NLOS Classification based on RSS and Ranging Statistics Obtained from Low-Cost UWB Devices

NLOS Classification based on RSS and Ranging Statistics Obtained from Low-Cost UWB Devices

Citation Author(s):
Valentin
Barral
University of A Coruña
Carlos J.
Escudero
University of A Coruña
Jose Antonio
García-Naya
Submitted by:
Valentin Barral
Last updated:
Wed, 02/27/2019 - 04:04
DOI:
10.21227/swz9-y281
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Abstract: 

Ultra Wide Band (UWB) devices have been largely considered for indoor location systems due to their high accu- racy. However, as in other wireless systems, such accuracy is significantly degraded under Non-Line-of-Sight (NLOS) propaga- tion conditions. Therefore, distinguishing between Line-of-Sight (LOS) and NLOS becomes essential to mitigate inaccuracies due to NLOS propagation.

Most of these classification processes are based on the study of the Channel Impulse Response (CIR), something that can be hard to perform depending on some aspects like the computational cost, the time of process or the availability of data from the CIR. In this research, we present an alternative for classification based on another set of parameters easier to obtain and work with, in particular the Radio Signal Strength (RSS) and the range estimation given by low-cost UWB devices. We analyze the effect of using different statistics of these parameters as features to feed a Support Vector Machine (SVM) Classifier. To test the classifier, we use measurements taken in a real scenario with real low-cost hardware and in both LOS and NLOS situations.

Instructions: 

In Matlab:

 

los = load('LOS.mat');

nlos_h = load('NLOS_H.mat');

nlos_s = load('NLOS_S.mat');

 

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[1] Valentin Barral, Carlos J. Escudero, Jose Antonio García-Naya, " NLOS Classification based on RSS and Ranging Statistics Obtained from Low-Cost UWB Devices", IEEE Dataport, 2019. [Online]. Available: http://dx.doi.org/10.21227/swz9-y281. Accessed: Jun. 19, 2019.
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doi = {10.21227/swz9-y281},
url = {http://dx.doi.org/10.21227/swz9-y281},
author = {Valentin Barral; Carlos J. Escudero; Jose Antonio García-Naya },
publisher = {IEEE Dataport},
title = { NLOS Classification based on RSS and Ranging Statistics Obtained from Low-Cost UWB Devices},
year = {2019} }
TY - DATA
T1 - NLOS Classification based on RSS and Ranging Statistics Obtained from Low-Cost UWB Devices
AU - Valentin Barral; Carlos J. Escudero; Jose Antonio García-Naya
PY - 2019
PB - IEEE Dataport
UR - 10.21227/swz9-y281
ER -
Valentin Barral, Carlos J. Escudero, Jose Antonio García-Naya. (2019). NLOS Classification based on RSS and Ranging Statistics Obtained from Low-Cost UWB Devices. IEEE Dataport. http://dx.doi.org/10.21227/swz9-y281
Valentin Barral, Carlos J. Escudero, Jose Antonio García-Naya, 2019. NLOS Classification based on RSS and Ranging Statistics Obtained from Low-Cost UWB Devices. Available at: http://dx.doi.org/10.21227/swz9-y281.
Valentin Barral, Carlos J. Escudero, Jose Antonio García-Naya. (2019). " NLOS Classification based on RSS and Ranging Statistics Obtained from Low-Cost UWB Devices." Web.
1. Valentin Barral, Carlos J. Escudero, Jose Antonio García-Naya. NLOS Classification based on RSS and Ranging Statistics Obtained from Low-Cost UWB Devices [Internet]. IEEE Dataport; 2019. Available from : http://dx.doi.org/10.21227/swz9-y281
Valentin Barral, Carlos J. Escudero, Jose Antonio García-Naya. " NLOS Classification based on RSS and Ranging Statistics Obtained from Low-Cost UWB Devices." doi: 10.21227/swz9-y281