Open AccessIMPROVED INDOOR LOCALIZATION WITH DIVERSITY AND FILTERING BASED ON RECEIVED SIGNAL STRENGTH MEASUREMENTS
Author(s) -
Andreas Fink,
Helmut Beikirch,
Matthias Voß
Publication year - 2010
Publication title -
computing
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.184
H-Index - 11
eISSN - 2312-5381
pISSN - 1727-6209
DOI - 10.47839/ijc.9.1.692
Subject(s) - computer science , signal (programming language) , signal strength , dropout (neural networks) , synchronization (alternating current) , antenna diversity , transmission (telecommunications) , diversity combining , node (physics) , position (finance) , simple (philosophy) , path (computing) , diversity scheme , diversity (politics) , real time computing , received signal strength indication , algorithm , data transmission , telecommunications , computer network , wireless , decoding methods , acoustics , machine learning , physics , channel (broadcasting) , philosophy , finance , epistemology , sociology , fading , anthropology , economics , programming language
Distance estimation by the evaluation of RSSI measurements is a simple and well-known technique to predict the position of an unknown node. Therefore the infrastructure does not have to be extended by expensive hardware for synchronization or direction approximation. However, with the localization based on RSSI measurements common and proven systems can be used for the infrastructure. For indoor environments the distance-pending path loss is affected by strong variations, especially appearing as frequency specific signal dropouts. A diversity concept with redundant data transmission in different frequency bands can reduce the dropout probability. If also space diversity and plausibility filtering are used, the Location Estimation Error can be reduced significantly. The investigations show that a good performance for precision and availability can also be reached with low infrastructural costs.