PLS initialized sequential estimator for target localization using AOA measurements

Yanzi Wang; Zhansheng Duan

doi:10.1109/CIVEMSA.2015.7158617

PLS initialized sequential estimator for target localization using AOA measurements

Yanzi Wang
, Zhansheng Duan

Faculty of Electronic and Information Engineering

Xi'an Jiaotong University

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

5 Scopus citations

Abstract

Target localization using AOA measurements has attracted substantial attention for several decades. Traditional algorithms regard the target position as a non-random parameter and employ estimators like least squares (LS) or maximum likelihood (ML) to estimate the target location. In this paper, we propose a new framework for target localization using AOA measurements. The idea of this framework is to treat the unknown position as a random vector and then use the linear minimum mean square error (LMMSE) criterion to obtain an estimator that sequentially fuses the AOA measurements from multiple sensors. The key difficulty of this criterion is how to determine the prior first two moments of the unknown location. This is tackled by pseudo-linear least squares (PLS), which is verified to be perfectly credible through three credibility measures. Extensive numerical examples show that the PLS initialized sequential estimator outperforms the existing PLS and its root-mean-square error (RMSE) is close to the Cramer-Rao lower bound (CRLB) in most cases.

Original language	English
Title of host publication	2015 IEEE International Conference on Computational Intelligence and Virtual Environments for Measurement Systems and Applications, CIVEMSA 2015
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9781479960910
DOIs	https://doi.org/10.1109/CIVEMSA.2015.7158617
State	Published - 14 Jul 2015
Event	2015 IEEE International Conference on Computational Intelligence and Virtual Environments for Measurement Systems and Applications, CIVEMSA 2015 - Shenzhen, China Duration: 12 Jun 2015 → 14 Jun 2015

Publication series

Name	2015 IEEE International Conference on Computational Intelligence and Virtual Environments for Measurement Systems and Applications, CIVEMSA 2015

Conference

Conference	2015 IEEE International Conference on Computational Intelligence and Virtual Environments for Measurement Systems and Applications, CIVEMSA 2015
Country/Territory	China
City	Shenzhen
Period	12/06/15 → 14/06/15

Keywords

angle of arrival
credibility measure
pseudo-linear least squares
sequential estimator
target localization

Access to Document

10.1109/CIVEMSA.2015.7158617

Cite this

Wang, Y., & Duan, Z. (2015). PLS initialized sequential estimator for target localization using AOA measurements. In 2015 IEEE International Conference on Computational Intelligence and Virtual Environments for Measurement Systems and Applications, CIVEMSA 2015 Article 7158617 (2015 IEEE International Conference on Computational Intelligence and Virtual Environments for Measurement Systems and Applications, CIVEMSA 2015). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/CIVEMSA.2015.7158617

Wang, Yanzi ; Duan, Zhansheng. / PLS initialized sequential estimator for target localization using AOA measurements. 2015 IEEE International Conference on Computational Intelligence and Virtual Environments for Measurement Systems and Applications, CIVEMSA 2015. Institute of Electrical and Electronics Engineers Inc., 2015. (2015 IEEE International Conference on Computational Intelligence and Virtual Environments for Measurement Systems and Applications, CIVEMSA 2015).

@inproceedings{282b99cf3bdd487e841bc135a0524a2d,

title = "PLS initialized sequential estimator for target localization using AOA measurements",

abstract = "Target localization using AOA measurements has attracted substantial attention for several decades. Traditional algorithms regard the target position as a non-random parameter and employ estimators like least squares (LS) or maximum likelihood (ML) to estimate the target location. In this paper, we propose a new framework for target localization using AOA measurements. The idea of this framework is to treat the unknown position as a random vector and then use the linear minimum mean square error (LMMSE) criterion to obtain an estimator that sequentially fuses the AOA measurements from multiple sensors. The key difficulty of this criterion is how to determine the prior first two moments of the unknown location. This is tackled by pseudo-linear least squares (PLS), which is verified to be perfectly credible through three credibility measures. Extensive numerical examples show that the PLS initialized sequential estimator outperforms the existing PLS and its root-mean-square error (RMSE) is close to the Cramer-Rao lower bound (CRLB) in most cases.",

keywords = "angle of arrival, credibility measure, pseudo-linear least squares, sequential estimator, target localization",

author = "Yanzi Wang and Zhansheng Duan",

note = "Publisher Copyright: {\textcopyright} 2015 IEEE.; 2015 IEEE International Conference on Computational Intelligence and Virtual Environments for Measurement Systems and Applications, CIVEMSA 2015 ; Conference date: 12-06-2015 Through 14-06-2015",

year = "2015",

month = jul,

day = "14",

doi = "10.1109/CIVEMSA.2015.7158617",

language = "英语",

series = "2015 IEEE International Conference on Computational Intelligence and Virtual Environments for Measurement Systems and Applications, CIVEMSA 2015",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

booktitle = "2015 IEEE International Conference on Computational Intelligence and Virtual Environments for Measurement Systems and Applications, CIVEMSA 2015",

