The existing algorithms for the design of digital filters with colored measurement noise involve a restriction on the dimension of the measurement error model. In this paper we use Kalman filter theory and state space partition to formulate an optimal tracking filter without such restrictions. The input to the new filter are two consecutive measurements, and it is initialized by using the first available measurements and the error model correlation matrix.
Several examples demonstrate the filter formulation and initialization.
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