Performance analysis of the robust least squares target localization scheme using RDOA measurements

Ka Hyung Choi, Won Sang Ra, Jin Bae Park, Tae Sung Yoon

Research output: Contribution to journalArticle

Abstract

A practical recursive linear robust estimation scheme is proposed for target localization in the sensor network which provides range difference of arrival (RDOA) measurements. In order to radically solve the known practical difficulties such as sensitivity for initial guess and heavy computational burden caused by intrinsic nonlinearity of the RDOA based target localization problem, an uncertain linear measurement model is newly derived. In the suggested problem setting, the target localization performance of the conventional linear estimation schemes might be severely degraded under the low SNR condition and be affected by the target position in the sensor network. This motivates us to devise a new sensor network localization algorithm within the framework of the recently developed robust least squares estimation theory. Provided that the statistical information regarding RDOA measurements are available, the estimate of the proposition method shows the convergence in probability to the true target position. Through the computer simulations, the omni-directional target localization performance and consistency of the proposed algorithm are compared to those of the existing ones. It is shown that the proposed method is more reliable than the total least squares method and the linear correction least squares method.

Original languageEnglish
Pages (from-to)606-614
Number of pages9
JournalJournal of Electrical Engineering and Technology
Volume7
Issue number4
DOIs
Publication statusPublished - 2012 Jul 1

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Sensor networks
Computer simulation

All Science Journal Classification (ASJC) codes

  • Electrical and Electronic Engineering

Cite this

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abstract = "A practical recursive linear robust estimation scheme is proposed for target localization in the sensor network which provides range difference of arrival (RDOA) measurements. In order to radically solve the known practical difficulties such as sensitivity for initial guess and heavy computational burden caused by intrinsic nonlinearity of the RDOA based target localization problem, an uncertain linear measurement model is newly derived. In the suggested problem setting, the target localization performance of the conventional linear estimation schemes might be severely degraded under the low SNR condition and be affected by the target position in the sensor network. This motivates us to devise a new sensor network localization algorithm within the framework of the recently developed robust least squares estimation theory. Provided that the statistical information regarding RDOA measurements are available, the estimate of the proposition method shows the convergence in probability to the true target position. Through the computer simulations, the omni-directional target localization performance and consistency of the proposed algorithm are compared to those of the existing ones. It is shown that the proposed method is more reliable than the total least squares method and the linear correction least squares method.",
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Performance analysis of the robust least squares target localization scheme using RDOA measurements. / Choi, Ka Hyung; Ra, Won Sang; Park, Jin Bae; Yoon, Tae Sung.

In: Journal of Electrical Engineering and Technology, Vol. 7, No. 4, 01.07.2012, p. 606-614.

Research output: Contribution to journalArticle

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