Browsing by Author "Langley, Richard"

Now showing 1 - 9 of 9
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    Carrier-phase multipath mitigation in RTK-based GNSS dual-antenna systems
    (University of New Brunswick, 2013) Serrano, Luis; Langley, Richard; Kim, Don
    Carrier-phase multipath mitigation in GPS/GNSS real-time kinematic (RTK) mode has been studied for several years, at least since on-the-fly ambiguity resolution techniques were introduced, and receiver hardware improvements to the point that GNSS RTKbased systems provide position estimates at the mm to cm-level accuracy in real-time. This level of accuracy has heralded a new era of applications where the use of GNSS RTK-based techniques have become a very practical navigation tool, especially in the fields of machine automation, industrial metro logy, control, and robotics. However, this incredible surge in accuracy tied with real-time capabilities comes with a cost: one must also ensure continuity, and integrity (safety). Typical users of these systems do not expect heavy machinery, guided and/or controlled by GNSS-based systems, to output erroneous solutions even in challenging multipath environments. In multipath-rich scenarios, phase-multipath reflections can seriously degrade the RTK solutions, and in worst scenarios, integer fixed solutions are no longer available. This dissertation intends to deal with these scenarios, where the rover algorithms should deal with multiple reflections and, in real-time, be able to ameliorate/mitigate their effect. GNSS-based heading/attitude is usually obtained combining the data from two or more antennas (also known as a moving baseline). Many companies provide commercial systems based on this technique, hence this dissertation finds its main applicability here. Typical heavy construction machinery includes dozers, motor-graders, excavators, scrappers, etc., which are being equipped more frequently with GNSS dual-antenna systems to provide positioning and orientation information to the operator. We have not used and collected data from one of these machines, although the author has worked extensively with such machinery and their GNSS-based systems. However, the theory developed throughout this dissertation and the proof of concept through controlled tests that mimic the machinery/installed GNSS dual-antenna systems, are the basis of this dissertation. Moreover the algorithms developed here are meant to be used independently from the receiver hardware, as well as from GNSS signals. Hence GLONASS, and/or Galileo signals can be processed too. This dissertation is based on the fundamental relationship between multiple multipath reflections from close-by strong reflections, and their effect on GNSS RTK-based dual-antenna systems. Two questions were answered: Firstly, is it possible to retrieve strong multipath reflectors in kinematic applications? Second, once these strong reflectors are correctly identified, how accurate/reliable are the corrections to the raw carrier-phase multipath, knowing that the host platform performs unpredictable manoeuvres? Based on the results, we can conclude that it is possible to estimate m real-time multipath parameters based on a strong effective reflector. In most of the tests it takes at least 2 minutes to obtain initial values (after Kalman filter convergence). Once they are determined, multipath corrections can be determined straightforwardly for each satellite being tracked, as long as there are no cycle-slips (mostly due to the combination of the machinery high dynamics, especially within the areas where antennas are located, and the machinery itself blocking momentarily satellite signals).
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    Control survey study for LRIS
    Hamilton, Angus; Wells, David; Chzranowski, Adam; Faig, Wolfgang; Langley, Richard; Vanĩcek, Petr; McLaughlin, John
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    Control survey study for LRIS
    Hamilton, Angus; Wells, David; Chzranowski, Adam; Faig, Wolfgang; Langley, Richard; Vanĩcek, Petr; McLaughlin, John
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    Development and assessment of loosely-coupled ins using smartphone sensors
    (University of New Brunswick, 2016) Infante, Eduardo; Langley, Richard
    Smartphone accelerometers and gyroscopes are quite common in today‟s society but little work has been done on assessing how accurate and reliable they are to be used in inertial navigation systems (INS). The goal of this research is to develop a loosely-coupled INS filter that only uses sensors found inside a Moto-X Android smartphone. Micro-electro-mechanical sensors (MEMS) accelerometers and gyroscopes provide the raw motion sensor data whereas the high-sensitivity GNSS receiver in the smartphone is used to provide position and velocity updates to the filter. Magnetometers, also included in the MEMS are a potential source of heading aiding that not only aids in INS alignment but helps constrain the heading drift. A successful filter implementation could potentially open the doors of inertial navigation to the everyday smartphone user. This would allow developers of smartphone applications to focus on the creative side of their application while using the loosely-coupled INS in the background. The loosely-coupled INS filter was developed in C++ and was run offline although the operations are exactly those that would be