@inproceedings{1cf49ebeaeb943f58a81421de52c706a,
title = "Conditional Rician K-Factor Discrimination for Indoor Localization via AOA Estimation",
abstract = "This paper proposes conditioning angle of arrival (AOA) algorithms for pseudo-spectrum fingerprint acquisition based on line of sight (LOS) and non-LOS detection schema for optimizing indoor localization. The proposed approach merges two AOA based methods being that of the MUltiple Signal Classsification (MUSIC) algorithm and virtual MUSIC algorithm into a conditional based localization approach with a uniform circular array (UCA). The paper begins by demonstrating the environmental dependencies of the two AOA approaches based on the Rician K-factor metric. The K-factor is then exploited as an algorithm selection metric to arrive at improved localization performance in a realistic indoor environment.",
author = "Hall, \{Donald L.\} and Jenkins, \{David M.\}",
note = "Publisher Copyright: {\textcopyright} 2021 IEEE.; 2021 IEEE Military Communications Conference, MILCOM 2021 ; Conference date: 29-11-2021 Through 02-12-2021",
year = "2021",
doi = "10.1109/MILCOM52596.2021.9653091",
language = "English (US)",
series = "Proceedings - IEEE Military Communications Conference MILCOM",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "969--974",
booktitle = "MILCOM 2021 - 2021 IEEE Military Communications Conference",
address = "United States",
}