PhD title: Multi-Constellation and Multi-Frequency Precise Point Positioning
Supervisors: Prof Terry Moore and Dr Chris Hill
The navigation system is undergoing dramatic changes, since the first global navigation system (GPS) and the satellite navigation has significantly developed to include GLONASS, Galileo and BeiDou. These Four constellation bring a great opportunity for scientific and engineering application with increase number of satellite and spatial geometry the accuracy, convergence time ,reliability and continuity could be improve.This project will investigate the performance of multi constellation (GPS, GLONASS, Galileo and Beidou) and multi frequency in term of high accuracy and precisions and comparison between the constellation and finding the best combination. High positioning technique will be used namely precise point positioning (PPP) in static case, using single receiver to process pseudo range and carrier phase measurement up to millimetre accuracy.
PhD title: Using Personal Data to Configure Navigation Support for Blind and Partially Sighted People
Supervisors: Dr Rob Houghton, Prof Terry Moore and Dr James Pinchin
This PhD looks into using visually impaired people’s personal data such as location history and preferences to provide them with a safe and personalised navigation solution. This PhD tries to identify the visually impaired people’s navigation requirements and needs and create a navigation based profile for each user so that each navigation journey is personalised to the user based on his/her user profile. In addition, the navigation solution considers the use of a low-cost and widely available navigation device which is smartphone. Further, this research will explore the extent to which the navigation of visually impaired people might be enhanced using the approach of this research in comparison to the approaches taken by the existing navigation solutions.
PhD title: Estimation of multi GNSS instrumental biases
Supervisors: Dr Marcio Aquino, Prof Alan Dodson and Dr Sreeja Vadakke Veettil
In ionospheric modelling, the Differential Code Biases (DCBs) cannot be neglected. These are frequently estimated by the different analysis centres of the IGS under an external constraint that the involved satellites DCBs have a zero mean. My research work involves the estimation of DCB for one receiver set by simulating signals that are free of the ionospheric, tropospheric and other group delays using a hardware signal simulator. This receiver DCB is then used as a ‘known’ parameter to constrain the global ionospheric solution in a network, where the receiver and satellite DCBs are estimated for the entire network. Currently, I am looking at how to incorporate these estimated DCBs in Precise Point Positioning (PPP) to get improved position and lower convergence time.
PhD title: Comparsion of some transformation procedures for the Nigerian Geodetic Network
Our position on the surface of the earth is defined by horizontal coordinates, latitude and longitude, which is in the past, referenced to local datum while the vertical coordinates, orthometric height, is referenced to the vertical datum. The unification of the two datum came with the advent of space technology which is based on the global datum. Coordinates can thus be transformed from one datum to another through datum transformation. This research is investigating different transformation models to derive set of transformation parameters for the Nigerian Geodetic Network to transform coordinates from global datum to local datum and vice versa.
PhD title: High Accuracy Multi-Constellation Multi-Frequency GNSS
With the evolving GNSS landscape, the IGS has started the Multi-GNSS Experiment to produce products for new constellations. However, at the moment these products can only be used in post-processing. In my research, a simulator of Multi – GNSS observations and Real – Time products has been developed to analyse the performance of GPS only, Galileo only and GPS plus Galileo Precise Point Positioning. The impact of different signals combined in the Ionosphere – Free combination and the potential of the Galileo E5 signal are analysed. Finally alternative methods of ionosphere delay mitigation are considered in order to ensure the best possible positioning performance.
Research title: Required Localisation Performance of Connected and Autonomous Vehicles
Supervisors: Dr Xiaolin Meng and Dr Simon Roberts
This project aims to establish requirement metrics of CAV in localisation and develop integrated localisation solutions for CAV. The required localisation performance of CAV will consist of three main parts, which are satellite positioning, sensing and communication. The relevant parameters, such as accuracy, availability, cost etc., will be defined and set up. The integrated localisation solutions will then be realised by the advanced algorithms which aims to provide required positioning performance in real driving environment. All the requirement metrics will then be assessed via a prototype CAV platform to verify and refine the CAV parameters.
