The reduction methodology of external noise with segmentalized PSO-FCM: Its application to phased conversion of the radar system on board

Hyun Seung Son, Jin Bae Park, Young Hoon Joo

Research output: Contribution to journalArticle

1 Citation (Scopus)

Abstract

This paper presents an intelligent reduction method for external noise. The main idea comes from PSO-FCM (Particle Swam Optimization Fused fuzzy C-Means) clustering. The data of the target is transformed from the antenna coordinates to the vessel one and to the system coordinates. In the conversion, the overall noises hinder observer to get the exact position and velocity of the maneuvering target. While the filter is used for tracking system, unexpected acceleration becomes the main factor which makes the uncertainty. In this paper, the tracking efficiency is improved with the PSO-FCM and the compensation methodology. The acceleration is approximated from the external noise splitted by the proposed clustering method. After extracting the approximated acceleration, the rest in the noise is filtered by the filter and the compensation is added to after that. Proposed tracking method is applicable to the linear model and nonlinear one together. Also, it can do to the on-line system. Finally, some examples are provided to examine the reliability of the proposed method.

Original languageEnglish
Pages (from-to)638-643
Number of pages6
JournalJournal of Institute of Control, Robotics and Systems
Volume18
Issue number7
DOIs
Publication statusPublished - 2012 Oct 31

All Science Journal Classification (ASJC) codes

  • Software
  • Control and Systems Engineering
  • Applied Mathematics

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