity resolution process. The two most promising methods, geometry-based filtered cascading and geometry-based filtered LAMBDA, are analysed in detail for two simulated users modelled after polar orbiting LEOs through an extensive covariance simulation. Both the proposed Galileo constellation and Galileo used in conjunction with the GPS constellation are tested and results are presented in terms of probabilities of correct ambiguity resolution and float and fixed solution baseline accuracies. The LAMBDA algorithm is shown to outperform the cascading method, particularly in the single-frequency dual-GNSS system case. Secondly, more frequencies and multiple GNSS always offer improvement, but the single-frequency dual-system case is found to have similar performance to the dual-frequency single-system case.
Open Access
Consumer GNSS Receiver Performance for Position and Trajectory Length Estimation
(2016) Norman, Laura Jane; Lachapelle, Gérard; O'Keefe, Kyle; Achari, Gopal
This research investigates the performance of handheld and wristwatch consumer grade GNSS receivers for absolute position determination, trajectory length estimation and cumulated height ascent and descent under ideal line of sight conditions and non-line of sight flat and mountainous environments. Experiments were also performed to demonstrate the capability of carrier phase positioning for the same purpose in line of sight conditions. Many receivers were tested to analyze how they react to various scenarios and what challenges and limitations arise in the process. These scenarios consisted of straight flat line of sight trajectories underneath forestry canopy on a rigorous back and forth straight trajectory segment and hiking trails in mountainous and partly forested areas.
Open Access
Cooperative V2X Relative Navigation using Tight-Integration of DGPS and V2X UWB Range and Simulated Bearing
(2015-02-25) Wang, Da; O'Keefe, Kyle
Many intelligent transportation systems applications require precise relative vehicle position. Global Navigation Satellite Systems, particularly GPS currently provide this through either absolute or differential positioning. GPS performance is limited in environments with degraded or block signals. This thesis proposes to augment differential GPS (DGPS) with range and bearing observations to surrounding vehicles and infrastructure and accomplishes this by tightly integrating DGPS, range and bearing observations in a small network of vehicles or infrastructure points. The performance of this system is assessed using real GPS, and Ultra-Wide Band (UWB) ranging radio observations and “simulated” bearing data. The integrated solution outperforms the DGPS only solution. A Vehicle-to-Infrastructure (V2I) test at a deep urban canyon intersection show sub-metre to metre level horizontal positioning accuracy with three UWB ranging radios deployed at intersection, compared to tens of metres accuracy of DGPS only. For Vehicle-to-Vehicle (V2V), the DGPS and UWB outperforms DGPS only by 10%. Systematic UWB range errors are effectively estimated if integrated with the DGPS carrier phase Real Time Kinematic (RTK) solution. As a result, the UWB ranges improves the convergence of the carrier phase RTK float solution and the time to fix ambiguities. A full-order decentralized filter with post estimation information fusion was developed for V2V cooperative navigation. The full-order decentralized estimate on each vehicle can be fused with the estimate of other vehicles to achieve the centralized equivalent estimate, even if these estimates have different nuisance error states (including UWB systematic errors and carrier phase ambiguities), by fully taking account of the correlation in the observations and state covariance the filter has, which is demonstrated using GPS data and UWB range data collected in three-vehicle V2V field tests. In other cases if some of the correlation between the nuisance error states and the position states is being ignored, the vehicle that has access to fewer observations can still also benefit from the cooperation via fusing its estimate with that of another vehicle that has better solution.
Open Access
Determining the polar cosmic ray effect on cloud microphysics and the Earth's ozone layer
(2012) Radons Beckie, Charlene; Skone, Susan; O'Keefe, Kyle
Earth's changing climate is an important topic where atmospheric ozone plays a critical role. Ozone has a direct influence on the amount and type of solar radiation received by the Earth. This study addresses how cosmic rays may influence the ozone layer by ionizing Earth's atmosphere and enhancing the growth of cloud condensation nuclei and rate of chemical reactions on polar ice cloud surfaces. This theory was largely based on the lifetime work by Lu [2010]. The region of interest was centered over the Thule, Greenland neutron monitor station. Using cosmic ray, satellite-based ISCCP and ICARE project cloud data along with TOMSOMI-SBUV and TEMIS total column ozone data, data comparisons were done. Plots of cosmic rays versus Antarctic atmospheric ozone from Lu [2009] were reproduced using regional Arctic data and extended to include years from 1983 to 2011. Comparisons to the research by Harris et al. [2010] were made by substituting ice cloud optical thickness for the cloud parameter and seasonal total column ozone for winter stratospheric ozone loss. The results of these data evaluations showed that the regional Arctic view matched very closely to Lu's work from the Antarctic. The ozone 3-point moving average case demonstrated a statistically significant correlation of -0.508. Extending the data duration exposed a cosmic ray data peak that was 14 percent larger than the two previous 11-year cycles. Ice cloud tau / ozone data comparisons did not produce the strong correlations from Harris et al. [2010]. Five years of low stratospheric temperatures and increased volumes of polar stratospheric clouds, identified by Rex et al. [2006], matched significant years of total column ozone minimums. Polar atmospheric CO2 trended along with ice cloud tau and oppositely to total column ozone, suggesting that lower stratospheric temperatures are instrumental in ozone reduction. Future work would involve using more extensive datasets, focusing on parameters such as ice water content and effective radius, or altitude specific studies concerning the stratosphere. Continued results from laboratory studies at the CERN facility may lead to a deeper understanding of cosmic ray, cloud microphysics and ozone relationships in nature.
