Compensated robust least-squares estimator for target localisation in sensor network using time difference of arrival measurements

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

Research output: Contribution to journalArticle

5 Citations (Scopus)

Abstract

target localisation estimator based on time difference of arrival (TDOA) measurement is proposed. The localisation estimator is designed in the framework of the recently developed robust least-squares (RoLS) estimator, which provides an unbiased estimation result and can be implemented with a recursive filtering structure. However, when the RoLS estimator is applied to the localisation problem, its localisation performance depends on the knowledge of the stochastic information of the TDOA measurement. This dependency means that incorrectly given information causes localisation error. Therefore to complement the dependency of the given stochastic information of the TDOA measurement, we design a compensation procedure based on the constraints on the state variables of the estimator. The performance of the proposition under several cases of incorrectly given stochastic information is verified through computer simulation, and its filtering structure is compared with other existing localisation algorithms mathematically. In addition, the entire process of the proposed localisation estimator is derived as a recursive form for real-time applications.

Original languageEnglish
Pages (from-to)664-673
Number of pages10
JournalIET Signal Processing
Volume7
Issue number8
DOIs
Publication statusPublished - 2013 Sep 30

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Sensor networks
Computer simulation
Time difference of arrival
Compensation and Redress

All Science Journal Classification (ASJC) codes

  • Signal Processing
  • Electrical and Electronic Engineering

Cite this

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title = "Compensated robust least-squares estimator for target localisation in sensor network using time difference of arrival measurements",
abstract = "target localisation estimator based on time difference of arrival (TDOA) measurement is proposed. The localisation estimator is designed in the framework of the recently developed robust least-squares (RoLS) estimator, which provides an unbiased estimation result and can be implemented with a recursive filtering structure. However, when the RoLS estimator is applied to the localisation problem, its localisation performance depends on the knowledge of the stochastic information of the TDOA measurement. This dependency means that incorrectly given information causes localisation error. Therefore to complement the dependency of the given stochastic information of the TDOA measurement, we design a compensation procedure based on the constraints on the state variables of the estimator. The performance of the proposition under several cases of incorrectly given stochastic information is verified through computer simulation, and its filtering structure is compared with other existing localisation algorithms mathematically. In addition, the entire process of the proposed localisation estimator is derived as a recursive form for real-time applications.",
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Compensated robust least-squares estimator for target localisation in sensor network using time difference of arrival measurements. / Choi, Ka Hyung; Ra, Won Sang; Park, Jin Bae; Yoon, Tae Sung.

In: IET Signal Processing, Vol. 7, No. 8, 30.09.2013, p. 664-673.

Research output: Contribution to journalArticle

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