A novel parameterization of state-transition distributions enables maximum-likelihood and score-matching estimators for joint recovery of linear dynamics and noise covariance that outperform ordinary least squares.
Mehra, On the identification of variances and adaptive Kalman filtering, IEEE Transactions on Automatic Control 15 (1970) 175–184
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Joint Identification of Linear Dynamics and Noise Covariance via Distributional Estimation
A novel parameterization of state-transition distributions enables maximum-likelihood and score-matching estimators for joint recovery of linear dynamics and noise covariance that outperform ordinary least squares.