@inproceedings{33a23d7bca5741e6b4ea8d2c9ffbc9e2,
title = "Multilateration localization based on Singular Value Decomposition for 3D indoor positioning",
abstract = "Localization is crucial for various applications, this includes resource coordination in small and ultra-small cells, as well as the whole range of Location Based Service (LBS). Multilateration is a localization technique that is based on distance measurements between multiple reference nodes and a target node. This paper introduces a multilateration localization approach that uses Singular Value Decomposition (SVD) for 3D indoor positioning. It also provides a mathematical multilateration formulation which considers the coordinates of the reference nodes and the relative distance between transmitting nodes. In practical deployments, the relative distance can be estimated using RSSI; we apply Kalman filtering to the RSSI measurements aiming to get a more accurate RSSI value. The approach is complemented by using two selection methods which help chosing the best nodes for multilateration computation. The paper concludes with a discussion of the experimental evaluation results obtained.",
keywords = "Kalman Filter, Localization, Multilateration, RSSI, Singular Value Decomposition (SVD)",
author = "Jihoon Yang and Haeyoung Lee and Klaus Moessner",
note = "{\textcopyright} 2016 IEEE.; 2016 International Conference on Indoor Positioning and Indoor Navigation, IPIN 2016 ; Conference date: 04-10-2016 Through 07-10-2016",
year = "2016",
month = nov,
day = "14",
doi = "10.1109/IPIN.2016.7743627",
language = "English",
series = "2016 International Conference on Indoor Positioning and Indoor Navigation, IPIN 2016",
publisher = "Institute of Electrical and Electronics Engineers (IEEE)",
booktitle = "2016 International Conference on Indoor Positioning and Indoor Navigation, IPIN 2016",
address = "United States",
}