Localisation of Sensor Nodes with Hybrid Measurements in Wireless Sensor Networks
Localisation in wireless networks faces challenges such as high levels of signal attenuation and unknown path-loss exponents, especially in urban environments. In response to these challenges, this paper proposes solutions to localisation problems in noisy environments. A new observation model for l...
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doaj-1f47d671612b4f4abacf2a56d9b30fb62020-11-25T00:05:21ZengMDPI AGSensors1424-82202016-07-01167114310.3390/s16071143s16071143Localisation of Sensor Nodes with Hybrid Measurements in Wireless Sensor NetworksMuhammad W. Khan0Naveed Salman1Andrew H. Kemp2Lyudmila Mihaylova3School of Electronic and Electrical Engineering, University of Leeds, Leeds LS2 9JT, UKDepartment of Automatic Control and Systems Engineering, Sheffield University, Sheffield S1 3JD, UKSchool of Electronic and Electrical Engineering, University of Leeds, Leeds LS2 9JT, UKDepartment of Automatic Control and Systems Engineering, Sheffield University, Sheffield S1 3JD, UKLocalisation in wireless networks faces challenges such as high levels of signal attenuation and unknown path-loss exponents, especially in urban environments. In response to these challenges, this paper proposes solutions to localisation problems in noisy environments. A new observation model for localisation of static nodes is developed based on hybrid measurements, namely angle of arrival and received signal strength data. An approach for localisation of sensor nodes is proposed as a weighted linear least squares algorithm. The unknown path-loss exponent associated with the received signal strength is estimated jointly with the coordinates of the sensor nodes via the generalised pattern search method. The algorithm’s performance validation is conducted both theoretically and by simulation. A theoretical mean square error expression is derived, followed by the derivation of the linear Cramer-Rao bound which serves as a benchmark for the proposed location estimators. Accurate results are demonstrated with 25%–30% improvement in estimation accuracy with a weighted linear least squares algorithm as compared to linear least squares solution.http://www.mdpi.com/1424-8220/16/7/1143hybrid localisationreceived signal strengthangle of arrivalgeneralised pattern search |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Muhammad W. Khan Naveed Salman Andrew H. Kemp Lyudmila Mihaylova |
spellingShingle |
Muhammad W. Khan Naveed Salman Andrew H. Kemp Lyudmila Mihaylova Localisation of Sensor Nodes with Hybrid Measurements in Wireless Sensor Networks Sensors hybrid localisation received signal strength angle of arrival generalised pattern search |
author_facet |
Muhammad W. Khan Naveed Salman Andrew H. Kemp Lyudmila Mihaylova |
author_sort |
Muhammad W. Khan |
title |
Localisation of Sensor Nodes with Hybrid Measurements in Wireless Sensor Networks |
title_short |
Localisation of Sensor Nodes with Hybrid Measurements in Wireless Sensor Networks |
title_full |
Localisation of Sensor Nodes with Hybrid Measurements in Wireless Sensor Networks |
title_fullStr |
Localisation of Sensor Nodes with Hybrid Measurements in Wireless Sensor Networks |
title_full_unstemmed |
Localisation of Sensor Nodes with Hybrid Measurements in Wireless Sensor Networks |
title_sort |
localisation of sensor nodes with hybrid measurements in wireless sensor networks |
publisher |
MDPI AG |
series |
Sensors |
issn |
1424-8220 |
publishDate |
2016-07-01 |
description |
Localisation in wireless networks faces challenges such as high levels of signal attenuation and unknown path-loss exponents, especially in urban environments. In response to these challenges, this paper proposes solutions to localisation problems in noisy environments. A new observation model for localisation of static nodes is developed based on hybrid measurements, namely angle of arrival and received signal strength data. An approach for localisation of sensor nodes is proposed as a weighted linear least squares algorithm. The unknown path-loss exponent associated with the received signal strength is estimated jointly with the coordinates of the sensor nodes via the generalised pattern search method. The algorithm’s performance validation is conducted both theoretically and by simulation. A theoretical mean square error expression is derived, followed by the derivation of the linear Cramer-Rao bound which serves as a benchmark for the proposed location estimators. Accurate results are demonstrated with 25%–30% improvement in estimation accuracy with a weighted linear least squares algorithm as compared to linear least squares solution. |
topic |
hybrid localisation received signal strength angle of arrival generalised pattern search |
url |
http://www.mdpi.com/1424-8220/16/7/1143 |
work_keys_str_mv |
AT muhammadwkhan localisationofsensornodeswithhybridmeasurementsinwirelesssensornetworks AT naveedsalman localisationofsensornodeswithhybridmeasurementsinwirelesssensornetworks AT andrewhkemp localisationofsensornodeswithhybridmeasurementsinwirelesssensornetworks AT lyudmilamihaylova localisationofsensornodeswithhybridmeasurementsinwirelesssensornetworks |
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