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Erschienen in: Journal of Reliable Intelligent Environments 2/2020

11.12.2019 | Original Article

Human movement effects on the performance of the RSSI-based trilateration method: adaptive filters for distance compensation

verfasst von: Yoschanin Sasiwat, Dujdow Buranapanichkit, Kanadit Chetpattananondh, Kiattisak Sengchuai, Nattha Jindapetch, Apidet Booranawong

Erschienen in: Journal of Reliable Intelligent Environments | Ausgabe 2/2020

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Abstract

In this paper, an experimental study of human movement effects in indoor wireless networks on the performance of the received signal strength indicator (RSSI)-based trilateration method is presented. The contribution of this work is that how the RSSI fluctuation caused by human movements nearby a target node influences the estimation accuracy of the trilateration method is studied. Additionally, efficient adaptive filters which can observe RSSI variation levels and select appropriate inputs (i.e., distance values converted from RSSI values) are proposed for handling the RSSI variation problem and compensating the position estimation error. Experiments using low-cost 2.4-GHz wireless nodes have been set and tested in a laboratory room. Results demonstrate that, during the human blocking the communication link between the transmitter and the receiver, RSSI data are fluctuated and the trilateration method shows a large estimation error. Here, the localization accuracy significantly depends on the RSSI variation level. The experimental results also indicate that, by applying our proposed solutions, they can automatically provide appropriate inputs for the trilateration method. The estimation error decreases by 43.76% and 46.28% for our test scenarios.

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Metadaten
Titel
Human movement effects on the performance of the RSSI-based trilateration method: adaptive filters for distance compensation
verfasst von
Yoschanin Sasiwat
Dujdow Buranapanichkit
Kanadit Chetpattananondh
Kiattisak Sengchuai
Nattha Jindapetch
Apidet Booranawong
Publikationsdatum
11.12.2019
Verlag
Springer International Publishing
Erschienen in
Journal of Reliable Intelligent Environments / Ausgabe 2/2020
Print ISSN: 2199-4668
Elektronische ISSN: 2199-4676
DOI
https://doi.org/10.1007/s40860-019-00094-x

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