Steady-State Behavior of Kalman Filter with Discrete- and Continuous-Time Observations

Bernard Friedland

Research output: Contribution to journalArticlepeer-review

10 Scopus citations


There is often a need for optimal mixing of continuous-time and Discrete-Time data. This can be readily accomplished by Kalman filtering, the theory of which is briefly reviewed. In the steady state, the filter gains for processing the continuous-time data are generally periodically varying functions of time and cannot be determined by simply solving either the Discrete-Time or the continuous-time filtering problem, but they can be determined with the aid of the solution of an equivalent Discrete-Time problem. An illustrative example is given for the system: x = white noise, with Discrete-Time observations of x and continuous-time observations of x.

Original languageEnglish (US)
Pages (from-to)988-992
Number of pages5
JournalIEEE Transactions on Automatic Control
Issue number5
StatePublished - Oct 1980
Externally publishedYes

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Computer Science Applications
  • Electrical and Electronic Engineering


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