LOCALIZING TRANSCEIVER-FREE OBJECTS: THE RF-BASED APPROACHES

The Hong Kong University of Science and Technology
Department of Computer Science and Engineering


PhD Thesis Defence


Title: "LOCALIZING TRANSCEIVER-FREE OBJECTS:
THE RF-BASED APPROACHES"

By

Miss Dian Zhang


Abstract

Traditional radio-based localization technologies all require the target 
object to carry a transmitter (e.g., active RFID), a receiver (e.g., 
802.11x detector), or a transceiver (e.g., sensor node). In practice, 
however, such requirements can not be satisfied in many applications, such 
as security and surveillance, intrusion detection, outdoor asset 
protection, and location-aware applications. In this dissertation, I 
propose a new localization scheme called transceiver-free localization. 
The basic idea of transceiver-free localization is to utilize the change 
of wireless signals of different wireless links to locate the target 
object. I prove that the object detection behavior of each wireless link 
can be described by two models. They are called S-D Model and T-R model. 
The former one is a deterministic model and the later one is a 
probabilistic model. T-R model presents many unique features and new 
requirements. Although it is derived from transceiver-free object 
localization, it presents promising generality which enable it be applied 
in a much broader scope of application, calling a revisit for most of 
coverage problems. Moreover, in order to serve different localization 
requirements and address the problem in centralized or distributed 
environments, I propose five localization algorithms called Midpoint, 
Intersection, Best-cover, Dynamic Clustering and RASS. The former 3 
algorithms are based on centralized environment. Dynamic Clustering and 
RASS are able to locate multiple objects. I prove that RASS guaranteed 
tracking accuracy is bounded by only about 0.26s without sacrificing the 
accuracy and scalability. Experimental results show that these algorithms 
can have remarkable high accuracy up to 0.85m. At Last, our 
transceiver-free localization approaches can also be utilized to improve 
the accuracy of traditional transceiver-based approaches. Cocktail is a 
hybrid approach by using WSN and RFID technologies. Experiment results 
show that it can improve the accuracy of traditional pure RFID system by 
75% in a large indoor area.


Date:			Friday, 14 May 2010

Time:			4:30pm – 6:30pm

Venue:			Room 3401
 			Lifts 17/18

Chairman:		Prof. Man Wong (ECE)

Committee Members:	Prof. Lionel Ni (Supervisor)
 			Prof. Bo Li
                     	Prof. Qian Zhang
                         Prof. Bing Zeng (ECE)
                         Prof. Jian-Nong Cao (Comp., PolyU.)


**** ALL are Welcome ****