applied in real time. The INS filter was verified by using raw inertial measurement unit (IMU) measurements from a high-end Northrop Grumman IMU-LN200 motion sensor and single-point GNSS position/velocity updates from a high accuracy NovAtel Flexpak6 receiver. Two datasets with distinct environments were used. The first one was a relatively open-sky dataset in NW Calgary and the second was an urban canyon dataset in downtown Calgary. Once the INS was verified to work within expectations, two more datasets were collected, this time with the Moto-X Android smartphone and the NovAtel SPAN system (IMU-LN200 + Flexpak6 running INS capable firmware). The datasets were again in open-sky and urban canyon environments. Due to the high noise of the Moto-X sensors, the high frequency noise of the raw data was removed via wavelet decomposition. This was very important as the faint sensor signal is buried under a lot of noise. Empirically derived estimates for sensor turn-on bias and scale factor errors were then found. The easiest way to assess the validity of the filter is to compare the attitude with the truth trajectory, where the truth trajectory is that of the NovAtel SPAN solution. The reason for this is that position and velocity are directly dependent on the quality of input filter updates. It is possible to have good results in position and velocity but still have a filter that diverges in attitude. When ran with the IMU-LN200 and NovAtel Flexpak6 data, the loosely-coupled INS filter had RMS differences in pitch and roll under 0.4º in the open-sky dataset and under 0.8º in the urban canyon dataset. RMS differences in heading were below 1º in the open-sky dataset and slightly above 1º in the urban canyon dataset. When ran with the Moto-X Android smartphone sensors, the INS filter had RMS differences in pitch and roll below 4.5 º in the open-sky dataset and below 16 º in the urban canyon datasets respectively. The RMS differences in heading were around 13º for the open-sky dataset and large enough to make the system useless for the urban canyon dataset. The results show the Moto-X Android smartphone sensors can be used for civilian enthusiast level of navigation under open-sky environments. It is however expected for MEMS sensors to improve over time thus improving the usability of a loosely-coupled INS filter using smartphone sensors.
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    Global Positioning System differential positioning simulations
    Davidson, Derek; Delikaraoglou, Demitris; Langley, Richard; Nickerson, Bradford; Vanicek, Petr; Wells, David
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    Global Positioning System differential positioning simulations
    Davidson, Derek; Delikaraoglou, Demitris; Langley, Richard; Nickerson, Bradford; Vanicek, Petr; Wells, David
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    Improved convergence for GNSS precise point positioning
    (University of New Brunswick, 2014) Banville, Simon; Langley, Richard
    The precise point positioning (PPP) methodology allows for cm-level positioning accuracies using a single GNSS receiver, through careful modelling of all error sources affecting the signals. Adoption of PPP in several applications is however muted due to the time required for solutions to converge or re-converge to their expected accuracy, which regularly exceeds 30 minutes for a moving receiver. In an attempt at solving the convergence issues associated with PPP, three aspects were investigated. First, signal tracking interruptions are typically associated with integer discontinuities in carrier-phase measurements, often referred to as a cycle slips. A refined method for detecting and correcting cycle slips was thus developed, in which all error sources affecting the observations are either modelled or estimated. Application of this technique allows for instantaneous cycle-slip correction, meaning that continuous PPP solutions can be obtained even in the presence of short losses of lock on satellites. Second, external information on the ionosphere allows for reduced convergence times, but consistency must be observed in the functional model. A new technique, termed integer levelling, was thus developed to generate ionospheric delay corrections compatible with PPP based on the decoupled-clock model. Depending on the inter-station distances in the network providing ionospheric corrections, instantaneous cm-level accuracies can be obtained in PPP. Third, processing of GLONASS signals is more problematic than GPS due to frequency division multiple access, leading to inter-frequency carrier-phase and code biases. A novel approach for the estimation of such biases was then proposed and facilitates processing of mixed receiver types. It also allows for undifferenced GLONASS ambiguity resolution based on a heterogeneous network of stations, the first demonstration of such an approach ,and therefore has the potential to further reduce PPP convergence times. This research also emphasized potential benefits of integer-levelled observations for improved ionosphere monitoring. The main justifications for adopting this approach are: a reduction in the determination of slant total electron content errors, a simplification in the GLONASS processing strategy, its applicability in real time, and the generation of satellite biases required for the use of ionospheric constraints in PPP with ambiguity resolution.
