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Localisation of mobile nodes in wireless networks with correlated in time measurement noise.

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Localisation of mobile nodes in wireless networks with correlated in time measurement noise. / Mihaylova, Lyudmila; Angelova, Donka; Bull, David R.; Canagarajah, Nishan.

In: IEEE Transactions on Mobile Computing, Vol. 10, No. 1, 01.2011, p. 44-53.

Research output: Contribution to Journal/MagazineJournal articlepeer-review

Harvard

Mihaylova, L, Angelova, D, Bull, DR & Canagarajah, N 2011, 'Localisation of mobile nodes in wireless networks with correlated in time measurement noise.', IEEE Transactions on Mobile Computing, vol. 10, no. 1, pp. 44-53. https://doi.org/10.1109/TMC.2010.132

APA

Mihaylova, L., Angelova, D., Bull, D. R., & Canagarajah, N. (2011). Localisation of mobile nodes in wireless networks with correlated in time measurement noise. IEEE Transactions on Mobile Computing, 10(1), 44-53. https://doi.org/10.1109/TMC.2010.132

Vancouver

Mihaylova L, Angelova D, Bull DR, Canagarajah N. Localisation of mobile nodes in wireless networks with correlated in time measurement noise. IEEE Transactions on Mobile Computing. 2011 Jan;10(1):44-53. https://doi.org/10.1109/TMC.2010.132

Author

Mihaylova, Lyudmila ; Angelova, Donka ; Bull, David R. ; Canagarajah, Nishan. / Localisation of mobile nodes in wireless networks with correlated in time measurement noise. In: IEEE Transactions on Mobile Computing. 2011 ; Vol. 10, No. 1. pp. 44-53.

Bibtex

@article{02cecfd2fc424150a490264fa1f27d12,
title = "Localisation of mobile nodes in wireless networks with correlated in time measurement noise.",
abstract = "Wireless sensor networks are an inherent part of decision making, object tracking and location awareness systems. This work is focused on simultaneous localisation of mobile nodes based on received signal strength indicators (RSSIs) with correlated in time measurement noises. Two approaches to deal with the correlated measurement noises are proposed in the framework of auxiliary particle filtering: with a noise augmented state vector and the second approach implements noise decorrelation. The performance of the two proposed multi model auxiliary particle filters (MM AUX-PFs) is validated over simulated and real RSSIs and high localisation accuracy is demonstrated.",
keywords = "wireless networks, auxiliary particle filtering, localisation, correlated measurement noises, multiple model estimation",
author = "Lyudmila Mihaylova and Donka Angelova and Bull, {David R.} and Nishan Canagarajah",
year = "2011",
month = jan,
doi = "10.1109/TMC.2010.132",
language = "English",
volume = "10",
pages = "44--53",
journal = "IEEE Transactions on Mobile Computing",
issn = "1536-1233",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
number = "1",

}

RIS

TY - JOUR

T1 - Localisation of mobile nodes in wireless networks with correlated in time measurement noise.

AU - Mihaylova, Lyudmila

AU - Angelova, Donka

AU - Bull, David R.

AU - Canagarajah, Nishan

PY - 2011/1

Y1 - 2011/1

N2 - Wireless sensor networks are an inherent part of decision making, object tracking and location awareness systems. This work is focused on simultaneous localisation of mobile nodes based on received signal strength indicators (RSSIs) with correlated in time measurement noises. Two approaches to deal with the correlated measurement noises are proposed in the framework of auxiliary particle filtering: with a noise augmented state vector and the second approach implements noise decorrelation. The performance of the two proposed multi model auxiliary particle filters (MM AUX-PFs) is validated over simulated and real RSSIs and high localisation accuracy is demonstrated.

AB - Wireless sensor networks are an inherent part of decision making, object tracking and location awareness systems. This work is focused on simultaneous localisation of mobile nodes based on received signal strength indicators (RSSIs) with correlated in time measurement noises. Two approaches to deal with the correlated measurement noises are proposed in the framework of auxiliary particle filtering: with a noise augmented state vector and the second approach implements noise decorrelation. The performance of the two proposed multi model auxiliary particle filters (MM AUX-PFs) is validated over simulated and real RSSIs and high localisation accuracy is demonstrated.

KW - wireless networks

KW - auxiliary particle filtering

KW - localisation

KW - correlated measurement noises

KW - multiple model estimation

U2 - 10.1109/TMC.2010.132

DO - 10.1109/TMC.2010.132

M3 - Journal article

VL - 10

SP - 44

EP - 53

JO - IEEE Transactions on Mobile Computing

JF - IEEE Transactions on Mobile Computing

SN - 1536-1233

IS - 1

ER -