The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. ex. Some numerals are expressed as "XNUMX".
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The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. Copyrights notice
La localisation de la source dans un réseau de capteurs sans fil (WSN) est sensible aux positions des capteurs. En pratique, en raison de la mobilité, les positions des récepteurs peuvent être connues de manière imprécise, entraînant une dégradation non négligeable des performances d'estimation de la localisation des sources. Le but de cet article est de développer une méthode de programmation semi-définie (SDP) utilisant la différence de temps d'arrivée (TDOA) et la différence de fréquence d'arrivée (FDOA) en prenant en compte les incertitudes de position du capteur. Plus précisément, nous transformons le problème de l’estimateur du maximum de vraisemblance (MLE) couramment utilisé en un problème d’optimisation convexe pour obtenir une estimation initiale. Pour réduire le couplage entre l'estimateur de position et de vitesse, nous proposons également une méthode itérative pour obtenir la vitesse et la position, en utilisant respectivement la méthode des moindres carrés pondérés (WLS) et la méthode SDP. Les simulations montrent que la méthode peut s'approcher de la limite inférieure de Cramér-Rao (CRLB) sous des niveaux de bruit légers et élevés.
Zhengfeng GU
Chinese Academy of Sciences,the University of Chinese Academy of Sciences
Hongying TANG
Chinese Academy of Sciences
Xiaobing YUAN
Chinese Academy of Sciences
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Zhengfeng GU, Hongying TANG, Xiaobing YUAN, "A Robust Semidefinite Source Localization TDOA/FDOA Method with Sensor Position Uncertainties" in IEICE TRANSACTIONS on Communications,
vol. E104-B, no. 4, pp. 472-480, April 2021, doi: 10.1587/transcom.2020EBP3086.
Abstract: Source localization in a wireless sensor network (WSN) is sensitive to the sensors' positions. In practice, due to mobility, the receivers' positions may be known inaccurately, leading to non-negligible degradation in source localization estimation performance. The goal of this paper is to develop a semidefinite programming (SDP) method using time-difference-of arrival (TDOA) and frequency-difference-of-arrival (FDOA) by taking the sensor position uncertainties into account. Specifically, we transform the commonly used maximum likelihood estimator (MLE) problem into a convex optimization problem to obtain an initial estimation. To reduce the coupling between position and velocity estimator, we also propose an iterative method to obtain the velocity and position, by using weighted least squares (WLS) method and SDP method, respectively. Simulations show that the method can approach the Cramér-Rao lower bound (CRLB) under both mild and high noise levels.
URL: https://global.ieice.org/en_transactions/communications/10.1587/transcom.2020EBP3086/_p
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@ARTICLE{e104-b_4_472,
author={Zhengfeng GU, Hongying TANG, Xiaobing YUAN, },
journal={IEICE TRANSACTIONS on Communications},
title={A Robust Semidefinite Source Localization TDOA/FDOA Method with Sensor Position Uncertainties},
year={2021},
volume={E104-B},
number={4},
pages={472-480},
abstract={Source localization in a wireless sensor network (WSN) is sensitive to the sensors' positions. In practice, due to mobility, the receivers' positions may be known inaccurately, leading to non-negligible degradation in source localization estimation performance. The goal of this paper is to develop a semidefinite programming (SDP) method using time-difference-of arrival (TDOA) and frequency-difference-of-arrival (FDOA) by taking the sensor position uncertainties into account. Specifically, we transform the commonly used maximum likelihood estimator (MLE) problem into a convex optimization problem to obtain an initial estimation. To reduce the coupling between position and velocity estimator, we also propose an iterative method to obtain the velocity and position, by using weighted least squares (WLS) method and SDP method, respectively. Simulations show that the method can approach the Cramér-Rao lower bound (CRLB) under both mild and high noise levels.},
keywords={},
doi={10.1587/transcom.2020EBP3086},
ISSN={1745-1345},
month={April},}
Copier
TY - JOUR
TI - A Robust Semidefinite Source Localization TDOA/FDOA Method with Sensor Position Uncertainties
T2 - IEICE TRANSACTIONS on Communications
SP - 472
EP - 480
AU - Zhengfeng GU
AU - Hongying TANG
AU - Xiaobing YUAN
PY - 2021
DO - 10.1587/transcom.2020EBP3086
JO - IEICE TRANSACTIONS on Communications
SN - 1745-1345
VL - E104-B
IS - 4
JA - IEICE TRANSACTIONS on Communications
Y1 - April 2021
AB - Source localization in a wireless sensor network (WSN) is sensitive to the sensors' positions. In practice, due to mobility, the receivers' positions may be known inaccurately, leading to non-negligible degradation in source localization estimation performance. The goal of this paper is to develop a semidefinite programming (SDP) method using time-difference-of arrival (TDOA) and frequency-difference-of-arrival (FDOA) by taking the sensor position uncertainties into account. Specifically, we transform the commonly used maximum likelihood estimator (MLE) problem into a convex optimization problem to obtain an initial estimation. To reduce the coupling between position and velocity estimator, we also propose an iterative method to obtain the velocity and position, by using weighted least squares (WLS) method and SDP method, respectively. Simulations show that the method can approach the Cramér-Rao lower bound (CRLB) under both mild and high noise levels.
ER -