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    On environmental adaptation in GNSS-based integrated navigation systems
    (University of New Brunswick, 2020) Smolyakov, Ivan; Langley, Richard
    The most efficient positioning and navigation solutions for mass-market applications are based on integration of data collected with several sensors installed on a user platform. The ability of the system, both to measure a variety of physical effects and to generate infrastructure-induced measurements, allows us to exploit strengths and to compensate, to an extent, for vulnerabilities of individual sensors. GNSS remains a key building block of integrated navigation systems; however, in urban scenarios it is negatively affected by reflection, attenuation, and blockage of radio signals. If unaccounted for, the GNSS performance variation caused by the above effects may result in sub-optimal state estimation. In a pursuit of a design allowing for a GNSS-based integrated navigation system to automatically adjust its parameters with respect to the surrounding GNSS environment, the following aspects were investigated. First, inaccurate specification of noise covariances in a Kalman filter may lead to a solution degradation. The novel concept of GNSS environment mapping has been developed, to allow a state estimation filter to adjust its measurement noise by relying on crowd-sourced GNSS measurement statistical representation over an urban area of operation, instead of relying solely on data available on an individual platform. Application of the concept leads to increased coordinate determination accuracy and to a faster solution re-convergence. By training a random forest model, the GNSS environment map availability is extended to areas for which no crowd-sourced GNSS data is available. Second, to decrease vulnerability of a minimum error variance estimator to inaccurate stochastic modelling, a filter could be extended with a worst-case error minimization criterion, such that it makes no assumptions on noise properties. In the new solution to continuously maintain balance between the two estimation criteria, a reinforcement learning framework has been introduced into the GNSS-based integrated navigation engine. Practical results show the capability of such a model to progressively self-improve while encountering diverse GNSS signal propagation scenarios. These novel developments have been tested with several configurations of GNSS-based integrated navigation engines; a 13% and 17% absolute accuracy improvement in the tightly- and loosely-coupled integration modes respectively is demonstrated. The identified shortcomings of the proposed techniques and the recommendations for further developments are provided.
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    Precise point positioning with wide area differential GPS corrections
    (University of New Brunswick, 2019) Rho, Hyun Ho; Langley, Richard
    Wide area differential GPS (WADGPS) satellite-based augmentation system (SBAS) services, such as the Wide Area Augmentation System (WAAS) in U.S.A., provide satellite orbit and clock corrections and ionospheric delay corrections. Although their corrections are optimized for use with GPS single-frequency pseudorange measurements, the satellite orbit and clock corrections can be used to improve GPS positioning accuracy for dual-frequency users. The main objective of the research described in this dissertation is the design of a GPS dual-frequency data processing technique capable of producing high-accuracy point positioning results with WADGPS corrections. In this research, three major issues were identified as the satellite clock referencing issue, the resolution of the fast clock correction issue and the residual orbit and clock issue. By considering that the ways to handle the identified issues in a precise point positioning (PPP) process are different for different position estimator and different basis observables, a SBAS PPP with a weighted least-squares approach using a carefully designed sequential forward carrier-phase smoother and a SBAS PPP with sequential least-squares approach using un-differenced dual-frequency code and carrier-phase measurements have been developed. To account for the satellite clock referencing issue, the effects of the satellite instrumental biases have been precisely investigated and the observation equations for the different observables assuming the source of corrections is WADGPS have been developed. To account for the low resolutions of WAAS (or/and any SBAS corrections which follows the RTCA standard [2001]) fast clock corrections, a weighted moving average filter was adopted and a proper smoothing factor has been carefully determined. Finally, to take into account the residual orbit and clock errors, a varying carrier-phase ambiguity concept has been applied rather than assuming the ambiguity is constant over time. This method is only applicable for the SBAS PPP with a sequential least-squares method which has an ambiguity parameter for each satellite in the observation model. Results determined via developed software indicate a few decimeter-level of positioning accuracy for both developed PPP algorithms with (real-time) WADGPS orbit and clock corrections in kinematic mode could be attainable. Although a few decimeter-level of positioning accuracy are slightly less accurate than that of using precise orbit and clock products, it will give more flexibility and chances to choose a proper positioning technique, which can meet the majority of user expectations and their application needs. Furthermore, the algorithms developed in this research can be used for seamless PPP solutions with future SBAS corrections when all the planned SBASs are in operation.