Sifu: A FINGERPRINT-BASED LOCALIZATION FRAMEWORK TO FUSE HETEROGENEOUS SIGNALS

MPhil Thesis Defence


Title: "Sifu: A FINGERPRINT-BASED LOCALIZATION FRAMEWORK TO FUSE 
HETEROGENEOUS SIGNALS"

By

Mr. Zhiheng DENG


Abstract

Signals such as WiFi, magnetism and GPS may be detected by mobile phones and 
used for localization. Fingerprint-based localization, due to its deployability 
in complex environment, emerges as a promising approach. Because each signal 
has its own strengths and limitations, fusing them potentially captures their 
strengths while mitigating their weaknesses. Recent works on that often are 
highly engineered and specificically designed for two or three signals whose 
data have to be fully available at localization step. They can hardly be 
extended to embrace flexible combination of arbitrary signals with different 
sampling rate.

We propse Sifu, a highly accurate fingerprint-based localization framework to 
fuse any number and combination of heterogeneous signals. Once in operation, 
Sifumay include new signals or exclude old ones without the need for retraining 
of the existing signals. To achieve this, Sifufirst extracts location-dependent 
features from signal readings with a novel machine learning model. Based on the 
features, it then estimates user location with maximum likelihood estimation 
(MLE). Sifu is simple to implement. We conduct extensive experiments in three 
markedly different sites. Sifuis shown to achieve significantly better 
performance as compared with state-of-the-art approaches, in terms of 
localization error (cutting the error by 20% in our experiments).


Date:			Thursday, 12 September 2019

Time:			10:00am - 12:00noon

Venue:			Room 3598
 			Lifts 27/28

Committee Members:	Prof. Gary Chan (Supervisor)
 			Dr. Raymond Wong (Chairperson)
 			Dr. Qifeng Chen


**** ALL are Welcome ****