Accurate and Reliable Human Localization Using Composite Particle/FIR Filtering

Jung Min Pak; Choon Ki Ahn; Yuriy S. Shmaliy; Peng Shi; Myo Taeg Lim

doi:10.1109/THMS.2016.2611826

Accurate and Reliable Human Localization Using Composite Particle/FIR Filtering

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

Research output: Contribution to journal › Article › peer-review

40 Citations (Scopus)

Abstract

The particle filter (PF) is a popular filtering algorithm in various localization problems represented by nonlinear state-space models. Although the PF can provide accurate localization results, it often fails in localization because of the sample impoverishment phenomenon. In this paper, we propose a novel nonlinear filtering method that combines a PF with a robust filter, called a finite impulse response (FIR) filter, in order to accomplish accurate and reliable localization. The proposed filter is called the composite particle/FIR filter (CPFF). In the CPFF framework, the PF is the main filter used in normal situations. When PF failures occur, the FIR filter is used to recover the PF from failures. To detect PF failures, a new decision-making algorithm is proposed in this paper. The proposed CPFF is applied to indoor human localization using a wireless sensor network. The CPFF is accurate and reliable under conditions in which the pure PF typically exhibits degraded accuracy or failures in localization.

Original language	English
Article number	7588034
Pages (from-to)	332-342
Number of pages	11
Journal	IEEE Transactions on Human-Machine Systems
Volume	47
Issue number	3
DOIs	https://doi.org/10.1109/THMS.2016.2611826
Publication status	Published - 2017 Jun

Keywords

Composite particle/finite impulse response (FIR) filter (CPFF)
human localization
particle filter (PF)

ASJC Scopus subject areas

Human Factors and Ergonomics
Control and Systems Engineering
Signal Processing
Human-Computer Interaction
Computer Science Applications
Computer Networks and Communications
Artificial Intelligence

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10.1109/THMS.2016.2611826

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title = "Accurate and Reliable Human Localization Using Composite Particle/FIR Filtering",

abstract = "The particle filter (PF) is a popular filtering algorithm in various localization problems represented by nonlinear state-space models. Although the PF can provide accurate localization results, it often fails in localization because of the sample impoverishment phenomenon. In this paper, we propose a novel nonlinear filtering method that combines a PF with a robust filter, called a finite impulse response (FIR) filter, in order to accomplish accurate and reliable localization. The proposed filter is called the composite particle/FIR filter (CPFF). In the CPFF framework, the PF is the main filter used in normal situations. When PF failures occur, the FIR filter is used to recover the PF from failures. To detect PF failures, a new decision-making algorithm is proposed in this paper. The proposed CPFF is applied to indoor human localization using a wireless sensor network. The CPFF is accurate and reliable under conditions in which the pure PF typically exhibits degraded accuracy or failures in localization.",

keywords = "Composite particle/finite impulse response (FIR) filter (CPFF), human localization, particle filter (PF)",

author = "Pak, {Jung Min} and Ahn, {Choon Ki} and Shmaliy, {Yuriy S.} and Peng Shi and Lim, {Myo Taeg}",

note = "Funding Information: This work was supported in part by the Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Science, ICT, and Future Planning under Grant NRF-2014R1A1A1006101, in part by the Basic Science Research Program through the NRF funded by the Ministry of Education under Grant NRF- 2016R1D1A1B01016071, in part by the National Natural Science Foundation of China under Grant 61573112 and Grant U1509217, and in part by the Australian Research Council under Grant DP140102180 and Grant LP140100471. This paper was recommended by Guest Editor L. Chen. Publisher Copyright: {\textcopyright} 2016 IEEE.",

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N1 - Funding Information: This work was supported in part by the Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Science, ICT, and Future Planning under Grant NRF-2014R1A1A1006101, in part by the Basic Science Research Program through the NRF funded by the Ministry of Education under Grant NRF- 2016R1D1A1B01016071, in part by the National Natural Science Foundation of China under Grant 61573112 and Grant U1509217, and in part by the Australian Research Council under Grant DP140102180 and Grant LP140100471. This paper was recommended by Guest Editor L. Chen. Publisher Copyright: © 2016 IEEE.

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Accurate and Reliable Human Localization Using Composite Particle/FIR Filtering

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Keywords

ASJC Scopus subject areas

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