H.R. Song,∗ M. Jeon,∗ Y.S. Lee,∗ T.-S. Choi,∗ and V. Shin∗
Discrete-time linear system, Kalman predictor, fusion formula, multisensor
New multi-step fusion predictors for discrete-time linear dynamic systems with different types of observations are proposed. The multi-step fusion predictors are formed by a summation of the local Kalman filters/predictors with matrix weights depending only on time instants. According to fusion sequence, there could be two kinds of multi-step fusion predictors; the relationship between these fusion predictors is established. Then, the accuracy and computational efficiency of the fusion predictors are demonstrated on a first-order Markov process and a ground moving target indicator model with multisensor environment.
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