About: Truncated Randomized Unscented Kalman Filter for Interval Constrained State Estimation     Goto   Sponge   NotDistinct   Permalink

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Description
  • The paper deals with state estimation of nonlinear stochastic dynamic systems with constraints imposed on the state. The constraints are considered in the form of a generally nonlinear inequality. Such constrained state estimation problems frequently appear in tracking application where kinematic or geometry constraints often arise. In the paper a truncated randomized unscented Kalman filter is developed that is built on the algorithm of the randomized unscented Kalman filter and a probability density function truncation technique. The proposed filter achieves quality estimates with low computational costs. The proposed filter is illustrated in two numerical tracking examples.
  • The paper deals with state estimation of nonlinear stochastic dynamic systems with constraints imposed on the state. The constraints are considered in the form of a generally nonlinear inequality. Such constrained state estimation problems frequently appear in tracking application where kinematic or geometry constraints often arise. In the paper a truncated randomized unscented Kalman filter is developed that is built on the algorithm of the randomized unscented Kalman filter and a probability density function truncation technique. The proposed filter achieves quality estimates with low computational costs. The proposed filter is illustrated in two numerical tracking examples. (en)
Title
  • Truncated Randomized Unscented Kalman Filter for Interval Constrained State Estimation
  • Truncated Randomized Unscented Kalman Filter for Interval Constrained State Estimation (en)
skos:prefLabel
  • Truncated Randomized Unscented Kalman Filter for Interval Constrained State Estimation
  • Truncated Randomized Unscented Kalman Filter for Interval Constrained State Estimation (en)
skos:notation
  • RIV/49777513:23520/13:43919523!RIV14-TA0-23520___
http://linked.open...avai/riv/aktivita
http://linked.open...avai/riv/aktivity
  • P(TA03030674), 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
  • 111952
http://linked.open...ai/riv/idVysledku
  • RIV/49777513:23520/13:43919523
http://linked.open...riv/jazykVysledku
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  • state estimation, nonlinear filtering, constraints, nonlinear discrete-time stochastic systems. (en)
http://linked.open.../riv/klicoveSlovo
http://linked.open...ontrolniKodProRIV
  • [0AABDC5091BB]
http://linked.open...v/mistoKonaniAkce
  • Istanbul, Turkey
http://linked.open...i/riv/mistoVydani
  • Piscataway
http://linked.open...i/riv/nazevZdroje
  • Proceedings of the 16th International Conference on Information Fusion (FUSION 2013)
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
  • Duník, Jindřich
  • 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
  • 978-605-86311-1-3
http://localhost/t...ganizacniJednotka
  • 23520
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