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The paper presents the problem of state estimation of linear stochastic time-varying system with generalized unknown disturbance (GUD) existing in the measurements. Such GUD can reflect the effects of sensor bias, deception jamming, navigation bias and so on. An upper-bound filter (UBF) is designed for such systems, and its optimal parameters are derived so that the minimum upper-bounds filter (MUBF)...
This letter presents a new class of discrete-time linear stochastic systems with the statistically-constrained disturbance input, which can represent an arbitrary linear combination of dynamic, random, and deterministic disturbance inputs to generalize the complicated modeling error encountered in actual applications. An adaptive filtering scheme is proposed for such systems by recursively constructing...
In this paper, a class of linear systems subject to process disturbances and structured measurement disturbances with unknown time-varying covariances is considered. First, we construct a finite-horizon filter structure to recursively obtain a suit of positive definite matrices and propose the sufficient conditions to ensure the above positive definite matrices to be upper bounds of the unknown covariances...
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