Advertisement

Particular Filtering Techniques

  • Thierry Chonavel
Part of the Advanced Textbooks in Control and Signal Processing book series (C&SP)

Abstract

Purpose In many problems, we want to evaluate a process X from partial knowledge of a process Y. According to whether knowledge about Y at instant n is limited to that of H Y,n , or to that of H Y,o:n = span {Y o,...,Y n }, we may opt to evaluate X n by X n /H Y,n , or X n /H Y,o:n The resolution of these problems is known as Wiener filtering and Kaiman filtering respectively. We next indicate how Kaiman’s recursive filtering can be generalised to computing recursively the distribution of X n conditional to {Y0,... , Y n } for systems that may not be linear. We finish this part with the presentation of the matched filter that enables detection of a known deterministic signal in the presence of noise.

Keywords

Kalman Filter Recurrence Equation State Space Model Matched Filter Wiener Filter 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Copyright information

© Springer-Verlag London 2002

Authors and Affiliations

  • Thierry Chonavel
    • 1
  1. 1.ENST de BretagneTechnopôle de Brest IroiseBrest CedexFrance

Personalised recommendations