Cholesky-KalmanNet: Model-Based Deep Learning With Positive Definite Error Covariance Structure
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DOI: 10.1109/lsp.2024.3519265
Abstract: State estimation from noisy observations is crucial across various fields. Traditional methods such as Kalman, Extended Kalman, and Unscented Kalman Filter often struggle with nonlinearities, model inaccuracies, and high observation noise. This letter introduces Cholesky-KalmanNet… read more here.
Keywords: error covariance; cholesky kalmannet; model; estimation ... See more keywords