Improving Reliability of Particle Filter-Based Localization in Wireless Sensor Networks via Hybrid Particle/FIR Filtering

Jung Min Pak, Choon Ki Ahn, Yuriy S. Shmaliy, Myo Taeg Lim

Research output: Contribution to journalArticle

134 Citations (Scopus)

Abstract

The need for accurate, fast, and reliable indoor localization using wireless sensor networks (WSNs) has recently grown in diverse areas of industry. Accurate localization in cluttered and noisy environments is commonly provided by means of a mathematical algorithm referred to as a state estimator or filter. The particle filter (PF), which is the most commonly used filter in localization, suffers from the sample impoverishment problem under typical conditions of real-time localization based on WSNs. This paper proposes a novel hybrid particle/finite impulse response (FIR) filtering algorithm for improving reliability of PF-based localization schemes under harsh conditions causing sample impoverishment. The hybrid particle/FIR filter detects the PF failures and recovers the failed PF by resetting the PF using the output of an auxiliary FIR filter. Combining the regularized particle filter (RPF) and the extended unbiased FIR (EFIR) filter, the hybrid RP/EFIR filter is constructed in this paper. Through simulations, the hybrid RP/EFIR filter demonstrates its improved reliability and ability to recover the RPF from failures.

Original languageEnglish
Article number7173021
Pages (from-to)1089-1098
Number of pages10
JournalIEEE Transactions on Industrial Informatics
Volume11
Issue number5
DOIs
Publication statusPublished - 2015 Oct 1

Keywords

  • hybrid particle/FIR filter
  • hybrid RP/EFIR filter
  • Indoor localization
  • wireless sensor network (WSN)

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Control and Systems Engineering
  • Computer Science Applications
  • Information Systems

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