Special Issue — Advanced Materials Development and Performance for its Optimal Application; Guest Editor: Yun-Hae KimNo Access

Localization–compensation algorithm based on the Mean kShift and the Kalman filter

Dong Myung Lee

Department of Computer Engineering, Tongmyong University, 428 Shinseon-ro, Nam-gu, Busan 608-711, Republic of Korea

Corresponding author.

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Tae Wan Kim

Department of Computer Engineering, Tongmyong University, 428 Shinseon-ro, Nam-gu, Busan 608-711, Republic of Korea

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, and

Yun-Hae Kim

Department of Marine Equipment Engineering, Korea Maritime and Ocean University, Youngdo-gu, Busan 606-791, Republic of Korea

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https://doi.org/10.1142/S0217984915400205Cited by:0 (Source: Crossref)

Abstract

In this paper, we propose a localization simulator based on the random walk/waypoint mobility model and a hybrid-type location–compensation algorithm using the Mean kShift/Kalman filter (MSKF) to enhance the precision of the estimated location value of mobile modules. From an analysis of our experimental results, the proposed algorithm using the MSKF can better compensate for the error rates, the average error rate per estimated distance moved by the mobile node (Err_ Rate_DV) and the error rate per estimated trace value of the mobile node (Err_Rate_TV) than the Mean shift or Kalman filter up to a maximum of 29% in a random mobility environment for the three scenarios.

Keywords:

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