Use this URL to cite or link to this record in EThOS: http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.673800
Title: Received signal strength based person localisation
Author: Cully, William Patrick Lloyd
ISNI:       0000 0004 5369 6275
Awarding Body: Queen's University Belfast
Current Institution: Queen's University Belfast
Date of Award: 2014
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Abstract:
This thesis focussed upon the localisation of people and specifically the effect that the human body had upon estimated positions produced by the tested localisation algorithms. These algorithms used the signal strength measured between two nodes to provide ranging information to allow a user's position to be estimated. However, the human body causes non-line of sight situations, termed as the body shadowing effect. This effect is especially important in this work as the node worn by the user took on a smartwatch style form factor worn on the wrist. This natural positioning meant that line of sight between two nodes could be easily blocked by the user's body. Body shadowing caused deviation from the true positions which were generally skewed from the true path depending upon the orientation of the user. These deviations are detailed in this thesis and a number' of approaches were taken to reduce them. Firstly was the implementation of a statistically based localisation algorithm, which incorporated a history of the user's estimated positions into its design. This reduced the erratic trajectories produced, and ensured momentary non-line of sight would have a lesser effect upon estimated trajectories. Secondly was the implementation of line of sight specific channel models which were employed depending upon the user's orientation. Thirdly, two diversity schemes were investigated, polarisation and spatial. Polarisation diversity took on the form of two receivers at each node built into the infrastructure arranged 90° to each other. Spatial diversity saw the user wear two nodes, one on each wrist. Finally an extension to the statistically based localisation algorithm was presented that allowed cooperation between multiple users to enhance their localisation accuracy.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.673800  DOI: Not available
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