Fingerprint- And kalman filter-based localization exploiting reference signal received power calibration

Chahyeon Eom, Sunghoon Jung, Chaehun Im, Chungyong Lee

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)

Abstract

This paper proposes a localization scheme exploiting reference signal received power (RSRP) for estimation of the next location. The proposed scheme can correct outliers without discarding data by adding RSRP as a state vector for a Kalman filter, and combining the Kalman filter with fingerprint-based localization. Performance evaluation is carried out via simulations in indoor environments. Results indicate that the proposed scheme can effectively correct outliers and enhance positioning accuracy. The root mean square error in the positioning error was reduced by 56%, compared to the conventional fingerprint-based localization schemes for indoor environments.

Original languageEnglish
Pages (from-to)238-243
Number of pages6
JournalIEIE Transactions on Smart Processing and Computing
Volume9
Issue number3
DOIs
Publication statusPublished - 2020 Jun

Bibliographical note

Funding Information:
This work was supported by a National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT) (NRF-2019R1A2C1010950).

Funding Information:
This research was supported in part by Basic Science

Funding Information:
This research was supported by the Tongmyong University Research Grants2019(2019F002) and Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education(NRF-2018R1D1A1B07048080)

Funding Information:
This work was supported by Institute of Information & Communications Technology Planning & Evaluation (IITP) grant funded by the Korean government (MSIT) (No.2018-0-00189, Security Technology for Portal Device that connects Human-Infrastructure-Service in highly trust intelligent information service)

Publisher Copyright:
© 2020 Institute of Electronics and Information Engineers. All rights reserved.

All Science Journal Classification (ASJC) codes

  • Signal Processing
  • Electrical and Electronic Engineering

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