PhD title: Trust and Calibration of Trust in Connected and Automated Vehicles
Supervisors: Dr Xiaolin Meng, Dr Gary Burnett and Dr Catherine Harvey
The focus of this Ph.D. is given by the new area that has emerged: the rise of the connected and automated vehicle. Although the concept is an old one that can be found in utopic/dystopic literature, early attempts to create driverless vehicles have existed before but only with the recent project sponsored by DARPA, the driverless car has stepped closer towards becoming a reality. Appropriate levels of trust are an integral part in the successful deployment of such vehicles, especially since the trust of a user in the automated system is crucial for its use, disuse or abuse. Although some of the technologies that are incorporated into driverless cars have already existed in other fields such as aviation (autopilot), the driver-vehicle-environment system has specific characteristics and consequently, knowledge from other areas does not necessarily transfer.
PhD title: Ionospheric scintillation sensitive tracking models and mitigation tools
Supervisors: Dr Marcio Aquino
Ionospheric scintillation, characterised by signal fluctuations caused by irregularities in the upper atmosphere, the ionosphere, is potentially the most critical phenomenon degrading GNSS positioning performance. Approaches to tackle this crippling effect include improved signal tracking models for GNSS receivers and specialist algorithms to exploit these models in high accuracy position estimation under scintillation conditions. The research will make significant contributions to the development of scintillation robust signal tracking models for multi-GNSS receivers as well as mitigation tools to support high accuracy GNSS positioning techniques. It is expected that novel scintillation mitigation tools will be developed that explore the concept of GNSS receiver tracking jitter maps.The research is part of the Marie Skłodowska-Curie Actions ITN titled TREASURE - "Training, REsearch and Applications network to Support the Ultimate Real time high accuracy EGNSS solution", and will be carried out in synergy with other research projects integrated in TREASURE."
PhD title: A Multiple Algorithm Approach to the Analysis of GNSS Time Series for Detecting Geohazards and Anomalies
Supervisors: Dr Panagiotis Psimoulis and Dr Richard Bingley
This research focuses on developing a multiple algorithm approach to the analysis of GNSS time series for detecting geohazards and anomalies. His research studies the GNSS time series in spatial, temporal and spatio-temporal domains using Machine learning, signal processing and spatial analysis algorithms. His approach was examined using three different applications (1) The analysis of the GNSS coordinate time series of the GEONET network in Japan, corresponding to the Tohoku-Oki 2011 Mw9.0 earthquake (2) The analysis of the long-term GNSS coordinate time series of the BIGF network in the British Isles. (3)The analysis of the long-term GNSS troposphere time series of the BIGF network in the British Isles.
PhD title: Connected and Autonomous Vehicle Cyber Security
Supervisors: Dr Xiaolin Meng and Dr Simon Roberts
Qiyi received her B.Sc degree in software engineering and BA degree in English in China, and M.Sc degree in advanced computer science (software engineering) from the University of Manchester. She is currently in her first year of her PhD in Civil Engineering at the University of Nottingham. Her research is now mainly on connected and autonomous vehicle cyber security, which includes machine learning, cryptography and other relevant fields.
PhD title: Modelling Land Cover Change Due to Oil activities in the Niger Delta
Supervisors: Dr Stephen Grebby and Dr Doreen Boyd
In recent decades, the oil industry has contributed significantly to land cover change within the Niger Delta region of Nigeria. However, the true extent and severity of the land cover change due to oil production and exploration activities remains unclear. Therefore, the aims of this project are:
PhD title: Application of Indoor Positioning to Understand Building Occupancy
Supervisors: Prof Terry Moore, Dr Peer-Olaf Siebers and Dr James Pinchin
Previous occupancy detection is limited to tracking individuals in office rooms using different sensor technology for presence and absence but cannot get the true trajectory of an individual’s occupancy. My research focuses on developing a novel indoor positioning system which can be used to understand Building occupancy and behavior in an Academic building. This data can potentially be used to better understand and predict building Energy usage eg: Electricity.
