Fast and robust stratified self-calibration using time-difference-of-arrival measurements

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2 Citations (SciVal)

Abstract

In this paper we study the problem of estimating receiver and sender positions using time-difference-of-arrival measurements. For this, we use a stratified, two-tiered approach. In the first step the problem is converted to a low-rank matrix estimation problem. We present new, efficient solvers for the minimal problems of this low-rank problem. These solvers are used in a hypothesis and test manner to efficiently remove outliers and find an initial estimate which is used for the subsequent step. Once a promising solution is obtained for a sufficiently large subset of the receivers and senders, the solution can be extended to the remaining receivers and senders. These steps are then combined with robust local optimization using the initial inlier set and the initial estimate as a starting point. The proposed system is verified on both real and synthetic data.

Original languageEnglish
Title of host publicationInternational Conference on Acoustics, Speech, and Signal Processing (ICASSP)
Pages4640-4644
Number of pages5
Volume2021-June
ISBN (Electronic)978-1-7281-7605-5
DOIs
Publication statusPublished - 2021
EventIEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2021 - Toronto, Canada
Duration: 2021 Jun 62021 Jun 11

Publication series

NameICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
ISSN (Print)1520-6149

Conference

ConferenceIEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2021
Country/TerritoryCanada
CityToronto
Period2021/06/062021/06/11

Subject classification (UKÄ)

  • Control Engineering

Keywords

  • Minimal problems
  • RANSAC
  • Self-calibration
  • TDOA

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