Suboptimal Linear Filtering and Generalized Millmans Formula

V. Shin, Y. Lee, and T.-S. Choi (Korea)


Estimation, kalman filter, adaptive filter, and multisensor


This paper considers the problem of recursive estimation in linear discrete-time systems. We derive an optimal combination of arbitrary number correlated estimates. In particular, for two estimates this combination represents the well-known Millman and Bar-Shalom-Campo formulae for uncorrelated and correlated estimation errors, respectively. This new result is applied to the various estimation problems as Kalman filtering and adaptive filtering. The new suboptimal filters with parallel structure are herein presented. It is also shown that these filters are very effective for multisensor systems containing different types of sensors. Example demonstrate the accuracy and efficiency of application of the generalized Millman's formula.

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