PhD title: Assessment of the accuracy and the contribution of multi-GNSS in structural monitoring
Supervisors: Dr Craig Hancock, Dr Panagiotis Psimoulis, Dr Gethin Roberts and Dr Lukasz Bonenberg
Hussein Msaewe is Assistant Professor of Surveying Engineering at the College of Engineering, University of Baghdad, Iraq. He is currently enrolled as a full-time PhD student with the Nottingham Geospatial Institute (NGI), the University of Nottingham, UK. His current research interests are concentrated around structural monitoring by multi-GNSS.
PhD title: Photogrammetric computer vision methods for the automatic reconstruction of virtual environments in Civil Engineering
Supervisors: Dr Martin Smith and Dr Nick Kokkas
Kostas is working on the emerging field of infrastructure computer vision that entails collecting real world data, analysing it into useful information, and generating knowledge by fusing sensors, data, and human input. The challenge is to transform traditional computer-aided geometric design workflows for parametric curve and surface reconstruction to automated processes using machine learning methods aiming to create augmented and virtual reality content for civil engineering applications
PhD title: Investigating the GPS noise characteristics on structural monitoring
Supervisors: Dr Panagiotis Psimoulis and Dr Xiaolin Meng
Research interests are in GPS reflectometry and multipath characterisation and mitigation on monitoring of dynamic motion. The main focus of this project is on using the multipath effect on the satellite signals to detect and measure the deflection of structures. This is done by using signal processing and analysis techniques on experimental and simulated positioning data. This project introduces a new approach on beneficially using the impact of multipath on the satellite signals for structural monitoring applications. The aim is to create a robust and reliable technique for the accurate estimation of the structural deformation on limited satellite visibility and heavy multipath environments.
PhD title: GNSS RTK-PPP Algorithm Development
Brian is an early stage researcher funded by the TREASURE (Training REsearch and Applications network to Support the Ultimate Real time high accuracy EGNSS solution) program. His goal is to develop innovative Real-time PPP and Network RTK algorithms to optimally combine the external atmospheric information for suitable integration into high accuracy and robust PPP and RTK solutions. Brian will incorporate the new algorithms into PPP software and develop a format to broadcast ionospheric and tropospheric models in an economic way. Also, he will extend the fast and reliable ambiguity-fixing to multi-GNSS, including GPS, GLONASS, Galileo and BeiDou with the ultimate aim to achieve robust centimetre level positioning for offshore applications.
PhD title: Ubiquitous Position Techniques for First Responders
Supervisors: Dr Xiaolin Meng and Dr Oluropo Ogundipe
This research focuses on firefighter communications and personnel location problems during fire accidents. The main aim of this project is to meet the requirement of firefighters and improve the performance of indoor tracking. As an indispensable part of the first responder, firefighters are always facing the most difficult situations, such as darkness, smoke, heat and heavy PPEs. A significant problem facing firefighters within a GPS challenged environment is the ability to communicate reliably between the firefighter and the command post or communications centre. By using an integrated UWB-IMU system with human motion analysis, the correct estimation of a moving subject in firefighting scenarios can be improved.
PhD title: Assessment of the accuracy of low cost GPS receivers integrated with acclerometers for the monitoring of dynamic motion of structures
Supervisors: Dr Xiaolin Meng and Dr Panagiotis Psimoulis
Although GNSS technologies are used broadly in structural health monitoring of stiff civil engineering structures, the relatively high cost of GNSS receivers adopted are restraining their applications. Therefore, the aim of my project is to investigate the accuracy of low-cost GNSS receivers in monitoring low and high frequency motion and evaluate the potentials of low-cost GNSS receivers in monitoring civil engineering structures. The investigation will first focus on defining noise characteristics of the low-cost GNSS receivers experimentally, then the low-cost GNSS receivers will be assessed in monitoring the motion based on the motion frequency in the lab followed by data analysis and real infrastructure monitoring.
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