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Preprint Sep 2026

Probe Sets for Nonlinear Kalman Filtering: Multi-Center Gains and Covariance Recalibration

Kalman filters (KFs) choose the gain as the product of the state--measurement cross-covariance and the inverse of the innovation covariance. In nonlinear systems, the predictive distribution generally changes shape, and these covariances require approximation. Conventional nonlinear KFs approximate them around a single...

Shi-Da Jiang, Shen Tao, Scott Moura · 0 citations

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