Multiple-source ellipsoidal localization using acoustic energy measurements

Fanqin Meng, Xiaojing Shen, Zhiguo Wang, Haiqi Liu, Junfeng Wang, Yunmin Zhu, Pramod K. Varshney

Research output: Contribution to journalArticle

Abstract

In this paper, the multiple-source ellipsoidal localization problem based on acoustic energy measurements is investigated via set-membership estimation theory. When the probability density function of measurement noise is unknown-but-bounded, multiple-source localization is a difficult problem since not only the acoustic energy measurements are complicated nonlinear functions of multiple sources, but also the multiple sources bring about a high-dimensional state estimation problem. First, when the energy parameter and the position of the source are bounded in an interval and a ball respectively, the nonlinear remainder bound of the Taylor series expansion is obtained analytically on-line. Next, based on the separability of the nonlinear measurement function, an efficient estimation procedure is developed. It solves the multiple-source localization problem by using an alternating optimization iterative algorithm, in which the remainder bound needs to be known on-line. For this reason, we first derive the remainder bound analytically. When the energy decay factor is unknown but bounded, an efficient estimation procedure is developed based on interval mathematics. Finally, numerical examples demonstrate the effectiveness of the ellipsoidal localization algorithms for multiple-source localization. In particular, our results show that when the noise is non-Gaussian, the set-membership localization algorithm performs better than the EM localization algorithm.

Original languageEnglish (US)
Article number108737
JournalAutomatica
Volume112
DOIs
StatePublished - Feb 2020

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Electric power measurement
Acoustics
Taylor series
State estimation
Probability density function

Keywords

  • Acoustic energy measurements
  • Multiple-source localization
  • Nonlinear measurements
  • Set-membership estimation

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Electrical and Electronic Engineering

Cite this

Multiple-source ellipsoidal localization using acoustic energy measurements. / Meng, Fanqin; Shen, Xiaojing; Wang, Zhiguo; Liu, Haiqi; Wang, Junfeng; Zhu, Yunmin; Varshney, Pramod K.

In: Automatica, Vol. 112, 108737, 02.2020.

Research output: Contribution to journalArticle

Meng, Fanqin ; Shen, Xiaojing ; Wang, Zhiguo ; Liu, Haiqi ; Wang, Junfeng ; Zhu, Yunmin ; Varshney, Pramod K. / Multiple-source ellipsoidal localization using acoustic energy measurements. In: Automatica. 2020 ; Vol. 112.
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