This paper deals with the estimation of the noise covariance matrices of systems described
by state‐space models. Stress is laid on the systematic survey and classification of both the …

Correct knowledge of noise statistics is essential for an estimator or controller to have
reliable performance. In practice, however, the noise statistics are unknown or not known …

To effectively maintain and analyze a large amount of real-time sensor data, one often uses
a filtering technique that reflects characteristics of original data well. This paper proposes a …

The paper deals with the estimation of the process and measurement noise covariance
matrices of a system described by the linear time-varying state–space model. In particular …

An adaptive unscented Kalman filter (AUKF) and an augmented state method are employed
to estimate the time-varying parameters and states of a kind of nonlinear high-speed objects …

Permanent magnet synchronous motors (PMSM) are widely used in many industry fields.
Maximizing their degree of thermal utilization reduces the motor's weight, volume and cost …

This article deals with noise identification of a system described by the linear time-varying
state-space model using correlation methods. In particular, the stress is laid on the …

This note introduces an extended environment for Kalman filtering that considers also the
presence of additive noise on input observations in order to solve the problem of optimal …

The Kalman filter is the optimal linear assimilation scheme only if the first-and second-order
statistics of the observational and system noise are correctly specified. If not, optimality can …

Modern data acquisition systems record large volumes of data which are often not suitable
for direct computer processing-a first stage of preprocessing (or data" editing") is usually …