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Title: Advances in UWB-based indoor position estimation and its application in fall detection
Author: Onalaja, Oladimeji
ISNI:       0000 0004 7224 6966
Awarding Body: London South Bank University
Current Institution: London South Bank University
Date of Award: 2015
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In an indoor propagation environment, the position of an Object of Interest (OOI) is typically estimated by cleverly manipulating range or proximity measurements that are obtained from a series of reference node combinations. In a noise-free propagation scenario, these measured parameters are fed into conventional position estimation techniques and an accurate estimate of the OOI’s position is obtained. In practice, the propagation scenario is never quite noise-free; hence the OOI’s position estimate is obtained in error. Ultra-Wideband (UWB) is a wireless communication technology that is able to resolve individual multipath components and this ensures that it is capable of estimating the arrival time of the first signal path. The implication of this lies in the fact that the accuracy of the range or proximity measurements obtained from the reference node combinations is guaranteed; hence leading to a reliable estimate of the OOI’s position. In the research work presented in this thesis, the body of knowledge that relates to indoor position estimation is advanced upon. With a primary focus of enhancing the estimation accuracy of indoor position estimation systems, UWB is utilised as the underlying wireless communications technology. The challenges faced by current UWBbased position estimation systems are identified and tackled directly. Specifically, the position estimation error that is due to multipath propagation is addressed and a pre-localisation algorithm that serves the purpose of resolving individual multipath UWB signals in the immediate environment is proposed. Additionally, a novel position estimation technique coined as Time Reflection of Arrival (TROA) is presented in this thesis. Through a series of Mean Squared Error (MSE) and Cram ́er-Rao Lower Bound (CRLB) analyses, TROA is shown to be very effective when compared to TOA and the typically unvoiced TSOA technique. In the last section of this thesis, an application of UWB in the area of Biomedical Engineering is demonstrated. Specifically, UWB-based position estimation is used to define a novel fall detection algorithm tailored for Dementia patients.
Supervisor: Xiao, Perry ; Dudley-McEvoy, Sandra Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral