Abstract
Estimation of noise covariance matrices for linear or nonlinear stochastic dynamic systems is treated. The novel off-line technique for estimation of the covariance matrices of the state and measurement noises is designed. The technique is based on the multi-step prediction error and on knowledge of the system initial condition and it takes an advantage of the well-known standard relations from the area of state estimation techniques and least square method. The theoretical results are illustrated in numerical examples.
Published Version
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