Research Article
RSS Fingerprint Based Signal Source Localization Using Singular Value Decomposition
@INPROCEEDINGS{10.1007/978-3-030-89814-4_60, author={Mingzhu Li and Lei Cai}, title={RSS Fingerprint Based Signal Source Localization Using Singular Value Decomposition}, proceedings={Mobile Multimedia Communications. 14th EAI International Conference, Mobimedia 2021, Virtual Event, July 23-25, 2021, Proceedings}, proceedings_a={MOBIMEDIA}, year={2021}, month={11}, keywords={Radio frequency fingerprint Signal source localization Singular value decomposition}, doi={10.1007/978-3-030-89814-4_60} }- Mingzhu Li
Lei Cai
Year: 2021
RSS Fingerprint Based Signal Source Localization Using Singular Value Decomposition
MOBIMEDIA
Springer
DOI: 10.1007/978-3-030-89814-4_60
Abstract
As the technique determines the position of a target device based on radio frequency (RF) fingerprint, received signal strength (RSS) fingerprint source localization technology is attracting increasing attention due to its numerous applications. In this paper, we propose a novel RSS Fingerprint Based Signal Source Localization algorithm. We use multi-dimensional interpolation to establish a fingerprint database, and singular value decomposition (SVD) is utilized to extract effective information from the fingerprint data. We divide the fingerprint database into multiple sub-fingerprint databases according to the location area andk-nearest neighbor (KNN) algorithm. Moreover, we adjust the fingerprints in each sub-fingerprint database to complete the offline training phase. In the online positioning phase, in order to improve the positioning efficiency, we use thek-dimensional (KD) tree algorithm to predict the fingerprint database using the fingerprint data received from the test point and determine the final position of the target source. Extensive measurements are carried out and it is proved that the proposed method is superior to existing ones.