Open Access
Development of combined gps l1/l2c acquisition and tracking methods for weak signals environments
(2009) Gernot, Cyrille; Lachapelle, Gérard; O'Keefe, Kyle
Open Access
Enhancing Wireless Received Signal Strength-based Indoor Location Systems
(2017) Li, Yuqi; Nielsen, John; Lachapelle, Gérard; Ling, Pei; Sesay, Abu; Dehghanian, Vahid; O'Keefe, Kyle
The ever-growing demand for Location Based Services has significantly boosted the research and development need for indoor positioning systems. Of various indoor positioning solutions, techniques making use of Received Signal Strength (RSS) of wireless signals of opportunity have gained extensive interest due to the ubiquitous wireless signal infrastructure and the readily available RSS measurements with standard mobile devices. However, the performance of RSS-based indoor positioning systems is highly affected by significant uncertainties in RSS due to many factors affecting wireless propagations. To enhance the performance of an RSS-based indoor positioning system, from a Bayesian filtering theory perspective, a better estimation of the a posteriori distribution of position is needed. This can be done through a better modelling of RSS measurements to mitigate uncertainties and/or incorporating prior information. This thesis specifically explores mitigating RSS uncertainties by modelling those due to human body shadowing and incorporating prior information from widely available security cameras and building maps. The characterization of RSS measurements indoors is first demonstrated using data collected in various environments. Experimental results characterize the RSS sensitivity to location and the uncertainty incurred by body shadowing effects on RSS measurements. Based on the characterization, an empirical model with a small number of parameters estimated from training data is proposed to model the RSS loss due to body shadowing. An estimator based on this model is proposed to improve positioning. Experimental results show that when the user heading is known, the positioning obviously improves. When the heading is unknown, and thus needs to be jointly estimated, the improvement becomes less apparent. This thesis then investigates the use of security cameras and building maps to enhance RSS-based positioning. An estimator based on computer vision processing is proposed to estimate user’s heading in corridors. Based on this, a camera-aided RSS system based on Kalman-filter is proposed and it is experimentally shown that a 37.5% improvement in horizontal position estimation occurs. To further incorporate building map information, a map-camera-aided RSS system based on particle filters is proposed. Experimental results indicate that the use of map constraints further bring 44.4% improvement in the across track direction.
Open Access
Evaluation of Kinematic GNSS PPP for Tropospheric Zenith Wet Delay Estimation in Mountainous Regions
(2021-08-31) Gratton, Paul Thomas; O'Keefe, Kyle; Lachapelle, Gérard; O'Keefe, Kyle; Lachapelle, Gérard; Banville, Simon; Gao, Yang
In this research, the effectiveness of kinematic zenith wet delay (ZWD) estimation using global navigation satellite systems (GNSS) precise point positioning (PPP) techniques is evaluated. The major challenges of kinematic ZWD estimation compared to static mode are (1) significant and variable GNSS signal obstruction, (2) trajectory durations of several hours compared to several days in static mode and (3) strong correlation between ZWD and height estimates. High-end and low-cost receivers are tested on vehicular highway trajectories through mountainous regions with height changes over 1000 m and varying levels of GNSS obstruction. Results are compared to static tests with open-sky conditions. Static agreement of ZWD profiles of high-end receivers was found to be at the sub-millimetre level. Agreement of low-cost receivers when using a high-grade antenna was found to be at the level of 3 mm or better. Low-cost receivers using low-cost antennas suffered ZWD biases of 3 cm due to height biases of 7-10 cm. Kinematic accuracy of ZWD profiles for high-end receivers in trajectories with minimal obstruction was found to be 5 mm, increasing to 10 mm in trajectories with more obstruction and 25 mm in very harsh obstructions. Accuracy of ZWD profiles for low-end receivers ranged from 8-20 mm in open conditions and 20-35 mm in more challenging conditions. Low-cost receivers were not tested in very harsh obstructions. Empirical ZWD models were found to agree with high-end receiver PPP-derived ZWD profiles within 15 mm or better, hence accuracy poorer than 15 mm appears ineffective.
