Hybrid TDOA and AOA Localization Using Constrained Least Squares

Jungkeun OH; Kyunghyun LEE; Kwanho YOU

doi:10.1587/transfun.E98.A.2713

Hybrid TDOA and AOA Localization Using Constrained Least Squares

Jungkeun OH, Kyunghyun LEE, Kwanho YOU

Full Text Views

0

Cite this

Summary :

In this paper, we propose a localization algorithm that uses the time difference of arrival (TDOA) and the angle of arrival (AOA). The problem is formulated in a hybrid linear matrix equation. TDOA and AOA measurements are used for estimating the target's position. Although it is known that the accuracy of TDOA based localization is superior to that of AOA based localization, TDOA based localization has a poor vertical accuracy in deteriorated geometrical conditions. This paper, therefore, proposes a localization algorithm in which the vertical position is estimated by AOA measurements and the horizontal position is estimated by TDOA measurement in order to achieve high location accuracy in three dimensions. In addition, the Lagrange multipliers are obtained efficiently and robustly. The simulation analysis shows that the proposed constrained linear squares (CLS) algorithm is an unbiased estimator, and that it approaches the Cramer-Rao lower bound (CRLB) when the measurement noise and the sensor's location errors are sufficiently small.

Publication: IEICE TRANSACTIONS on Fundamentals Vol.E98-A No.12 pp.2713-2718

Publication Date: 2015/12/01

Publicized

Online ISSN: 1745-1337

DOI: 10.1587/transfun.E98.A.2713

Type of Manuscript: LETTER

Category: Systems and Control

Authors

Jungkeun OH
  Sungkyunkwan Univ.
Kyunghyun LEE
  Sungkyunkwan Univ.
Kwanho YOU
  Sungkyunkwan Univ.

Keyword

time difference of arrival, angle of arrival, constrained least square, localization, CRLB

Cite this

Copy

Jungkeun OH, Kyunghyun LEE, Kwanho YOU, "Hybrid TDOA and AOA Localization Using Constrained Least Squares" in IEICE TRANSACTIONS on Fundamentals, vol. E98-A, no. 12, pp. 2713-2718, December 2015, doi: 10.1587/transfun.E98.A.2713.
Abstract: In this paper, we propose a localization algorithm that uses the time difference of arrival (TDOA) and the angle of arrival (AOA). The problem is formulated in a hybrid linear matrix equation. TDOA and AOA measurements are used for estimating the target's position. Although it is known that the accuracy of TDOA based localization is superior to that of AOA based localization, TDOA based localization has a poor vertical accuracy in deteriorated geometrical conditions. This paper, therefore, proposes a localization algorithm in which the vertical position is estimated by AOA measurements and the horizontal position is estimated by TDOA measurement in order to achieve high location accuracy in three dimensions. In addition, the Lagrange multipliers are obtained efficiently and robustly. The simulation analysis shows that the proposed constrained linear squares (CLS) algorithm is an unbiased estimator, and that it approaches the Cramer-Rao lower bound (CRLB) when the measurement noise and the sensor's location errors are sufficiently small.
URL: https://global.ieice.org/en_transactions/fundamentals/10.1587/transfun.E98.A.2713/_p

Copy

@ARTICLE{e98-a_12_2713,
author={Jungkeun OH, Kyunghyun LEE, Kwanho YOU, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={Hybrid TDOA and AOA Localization Using Constrained Least Squares},
year={2015},
volume={E98-A},
number={12},
pages={2713-2718},
abstract={In this paper, we propose a localization algorithm that uses the time difference of arrival (TDOA) and the angle of arrival (AOA). The problem is formulated in a hybrid linear matrix equation. TDOA and AOA measurements are used for estimating the target's position. Although it is known that the accuracy of TDOA based localization is superior to that of AOA based localization, TDOA based localization has a poor vertical accuracy in deteriorated geometrical conditions. This paper, therefore, proposes a localization algorithm in which the vertical position is estimated by AOA measurements and the horizontal position is estimated by TDOA measurement in order to achieve high location accuracy in three dimensions. In addition, the Lagrange multipliers are obtained efficiently and robustly. The simulation analysis shows that the proposed constrained linear squares (CLS) algorithm is an unbiased estimator, and that it approaches the Cramer-Rao lower bound (CRLB) when the measurement noise and the sensor's location errors are sufficiently small.},
keywords={},
doi={10.1587/transfun.E98.A.2713},
ISSN={1745-1337},
month={December},}

Copy

TY - JOUR
TI - Hybrid TDOA and AOA Localization Using Constrained Least Squares
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 2713
EP - 2718
AU - Jungkeun OH
AU - Kyunghyun LEE
AU - Kwanho YOU
PY - 2015
DO - 10.1587/transfun.E98.A.2713
JO - IEICE TRANSACTIONS on Fundamentals
SN - 1745-1337
VL - E98-A
IS - 12
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - December 2015
AB - In this paper, we propose a localization algorithm that uses the time difference of arrival (TDOA) and the angle of arrival (AOA). The problem is formulated in a hybrid linear matrix equation. TDOA and AOA measurements are used for estimating the target's position. Although it is known that the accuracy of TDOA based localization is superior to that of AOA based localization, TDOA based localization has a poor vertical accuracy in deteriorated geometrical conditions. This paper, therefore, proposes a localization algorithm in which the vertical position is estimated by AOA measurements and the horizontal position is estimated by TDOA measurement in order to achieve high location accuracy in three dimensions. In addition, the Lagrange multipliers are obtained efficiently and robustly. The simulation analysis shows that the proposed constrained linear squares (CLS) algorithm is an unbiased estimator, and that it approaches the Cramer-Rao lower bound (CRLB) when the measurement noise and the sensor's location errors are sufficiently small.
ER -