TY - GEN
T1 - Localization of vehicular ad-hoc networks with RSS based distance estimation
AU - Saeed, Nasir
AU - Ahmad, Waqas
AU - Bhatti, Dost Muhammad Saqib
N1 - Publisher Copyright:
© 2018 IEEE.
PY - 2018/4/24
Y1 - 2018/4/24
N2 - Location information of a vehicle provides numerous applications such as, emergency calling, navigation, vehicle tracking and other location based services. Vehicles localization in vehicular adhoc networks (VANETs) in urban scenarios is a key issue for public safety applications. Motivated by localization of vehicles in urban areas for public safety, where the de facto standard solution global positioning system (GPS) does not provide the required localization accuracy, a local closed form solution is proposed for VANETs localization exploiting the communication with road side units (RSUs). In proposed technique the vehicle receives signals from the RSUs within its range, and computes the average receive signal strength (RSS) from each RSU. The average RSS measurements are fed to the proposed closed form localization algorithm which computes the the vehicle position. The proposed algorithm only take the RSS measurements from the closer RSUs with higher signal to noise ratio, which results in better location estimation. The performance of the proposed closed form solution is analyzed by deriving its Cramer Rao lower bound. Numerous simulations are performed to show that the proposed RSS based closed form solution outperforms the least square and weighted least square techniques.
AB - Location information of a vehicle provides numerous applications such as, emergency calling, navigation, vehicle tracking and other location based services. Vehicles localization in vehicular adhoc networks (VANETs) in urban scenarios is a key issue for public safety applications. Motivated by localization of vehicles in urban areas for public safety, where the de facto standard solution global positioning system (GPS) does not provide the required localization accuracy, a local closed form solution is proposed for VANETs localization exploiting the communication with road side units (RSUs). In proposed technique the vehicle receives signals from the RSUs within its range, and computes the average receive signal strength (RSS) from each RSU. The average RSS measurements are fed to the proposed closed form localization algorithm which computes the the vehicle position. The proposed algorithm only take the RSS measurements from the closer RSUs with higher signal to noise ratio, which results in better location estimation. The performance of the proposed closed form solution is analyzed by deriving its Cramer Rao lower bound. Numerous simulations are performed to show that the proposed RSS based closed form solution outperforms the least square and weighted least square techniques.
KW - Cramer Rao lower bound
KW - Location Information
KW - Received signal strength
KW - Vehicular adhoc networks
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U2 - 10.1109/ICOMET.2018.8346313
DO - 10.1109/ICOMET.2018.8346313
M3 - Conference contribution
AN - SCOPUS:85050967489
T3 - 2018 International Conference on Computing, Mathematics and Engineering Technologies: Invent, Innovate and Integrate for Socioeconomic Development, iCoMET 2018 - Proceedings
SP - 1
EP - 6
BT - 2018 International Conference on Computing, Mathematics and Engineering Technologies
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2018 International Conference on Computing, Mathematics and Engineering Technologies, iCoMET 2018
Y2 - 3 March 2018 through 4 March 2018
ER -