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Thesis

Robust indoor positioning with lifelong learning

Abstract:

Indoor tracking and navigation is a fundamental need for pervasive and context-aware applications. However, no practical and reliable indoor positioning solution is available at present. The major challenge of a practical solution lies in the fact that only the existing devices and infrastructure can be utilized to achieve high positioning accuracy.

This thesis presents a robust indoor positioning system with the lifelong learning ability. The typical features of the proposed soluti...

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Institution:
University of Oxford
Research group:
Sensor Networks Group
Oxford college:
Kellogg College
Department:
Mathematical,Physical & Life Sciences Division - Computer Science,Department of
Role:
Author

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Role:
Supervisor
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Funding agency for:
Zhuoling Xiao
Publication date:
2014
Type of award:
DPhil
Level of award:
Doctoral
Awarding institution:
Oxford University, UK
URN:
uuid:218283f1-e28a-4ad0-9637-e2acd67ec394
Local pid:
ora:11528

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