Target Localization Using Instrumental Variable Method in Sensor Network

Yong Hwi KIM; Ka Hyung CHOI; Tae Sung YOON; Jin Bae PARK

doi:10.1587/transcom.E96.B.1202

Target Localization Using Instrumental Variable Method in Sensor Network

Yong Hwi KIM, Ka Hyung CHOI, Tae Sung YOON, Jin Bae PARK

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An instrumental variable (IV) based linear estimator is proposed for effective target localization in sensor network by using time-difference-of-arrival (TDOA) measurement. Although some linear estimation approaches have been proposed in much literature, the target localization based on TDOA measurement still has a room for improvement. Therefore, we analyze the estimation errors of existing localization estimators such as the well-known quadratic correction least squares (QCLS) and the robust least squares (RoLS), and demonstrate advantages of the proposition by comparing the estimation errors mathematically and showing localization results through simulation. In addition, a recursive form of the proposition is derived to consider a real time application.

Publication: IEICE TRANSACTIONS on Communications Vol.E96-B No.5 pp.1202-1210

Publication Date: 2013/05/01

Publicized

Online ISSN: 1745-1345

DOI: 10.1587/transcom.E96.B.1202

Type of Manuscript: PAPER

Category: Sensing

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Yong Hwi KIM, Ka Hyung CHOI, Tae Sung YOON, Jin Bae PARK, "Target Localization Using Instrumental Variable Method in Sensor Network" in IEICE TRANSACTIONS on Communications, vol. E96-B, no. 5, pp. 1202-1210, May 2013, doi: 10.1587/transcom.E96.B.1202.
Abstract: An instrumental variable (IV) based linear estimator is proposed for effective target localization in sensor network by using time-difference-of-arrival (TDOA) measurement. Although some linear estimation approaches have been proposed in much literature, the target localization based on TDOA measurement still has a room for improvement. Therefore, we analyze the estimation errors of existing localization estimators such as the well-known quadratic correction least squares (QCLS) and the robust least squares (RoLS), and demonstrate advantages of the proposition by comparing the estimation errors mathematically and showing localization results through simulation. In addition, a recursive form of the proposition is derived to consider a real time application.
URL: https://globals.ieice.org/en_transactions/communications/10.1587/transcom.E96.B.1202/_p

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@ARTICLE{e96-b_5_1202,
author={Yong Hwi KIM, Ka Hyung CHOI, Tae Sung YOON, Jin Bae PARK, },
journal={IEICE TRANSACTIONS on Communications},
title={Target Localization Using Instrumental Variable Method in Sensor Network},
year={2013},
volume={E96-B},
number={5},
pages={1202-1210},
abstract={An instrumental variable (IV) based linear estimator is proposed for effective target localization in sensor network by using time-difference-of-arrival (TDOA) measurement. Although some linear estimation approaches have been proposed in much literature, the target localization based on TDOA measurement still has a room for improvement. Therefore, we analyze the estimation errors of existing localization estimators such as the well-known quadratic correction least squares (QCLS) and the robust least squares (RoLS), and demonstrate advantages of the proposition by comparing the estimation errors mathematically and showing localization results through simulation. In addition, a recursive form of the proposition is derived to consider a real time application.},
keywords={},
doi={10.1587/transcom.E96.B.1202},
ISSN={1745-1345},
month={May},}

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TY - JOUR
TI - Target Localization Using Instrumental Variable Method in Sensor Network
T2 - IEICE TRANSACTIONS on Communications
SP - 1202
EP - 1210
AU - Yong Hwi KIM
AU - Ka Hyung CHOI
AU - Tae Sung YOON
AU - Jin Bae PARK
PY - 2013
DO - 10.1587/transcom.E96.B.1202
JO - IEICE TRANSACTIONS on Communications
SN - 1745-1345
VL - E96-B
IS - 5
JA - IEICE TRANSACTIONS on Communications
Y1 - May 2013
AB - An instrumental variable (IV) based linear estimator is proposed for effective target localization in sensor network by using time-difference-of-arrival (TDOA) measurement. Although some linear estimation approaches have been proposed in much literature, the target localization based on TDOA measurement still has a room for improvement. Therefore, we analyze the estimation errors of existing localization estimators such as the well-known quadratic correction least squares (QCLS) and the robust least squares (RoLS), and demonstrate advantages of the proposition by comparing the estimation errors mathematically and showing localization results through simulation. In addition, a recursive form of the proposition is derived to consider a real time application.
ER -