The Discrete Kalman Filter

  • Donald E. Catlin
Part of the Applied Mathematical Sciences book series (AMS, volume 71)


In Chapter 6, we discussed the problem of making recursive estimates of a random vector X. The problem was static in the sense that every measurement was used to update or improve the estimate of the same random vector X. We now consider the case where the random vector changes in time, between measurements, according to a specified statistical dynamic.


Kalman Filter Random Vector State Transition Matrix Maximum Entropy Principle Kalman Gain 
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.


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Copyright information

© Sringer-Verlag New York Inc. 1989

Authors and Affiliations

  • Donald E. Catlin
    • 1
  1. 1.Department of Mathematics and StatisticsUniversity of MassachusettsAmherstUSA

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