}

Wang, Y & Duan, Z 2015, PLS initialized sequential estimator for target localization using AOA measurements. in 2015 IEEE International Conference on Computational Intelligence and Virtual Environments for Measurement Systems and Applications, CIVEMSA 2015., 7158617, 2015 IEEE International Conference on Computational Intelligence and Virtual Environments for Measurement Systems and Applications, CIVEMSA 2015, Institute of Electrical and Electronics Engineers Inc., 2015 IEEE International Conference on Computational Intelligence and Virtual Environments for Measurement Systems and Applications, CIVEMSA 2015, Shenzhen, China, 12/06/15. https://doi.org/10.1109/CIVEMSA.2015.7158617

PLS initialized sequential estimator for target localization using AOA measurements. / Wang, Yanzi; Duan, Zhansheng.
2015 IEEE International Conference on Computational Intelligence and Virtual Environments for Measurement Systems and Applications, CIVEMSA 2015. Institute of Electrical and Electronics Engineers Inc., 2015. 7158617 (2015 IEEE International Conference on Computational Intelligence and Virtual Environments for Measurement Systems and Applications, CIVEMSA 2015).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - PLS initialized sequential estimator for target localization using AOA measurements

AU - Wang, Yanzi

AU - Duan, Zhansheng

PY - 2015/7/14

Y1 - 2015/7/14

N2 - Target localization using AOA measurements has attracted substantial attention for several decades. Traditional algorithms regard the target position as a non-random parameter and employ estimators like least squares (LS) or maximum likelihood (ML) to estimate the target location. In this paper, we propose a new framework for target localization using AOA measurements. The idea of this framework is to treat the unknown position as a random vector and then use the linear minimum mean square error (LMMSE) criterion to obtain an estimator that sequentially fuses the AOA measurements from multiple sensors. The key difficulty of this criterion is how to determine the prior first two moments of the unknown location. This is tackled by pseudo-linear least squares (PLS), which is verified to be perfectly credible through three credibility measures. Extensive numerical examples show that the PLS initialized sequential estimator outperforms the existing PLS and its root-mean-square error (RMSE) is close to the Cramer-Rao lower bound (CRLB) in most cases.

AB - Target localization using AOA measurements has attracted substantial attention for several decades. Traditional algorithms regard the target position as a non-random parameter and employ estimators like least squares (LS) or maximum likelihood (ML) to estimate the target location. In this paper, we propose a new framework for target localization using AOA measurements. The idea of this framework is to treat the unknown position as a random vector and then use the linear minimum mean square error (LMMSE) criterion to obtain an estimator that sequentially fuses the AOA measurements from multiple sensors. The key difficulty of this criterion is how to determine the prior first two moments of the unknown location. This is tackled by pseudo-linear least squares (PLS), which is verified to be perfectly credible through three credibility measures. Extensive numerical examples show that the PLS initialized sequential estimator outperforms the existing PLS and its root-mean-square error (RMSE) is close to the Cramer-Rao lower bound (CRLB) in most cases.

KW - angle of arrival

KW - credibility measure

KW - pseudo-linear least squares

KW - sequential estimator

KW - target localization

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BT - 2015 IEEE International Conference on Computational Intelligence and Virtual Environments for Measurement Systems and Applications, CIVEMSA 2015

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2015 IEEE International Conference on Computational Intelligence and Virtual Environments for Measurement Systems and Applications, CIVEMSA 2015

Y2 - 12 June 2015 through 14 June 2015

ER -

Wang Y, Duan Z. PLS initialized sequential estimator for target localization using AOA measurements. In 2015 IEEE International Conference on Computational Intelligence and Virtual Environments for Measurement Systems and Applications, CIVEMSA 2015. Institute of Electrical and Electronics Engineers Inc. 2015. 7158617. (2015 IEEE International Conference on Computational Intelligence and Virtual Environments for Measurement Systems and Applications, CIVEMSA 2015). doi: 10.1109/CIVEMSA.2015.7158617

PLS initialized sequential estimator for target localization using AOA measurements

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