E-SALDAT: Efficient Single-Anchor Localization of Dual-Antenna Tags

Leo Happ Botler, Konrad Diwold, Kay Uwe Römer

Research output: Chapter in Book/Report/Conference proceedingConference paperpeer-review

Abstract

Accurate localization is required to enable location awareness of devices in many IoT applications. Current state-of-the-art ultra-wideband solutions make use of ranging measurements in a multi-anchor setup. In this paper, we propose a novel single-anchor scheme (E-SALDAT): an improvement of the Dual Wireless Radio Localization (DWRL). While four ranging measurements were previously required for semi-localization (usually,the first step towards definite localization/rigid-localization), E-SALDAT allows for semi-localization with only two ranging measurements. This results in a significant improvement of overall power efficiency and localization ratio. We present a comparison
of the proposed localization scheme E-SALDAT to its predecessors I-DWRL and DWRL. The comparison was performed based on simulations. Our results suggest that E-SALDAT, on average, can achieve double the localization ratio of
I-DWRL with just 23 % more messages
Original languageEnglish
Title of host publication2019 16th Workshop on Positioning, Navigation and Communication, WPNC 2019
PublisherIEEE Xplore
Number of pages6
ISBN (Electronic)978-1-7281-2082-9
DOIs
Publication statusPublished - 30 Mar 2020
EventIEEE 16th Workshop on Positioning, Navigation and Communications - Bremen, Bremen, Germany
Duration: 23 Oct 201924 Oct 2019
https://wpnc.info/

Workshop

WorkshopIEEE 16th Workshop on Positioning, Navigation and Communications
Abbreviated titleWPNC'19
Country/TerritoryGermany
CityBremen
Period23/10/1924/10/19
Internet address

Keywords

  • Localization, single-anchor, UWB, sensor net- work, IoT
  • UWB
  • Single-anchor
  • Sensor network
  • Localization
  • IoT

ASJC Scopus subject areas

  • Control and Optimization
  • Instrumentation
  • Computer Networks and Communications

Fields of Expertise

  • Information, Communication & Computing

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