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Windowing-based Gaussian approximation fusion filtering for multi-sensor nonlinear systems with false data injection attacks
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DOI：10.1016/j.amc.2026.130211.png)
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Abstract
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• A new recursive framework of the local filter is given considering the impact of the attacks Bayesian estimation theory. • The moving window approximation and random weighting estimation methods are extended to dynamically estimate and adjust noise statistics. • A new SDCI fusion algorithm is proposed to provide higher estimation accuracy than CI and SCI methods.
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3.4
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2.3W
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