Open Access
Four-constellation GNSS Reliability and the Estimation of Inter-system Time-offsets for Improved Performance in Challenging Signal Environments
(2013-12-13) Winit, Rasika; O'Keefe, Kyle
The new GNSS constellations such as Galileo and BeiDou being planned and launched will result in a greatly increased number of available ranging sources, hence, improvement in constellation geometry and coverage. When using signals from multiple constellations, however, the challenges are not only to maximize the benefit from the additional ranging observations but also to deal with the differences among satellite systems such as the time-offset between the constellations. Also, challenges exist when using the ranging signal in GNSS degraded environments where GNSS users potentially see a limited number of satellites from multiple GNSS constellations. This work investigates the accuracy and reliably of position solutions when using ranging signals from combined GPS, GLONASS, BeiDou and Galileo constellations in urban environments. Furthermore, this study assesses the benefits of using a priori inter-system clock-offset information. The positioning performance of multiple GNSS constellations has been examined through covariance simulation and with live data. The benefit of using a priori clock-offset constraints has been demonstrated. It has been found that the benefits of using a priori clock-offset constraints to help enhance the availability of position solutions and fault detection and exclusion capabilities are particularly significant when the receiver is located in areas where limited GNSS signals are available such as in the urban-canyon environment.
Open Access
GNSS Integrity Monitoring with Modelling Temporal Correlated Measurement Noise and an Application to RTK
(2021-09) Gao, Yuting; Gao, Yang; O'Keefe, Kyle; EI-Sheimy, Naser
The reliability of a navigation system is important in support of applications from self-driving cars to smartphones, especially for safety-critical and liability-critical applications which require stringent reliability requirements. In recent years, there is an increasing demand for global navigation satellite system (GNSS) integrity monitoring of precise positioning. Due to the features of fast response, strong autonomy and low-cost, user level GNSS integrity monitoring is an effective way to assess the reliability of GNSS positioning systems. It makes use of the measurements redundancy to check the statistical consistency of measurements and provide timely alarms. GNSS measurement noises are typically assumed to be uncorrelated Gaussian white noises in KF for GNSS integrity monitoring. However, this assumption does not hold in practical applications because GNSS observations can be contaminated by hardware noise, multipath, and unmodeled errors, resulting in correlated noises. To tackle the above limitations, an algorithm of user level GNSS integrity monitoring is proposed, which considers temporally correlated measurement noise with an application to real-time kinematic (RTK) positioning. An approach based on colored Kalman filter (CKF) is presented which considers measurement time correlation by a first-order autoregressive model and rebuilds a new measurement model for the CKF. The state variance matrix obtained by the CKF can accurately reflect the realistic position error, while the estimate of the standard Kalman filter is found to be overly optimistic. Then, by considering colored noises in standard KF, an algorithm of enhanced fault detection and exclusion is developed and investigated. This study examined and analyzed the CKF-based fault detection test, a fault identification test, a minimum detectable bias (MDB), error distribution, and positioning results. The CKF-based FDE can obtain realistic statistical information to improve integrity monitoring reliability by reducing false alarm rates. A new method of calculating protection level in the position domain is developed, based on a linear KF by modeling measurement time-correlated colored noise that provides a more realistic protection level in the position domain.
Open Access
GPS Signal Authentication Using INS - A Comparative Study and Analysis
(2016) Manickam, Sashidharan; O'Keefe, Kyle; Sadeghpour, Farnaz; Gao, Yang
Global Navigation Satellite System (GNSS) signal spoofing is an emerging threat to civilian GNSS receivers. Inertial Navigation Systems (INS) are often integrated with GNSS for accurate positioning and navigation, and to bridge GNSS outages in cases where GNSS-only navigation is not feasible. Inertial observations, being self-contained, are not easily spoofed and this redundant information can be used to authenticate GNSS observations. This thesis presents a comparative study and analysis of the GNSS signal authentication limits using INS in terms of minimum detectable blunder while using different grades of GNSS/INS integrated systems to detect/identify a fault in GPS observation. Results show that for lower spoofing dynamics and longer spoofing duration, all sensor grades fail to detect the GNSS spoofing error immediately. When the spoofing dynamics are high, a high quality INS provides better GNSS signal authentication performance. GNSS/INS integration provides a marginal improvement in the detection/identification performance of spoofed GNSS observations.
Open Access
In-orbit performance of the canx-2 nanosatellite's gps receiver
(2011) Kahr, Erin Jennifer; O'Keefe, Kyle
The CanX-2 Nanosatellite is a student built satellite launched into orbit April 28tl1, 2008. Among its scientific payloads, CanX-2 is carrying a commercial off the shelf dual frequency geodetic grade GPS receiver. The receiver, a Nov Ate] OEM4-G2L, is operated intermittently and has been used for the collection of both radio occultation data and orbit determination data. This thesis presents an empirical study of the acquisition properties of the OEM4-G2L under orbital dynamics. A method has been designed for rapidly acquiring a position fix in spite of CanX-2's orbital velocity. First hand experiences of acquisition successes and challenges in orbit have helped refine the method, ultimately cutting the average acquisition time down from 20 minutes to 3.5 minutes, at the cost of operational complexity. An algorithm enabling the same rapid acquisition without ground support has been designed based on the constraints of nanosatellite operations, and validated using CanX-2 data.