A Linear-Correction Method for TDOA and FDOA-Based Moving Source Localization
Summary :
A linear-correction method is developed for source position and velocity estimation using time difference of arrival (TDOA) and frequency difference of arrival (FDOA) measurements. The proposed technique first obtains an initial source location estimate using the first-step processing of an existing algebraic algorithm. It then refines the initial localization result by estimating via weighted least-squares (WLS) optimization and subtracting out its estimation error. The new solution is shown to be able to achieve the Cramer-Rao lower bound (CRLB) accuracy and it has better accuracy over several benchmark methods at relatively high noise levels.
- Publication
- IEICE TRANSACTIONS on Fundamentals Vol.E100-A No.4 pp.1066-1069
- Publication Date
- 2017/04/01
- Publicized
- Online ISSN
- 1745-1337
- DOI
- 10.1587/transfun.E100.A.1066
- Type of Manuscript
- LETTER
- Category
- Digital Signal Processing
Authors
Bing DENG
the Zhengzhou Institute of Information Science and Technology,the National Key Laboratory of Science and Technology on Blind Signal Processing
Zhengbo SUN
the National Key Laboratory of Science and Technology on Blind Signal Processing
Le YANG
Jiangnan University
Dexiu HU
the Zhengzhou Institute of Information Science and Technology
Keyword
Latest Issue
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Bing DENG, Zhengbo SUN, Le YANG, Dexiu HU, "A Linear-Correction Method for TDOA and FDOA-Based Moving Source Localization" in IEICE TRANSACTIONS on Fundamentals,
vol. E100-A, no. 4, pp. 1066-1069, April 2017, doi: 10.1587/transfun.E100.A.1066.
Abstract: A linear-correction method is developed for source position and velocity estimation using time difference of arrival (TDOA) and frequency difference of arrival (FDOA) measurements. The proposed technique first obtains an initial source location estimate using the first-step processing of an existing algebraic algorithm. It then refines the initial localization result by estimating via weighted least-squares (WLS) optimization and subtracting out its estimation error. The new solution is shown to be able to achieve the Cramer-Rao lower bound (CRLB) accuracy and it has better accuracy over several benchmark methods at relatively high noise levels.
URL: https://global.ieice.org/en_transactions/fundamentals/10.1587/transfun.E100.A.1066/_p
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@ARTICLE{e100-a_4_1066,
author={Bing DENG, Zhengbo SUN, Le YANG, Dexiu HU, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={A Linear-Correction Method for TDOA and FDOA-Based Moving Source Localization},
year={2017},
volume={E100-A},
number={4},
pages={1066-1069},
abstract={A linear-correction method is developed for source position and velocity estimation using time difference of arrival (TDOA) and frequency difference of arrival (FDOA) measurements. The proposed technique first obtains an initial source location estimate using the first-step processing of an existing algebraic algorithm. It then refines the initial localization result by estimating via weighted least-squares (WLS) optimization and subtracting out its estimation error. The new solution is shown to be able to achieve the Cramer-Rao lower bound (CRLB) accuracy and it has better accuracy over several benchmark methods at relatively high noise levels.},
keywords={},
doi={10.1587/transfun.E100.A.1066},
ISSN={1745-1337},
month={April},}
Copy
TY - JOUR
TI - A Linear-Correction Method for TDOA and FDOA-Based Moving Source Localization
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 1066
EP - 1069
AU - Bing DENG
AU - Zhengbo SUN
AU - Le YANG
AU - Dexiu HU
PY - 2017
DO - 10.1587/transfun.E100.A.1066
JO - IEICE TRANSACTIONS on Fundamentals
SN - 1745-1337
VL - E100-A
IS - 4
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - April 2017
AB - A linear-correction method is developed for source position and velocity estimation using time difference of arrival (TDOA) and frequency difference of arrival (FDOA) measurements. The proposed technique first obtains an initial source location estimate using the first-step processing of an existing algebraic algorithm. It then refines the initial localization result by estimating via weighted least-squares (WLS) optimization and subtracting out its estimation error. The new solution is shown to be able to achieve the Cramer-Rao lower bound (CRLB) accuracy and it has better accuracy over several benchmark methods at relatively high noise levels.
ER -
English
