Localization and tracking objects or people in real time in indoor environments have
gained great importance. In the literature and market, many different location
estimation and tracking solutions using received signal strength indication (RSSI) are
proposed. But there is a lack of information on the comparison of these techniques
revealing their weak and strong behaviors over each other. There is a need for the
answer to the question / &ldquo / which localization/tracking method is more suitable to my
system needs?&rdquo / . So, one purpose of this thesis is to seek the answer to this question.
Hence, we investigated the behaviors of commonly proposed localization methods,
mainly nearest neighbors based methods, grid based Bayesian filtering and particle
filtering methods by both simulation and experimental work on the same test bed.
The other purpose of this thesis is to propose an improved method that is simple to
install, cost effective and moderately accurate to use for real life applications. Our
proposed method uses an improved type of sampling importance resampling (SIR)
filter incorporating automatic calibration of propagation model parameters of logv
distance path loss model and RSSI measurement noise by using reference tags. The
proposed method also uses an RSSI smoothing algorithm exploiting the RSSI
readings from the reference tags.
We used an active RFID system composed of 3 readers, 1 target tag and 4 reference
tags in a home environment of two rooms with a total area of 36 m² / . The proposed
method yielded 1.25 m estimation RMS error for tracking a mobile target.
| Identifer | oai:union.ndltd.org:METU/oai:etd.lib.metu.edu.tr:http://etd.lib.metu.edu.tr/upload/12613014/index.pdf |
| Date | 01 February 2011 |
| Creators | Ozkaya, Bora |
| Contributors | Koc, Arzu |
| Publisher | METU |
| Source Sets | Middle East Technical Univ. |
| Language | English |
| Detected Language | English |
| Type | M.S. Thesis |
| Format | text/pdf |
| Rights | To liberate the content for public access |
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