Improving location estimation with two-tier particle filtering in mobile wireless environment

Kwangjae Sung, Suk Kyu Lee, Hwangnam Kim

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

A particle filter is a sequential Monte Carlo method that is superior in estimating the state of a dynamic system under nonlinear/non-Gaussian circumstance. Due to its nature, a particle filter has been regarded as an appropriate algorithm for localization. However, conventional problems, such as sample impoverishment and degeneracy problem, have not been perfectly solved yet. To solve these problems in mobile wireless environment, we propose an enhanced localization scheme, called Gaussian kernel density estimation-based particle filtering (GKPF), which calculates the target distribution (for location estimation) based on nonparametric technique. In order to estimate the target distribution, the GKPF algorithm creates both unimodal and multimodal distributions based on particle representations, and it calculates a pdf for each distribution with Gaussian kernel-density estimation. Simulation study indicates that the proposed GKPE scheme can accurately estimate the location in mobile wireless environment.

Original languageEnglish
Title of host publicationProceedings - International Conference on Computer Communications and Networks, ICCCN
DOIs
Publication statusPublished - 2011 Sep 26
Event2011 20th International Conference on Computer Communications and Networks, ICCCN 2011 - Maui, HI, United States
Duration: 2011 Jul 312011 Aug 4

Other

Other2011 20th International Conference on Computer Communications and Networks, ICCCN 2011
CountryUnited States
CityMaui, HI
Period11/7/3111/8/4

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ASJC Scopus subject areas

  • Computer Networks and Communications
  • Hardware and Architecture
  • Software

Cite this

Sung, K., Lee, S. K., & Kim, H. (2011). Improving location estimation with two-tier particle filtering in mobile wireless environment. In Proceedings - International Conference on Computer Communications and Networks, ICCCN [6006052] https://doi.org/10.1109/ICCCN.2011.6006052