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".
Copyrights notice
The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. Copyrights notice
L'objectif de la localisation sans fil est de déterminer l'emplacement de la station mobile (MS) dans un système de communications cellulaires sans fil. Lorsque les signaux se propagent via des trajets sans visibilité directe (NLOS), les mesures au niveau des stations de base (BS) contiennent de grandes erreurs qui se traduisent par une mauvaise détectabilité d'une MS par les BS environnantes. Dans ces situations, il est nécessaire d’intégrer toutes les mesures hétérogènes disponibles pour améliorer la précision de la localisation. Cet article présente des méthodes hybrides qui combinent l'heure d'arrivée (TOA) au niveau de trois BS et les informations d'angle d'arrivée (AOA) au niveau de la BS de desserte pour obtenir une estimation de l'emplacement de la MS. Les méthodes proposées atténuent l'effet NLOS en utilisant la somme pondérée des intersections entre trois cercles TOA et la ligne AOA sans nécessiter le a à priori connaissance des statistiques d'erreurs NLOS. Les résultats numériques montrent que toutes les méthodes de positionnement offrent une précision d'estimation améliorée par rapport à celles qui reposent sur deux cercles et deux lignes. Les méthodes proposées obtiennent toujours une meilleure précision de localisation que l'algorithme des séries de Taylor (TSA) et l'algorithme des lignes de position hybrides (HLOP), quelles que soient les statistiques d'erreur NLOS.
The copyright of the original papers published on this site belongs to IEICE. Unauthorized use of the original or translated papers is prohibited. See IEICE Provisions on Copyright for details.
Copier
Chien-Sheng CHEN, Szu-Lin SU, Yih-Fang HUANG, "Mobile Location Estimation in Wireless Communication Systems" in IEICE TRANSACTIONS on Communications,
vol. E94-B, no. 3, pp. 690-693, March 2011, doi: 10.1587/transcom.E94.B.690.
Abstract: The objective of wireless location is to determine the mobile station (MS) location in a wireless cellular communications system. When signals are propagated through non-line-of-sight (NLOS) paths, the measurements at the base stations (BSs) contain large errors which result in poor detectability of an MS by the surrounding BSs. In those situations, it is necessary to integrate all available heterogeneous measurements to improve location accuracy. This paper presents hybrid methods that combine time of arrival (TOA) at three BSs and angle of arrival (AOA) information at the serving BS to obtain a location estimate for the MS. The proposed methods mitigate the NLOS effect by using the weighted sum of the intersections between three TOA circles and the AOA line without requiring the a priori knowledge of NLOS error statistics. Numerical results show that all positioning methods offer improved estimation accuracy over those which rely on the two circles and two lines. The proposed methods always achieve better location accuracy than the Taylor series algorithm (TSA) and the hybrid lines of position algorithm (HLOP) do, regardless of the NLOS error statistics.
URL: https://global.ieice.org/en_transactions/communications/10.1587/transcom.E94.B.690/_p
Copier
@ARTICLE{e94-b_3_690,
author={Chien-Sheng CHEN, Szu-Lin SU, Yih-Fang HUANG, },
journal={IEICE TRANSACTIONS on Communications},
title={Mobile Location Estimation in Wireless Communication Systems},
year={2011},
volume={E94-B},
number={3},
pages={690-693},
abstract={The objective of wireless location is to determine the mobile station (MS) location in a wireless cellular communications system. When signals are propagated through non-line-of-sight (NLOS) paths, the measurements at the base stations (BSs) contain large errors which result in poor detectability of an MS by the surrounding BSs. In those situations, it is necessary to integrate all available heterogeneous measurements to improve location accuracy. This paper presents hybrid methods that combine time of arrival (TOA) at three BSs and angle of arrival (AOA) information at the serving BS to obtain a location estimate for the MS. The proposed methods mitigate the NLOS effect by using the weighted sum of the intersections between three TOA circles and the AOA line without requiring the a priori knowledge of NLOS error statistics. Numerical results show that all positioning methods offer improved estimation accuracy over those which rely on the two circles and two lines. The proposed methods always achieve better location accuracy than the Taylor series algorithm (TSA) and the hybrid lines of position algorithm (HLOP) do, regardless of the NLOS error statistics.},
keywords={},
doi={10.1587/transcom.E94.B.690},
ISSN={1745-1345},
month={March},}
Copier
TY - JOUR
TI - Mobile Location Estimation in Wireless Communication Systems
T2 - IEICE TRANSACTIONS on Communications
SP - 690
EP - 693
AU - Chien-Sheng CHEN
AU - Szu-Lin SU
AU - Yih-Fang HUANG
PY - 2011
DO - 10.1587/transcom.E94.B.690
JO - IEICE TRANSACTIONS on Communications
SN - 1745-1345
VL - E94-B
IS - 3
JA - IEICE TRANSACTIONS on Communications
Y1 - March 2011
AB - The objective of wireless location is to determine the mobile station (MS) location in a wireless cellular communications system. When signals are propagated through non-line-of-sight (NLOS) paths, the measurements at the base stations (BSs) contain large errors which result in poor detectability of an MS by the surrounding BSs. In those situations, it is necessary to integrate all available heterogeneous measurements to improve location accuracy. This paper presents hybrid methods that combine time of arrival (TOA) at three BSs and angle of arrival (AOA) information at the serving BS to obtain a location estimate for the MS. The proposed methods mitigate the NLOS effect by using the weighted sum of the intersections between three TOA circles and the AOA line without requiring the a priori knowledge of NLOS error statistics. Numerical results show that all positioning methods offer improved estimation accuracy over those which rely on the two circles and two lines. The proposed methods always achieve better location accuracy than the Taylor series algorithm (TSA) and the hybrid lines of position algorithm (HLOP) do, regardless of the NLOS error statistics.
ER -