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Wireless Localization with Spatial-Temporal Robust Fingerprints

Published: 22 October 2021 Publication History

Abstract

Indoor localization has gained increasing attention in the era of the Internet of Things. Among various technologies, WiFi fingerprint-based localization has become a mainstream solution. However, RSS fingerprints suffer from critical drawbacks of spatial ambiguity and temporal instability that root in multipath effects and environmental dynamics, which degrade the performance of these systems and therefore impede their wide deployment in the real world. Pioneering works overcome these limitations at the costs of ubiquity as they mostly resort to additional information or extra user constraints. In this article, we present the design and implementation of ViViPlus, an indoor localization system purely based on WiFi fingerprints, which jointly mitigates spatial ambiguity and temporal instability and derives reliable performance without impairing the ubiquity. The key idea is to embrace the spatial awareness of RSS values in a novel form of RSS Spatial Gradient (RSG) matrix for enhanced WiFi fingerprints. We devise techniques for the representation, construction, and localization of the proposed fingerprint form and integrate them all in a practical system. Extensive experiments across 7 months in different environments demonstrate that ViViPlus significantly improves the accuracy in localization scenarios by about 30% to 50% compared with the state-of-the-art approaches.

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      cover image ACM Transactions on Sensor Networks
      ACM Transactions on Sensor Networks  Volume 18, Issue 1
      February 2022
      434 pages
      ISSN:1550-4859
      EISSN:1550-4867
      DOI:10.1145/3484935
      Issue’s Table of Contents
      Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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      Publication History

      Published: 22 October 2021
      Accepted: 01 August 2021
      Revised: 01 August 2021
      Received: 01 April 2021
      Published in TOSN Volume 18, Issue 1

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      Author Tags

      1. Indoor localization
      2. RSS fingerprint
      3. spatial gradient

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      • (2024)Multimodal Dialogue Systems via Capturing Context-aware Dependencies and Ordinal Information of Semantic ElementsACM Transactions on Intelligent Systems and Technology10.1145/364509915:3(1-25)Online publication date: 15-Apr-2024
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