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Description
  • The paper presents MATLAB based software framework designed for nonlinear state estimation of discrete-time dynamic systems. The framework is designed to facilitate implementation, testing and use of various nonlinear state estimation methods. It allows simple description of the problem, specification of estimation experiment and processing the resulting data in order to simply compare various estimators. The aim of the paper is to get acquainted with the possibilities of the toolbox. It will demonstrate the easy and natural way in which the estimation problem can be described within the means provided by the framework. Two examples of target tracking will be demonstrated with the estimation experiment setup using the presented framework.
  • The paper presents MATLAB based software framework designed for nonlinear state estimation of discrete-time dynamic systems. The framework is designed to facilitate implementation, testing and use of various nonlinear state estimation methods. It allows simple description of the problem, specification of estimation experiment and processing the resulting data in order to simply compare various estimators. The aim of the paper is to get acquainted with the possibilities of the toolbox. It will demonstrate the easy and natural way in which the estimation problem can be described within the means provided by the framework. Two examples of target tracking will be demonstrated with the estimation experiment setup using the presented framework. (en)
Title
  • Nonlinear Estimation Framework: a Versatile Tool for State Estimation
  • Nonlinear Estimation Framework: a Versatile Tool for State Estimation (en)
skos:prefLabel
  • Nonlinear Estimation Framework: a Versatile Tool for State Estimation
  • Nonlinear Estimation Framework: a Versatile Tool for State Estimation (en)
skos:notation
  • RIV/49777513:23520/13:43919237!RIV14-MSM-23520___
http://linked.open...avai/predkladatel
http://linked.open...avai/riv/aktivita
http://linked.open...avai/riv/aktivity
  • P(GAP103/11/1353), S
http://linked.open...vai/riv/dodaniDat
http://linked.open...aciTvurceVysledku
http://linked.open.../riv/druhVysledku
http://linked.open...iv/duvernostUdaju
http://linked.open...titaPredkladatele
http://linked.open...dnocenehoVysledku
  • 91962
http://linked.open...ai/riv/idVysledku
  • RIV/49777513:23520/13:43919237
http://linked.open...riv/jazykVysledku
http://linked.open.../riv/klicovaSlova
  • Particle filter; UKF; EKF; Tracking; Bayesian approach; Nonlinear state and parameter estimation (en)
http://linked.open.../riv/klicoveSlovo
http://linked.open...ontrolniKodProRIV
  • [5CF4E00D94BE]
http://linked.open...v/mistoKonaniAkce
  • Międzyzdroje, Poland
http://linked.open...i/riv/mistoVydani
  • Piscataway
http://linked.open...i/riv/nazevZdroje
  • 201318th International Conference on Methods and Models in Automation and Robotics
http://linked.open...in/vavai/riv/obor
http://linked.open...ichTvurcuVysledku
http://linked.open...cetTvurcuVysledku
http://linked.open...vavai/riv/projekt
http://linked.open...UplatneniVysledku
http://linked.open...iv/tvurceVysledku
  • Straka, Ondřej
  • Šimandl, Miroslav
  • Flídr, Miroslav
  • Havlík, Jindřich
http://linked.open...vavai/riv/typAkce
http://linked.open.../riv/zahajeniAkce
number of pages
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  • IEEE
https://schema.org/isbn
  • 978-1-4673-5506-3
http://localhost/t...ganizacniJednotka
  • 23520
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