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 journalArticlepeer-review

46 Citations (Scopus)


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 languageEnglish
Article number7588034
Pages (from-to)332-342
Number of pages11
JournalIEEE Transactions on Human-Machine Systems
Issue number3
Publication statusPublished - 2017 Jun

Bibliographical 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:
© 2016 IEEE.


  • 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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