View Proposal

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Proposer

Phil Bartie

Title

Improving Outdoor Positoning Solutions

Goal

Improve upon GNSS positioning

Description

GNSS (e.g. GPS, GLONASS) offers a very useful positioning solution for outdoor situations. In most cases these technologies can locate a user to withing 10metres of their actual location. However for some tasks (e.g. robotics, autonomous vehicles, pedestrian navigation guides) this accuracy is not great enough. Positional accuracy is particularly problematic in urban environments (e.g. buildings occluding direct line of sight to the satellites). Pedestrians are also much harder than vehicles to locate accurately as they can turn on the spot, and don't have to follow road regulations. This project will explore a variety of solutions to improve on the performance using map matching techniques, particle filters, and GNSS shadowing. This will involve developing code to process GNSS positions in conjunction with geospatial datasets for roads, pavements and buildings. Building heights could also be used for modelling theoretical lines of sight to GNSS satellites. Ideally software will be written in Python and made available as opensource at the end of the project.

Resources

OS Master Map Data, Mobile phone

Background

Url

Difficulty Level

High

Ethical Approval

None

Number Of Students

1

Supervisor

Phil Bartie

Keywords

Degrees

Bachelor of Science in Computer Science
Bachelor of Science in Computer Systems
Master of Engineering in Software Engineering