Adaptive special strategies resampling for inertial-based mobile indoor positioning systems: an initial proposal

The phenomenon of sample impoverishment during particle filtering always contribute computation burden to the inertial-based mobile IPS systems. This is due to the factor of noise measurement and number of particle. Usually, the special strategies resampling algorithms was used. However, these algor...

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Bibliographic Details
Main Authors: Bejuri, W. M. Y. W., Murtadha Mohamad, M., Radzi, R. Z. R. M., Salleh, M., Yusof, A. F.
Format: Article
Published: Science and Engineering Research Support Society 2017
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Online Access:http://eprints.utm.my/id/eprint/76354/
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85033360262&doi=10.14257%2fijca.2017.10.10.10&partnerID=40&md5=30a597bdcc6a9126a266a4d0ce76dd7e
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Summary:The phenomenon of sample impoverishment during particle filtering always contribute computation burden to the inertial-based mobile IPS systems. This is due to the factor of noise measurement and number of particle. Usually, the special strategies resampling algorithms was used. However, these algorithms just can fit in certain environment. This needs an adaptation of noise measurement and number of particle in a algorithm in order to make resampling with more intelligence, reliability and robust. In this paper, we will propose an adaptive special strategies resampling by adapting noise and particle measurement. These adaptation is used to determine the most suitable algorithm of special strategies resampling, that can be switched for resampling purpose. Finally, we illustrate our proposed solution our for indoor environment setup.