Thesis Details
Klasifikace přímého a odraženého signálu pomocí vestavěného systému
This thesis aims to design and implement an algorithm for classification of signals that are used for tracking objects using ultra-wideband technology. The classification method should be able to detect an obstruction between receiver and transmitter, which means to classify signals as those with line of sight (LOS) and non-line of sight (NLOS). This system must be quick and lightweight enough, so real-time detection can be achieved directly in the embedded system. While searching for the solution, multiple classification methods were examined. The best-performing ones involved numerous variants of decision tree classifiers. Considering the restricted computing power of embedded devices, random forest classifier was chosen as the final solution. This classification method was able to achieve accuracy of up to 89% while evaluating the dataset. When deployed in real-life environment, it was able to detect an object between transmitter and receiver. Classification and calculation of parameters takes 6000 instruction cycles and the algorithm fits into 4kB of memory. Results of this thesis enable improvement of existing solutions for detection of NLOS signals that degrade tracking performance. This will boost the accuracy of localization while tracking objects in indoor environments.
UWB, Signals, classification, DW1000
Bartík Vladimír, Ing., Ph.D. (DIFS FIT BUT), člen
Češka Milan, doc. RNDr., Ph.D. (DITS FIT BUT), člen
Jaroš Jiří, doc. Ing., Ph.D. (DCSY FIT BUT), člen
Orság Filip, Ing., Ph.D. (DITS FIT BUT), člen
@bachelorsthesis{FITBT23962,
author = "Miroslav Chalko",
type = "Bachelor's thesis",
title = "Klasifikace p\v{r}\'{i}m\'{e}ho a odra\v{z}en\'{e}ho sign\'{a}lu pomoc\'{i} vestav\v{e}n\'{e}ho syst\'{e}mu",
school = "Brno University of Technology, Faculty of Information Technology",
year = 2022,
location = "Brno, CZ",
language = "slovak",
url = "https://www.fit.vut.cz/study/thesis/23962/"
}