@inproceedings{633c507522884f87874d3ea8c683f8fe,
title = "Localization Error Analysis of Indoor Positioning System Based on UWB Measurements",
abstract = "Ultra wide band (UWB) systems use time information instead of the popular received signal strength indication (RSSI). UWB is known for its high position accuracy in localization. RSSI-based localization is easily affected by signal attenuation and has a poor localization accuracy as compared to the time of arrival (TOA) technique. In this paper, different localization algorithms for the UWB system were analytically reviewed. The performance of the localization algorithms is discussed in terms of root mean square and cumulative distribution function of localization errors. The experiment results demonstrate the effectiveness of different localization algorithms for UWB indoor positioning. The fingerprint estimation algorithm shows better performance compared to linearized least square estimation and weighted centroid estimation algorithms. The experimental results show that the linearized least square algorithm has poor performance for UWB indoor localization.",
keywords = "fingerprint estimation, Indoor localization, least square estimation, ultra wide band, weighted centroid estimation",
author = "Alwin Poulose and Eyobu, {Odongo Steven} and Myeongjin Kim and Han, {Dong Seog}",
note = "Publisher Copyright: {\textcopyright} 2019 IEEE.; 11th International Conference on Ubiquitous and Future Networks, ICUFN 2019 ; Conference date: 02-07-2019 Through 05-07-2019",
year = "2019",
month = jul,
doi = "10.1109/ICUFN.2019.8806041",
language = "English",
series = "International Conference on Ubiquitous and Future Networks, ICUFN",
publisher = "IEEE Computer Society",
pages = "84--88",
booktitle = "ICUFN 2019 - 11th International Conference on Ubiquitous and Future Networks",
address = "United States",
}