Encyclopedia of Systems and Control

2015 Edition
| Editors: John Baillieul, Tariq Samad

Nonlinear Filters

  • Frederick E. Daum
Reference work entry
DOI: https://doi.org/10.1007/978-1-4471-5058-9_63

Abstract

Nonlinear filters estimate the state of dynamical systems given noisy measurements related to the state vector. In theory, such filters can provide optimal estimation accuracy for nonlinear measurements with nonlinear dynamics and non-Gaussian noise. However, in practice, the actual performance of nonlinear filters is limited by the curse of dimensionality. There are many different types of nonlinear filters, including the extended Kalman filter, the unscented Kalman filter, and particle filters.

Keywords

Bayesian Computational complexity Curse of dimensionality Estimation Extended Kalman filter Non-Gaussian Particle filter Prediction Smoothing Stability Unscented Kalman filter 
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Copyright information

© Springer-Verlag London 2015

Authors and Affiliations

  • Frederick E. Daum
    • 1
  1. 1.Raytheon CompanyWoburnUSA