Dynamic target navigation based on multisensor Kalman filtering and neighbor discovery algorithm

Kazuya Kosugi, Toru Namerikawa

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

2 Citations (Scopus)

Abstract

This paper deals with an estimate algorithm which considers optimal control input for dynamic target navigation by using wireless sensor networks and distributed Kalman filter. We propose a novel sensor scheduling algorithm based on a neighbor discovery algorithm for discrete-time linear time-invariant systems. Then we propose an estimate algorithm by sharing predicted estimate values and analyze characteristic of this algorithm. Finally, experimental results show effectiveness of the proposed method in sensor networked feedback systems.

Original languageEnglish
Title of host publicationSICE 2011 - SICE Annual Conference 2011, Final Program and Abstracts
PublisherSociety of Instrument and Control Engineers (SICE)
Pages1392-1397
Number of pages6
ISBN (Print)9784907764395
Publication statusPublished - 2011 Jan 1
Event50th Annual Conference on Society of Instrument and Control Engineers, SICE 2011 - Tokyo, Japan
Duration: 2011 Sep 132011 Sep 18

Publication series

NameProceedings of the SICE Annual Conference

Other

Other50th Annual Conference on Society of Instrument and Control Engineers, SICE 2011
CountryJapan
CityTokyo
Period11/9/1311/9/18

Keywords

  • Distributed control
  • Guidance control
  • Multisensor Kalman Filtering
  • Sensor Networks
  • Sensor scheduling

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Computer Science Applications
  • Electrical and Electronic Engineering

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  • Cite this

    Kosugi, K., & Namerikawa, T. (2011). Dynamic target navigation based on multisensor Kalman filtering and neighbor discovery algorithm. In SICE 2011 - SICE Annual Conference 2011, Final Program and Abstracts (pp. 1392-1397). [6060552] (Proceedings of the SICE Annual Conference). Society of Instrument and Control Engineers (SICE).