Abstract
The networked measurements arrive at information processing center with different time delays. As a result, the filter is required for different filtration scenes. The existing filtering algorithms are mostly proposed for specific filtration scenes. This situation motivates our present research. A linear time-varying system with unknown noise statistical properties is considered in this paper, and a unified finite horizon H∞ performance criterion function is built for different filtration scenes, firstly. Secondly, the performance criterion function is expressed as an indefinite quadratic inequality. And, the projection in Krein space corresponding to the indefinite quadratic form is analyzed in different filtration scenes. Thirdly, two unified finite horizon H∞ filtering methods are deduced, according to the idea of re-filtering and updating directly. Finally, a numerical simulation with different measurement arrival scenes, illustrates the effectiveness and otherness of the proposed unified finite horizon H∞ filtering methods.
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