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Steady-state behavior of Kalman filter with discrete- and continuous-time observations

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1 Author(s)
B. Friedland ; Singer Company, Little Falls, NJ, USA

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: \ddot{x} = white noise, with discrete-time observations of x and continuous-time observations of \dot{x} .

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IEEE Transactions on Automatic Control  (Volume:25 ,  Issue: 5 )