The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
For the multisensor autoregressive moving average (ARMA) signals with unknown model parameters and noise variances, using recursive instrumental variable (RIV) algorithm, the correlation method and the Gevers-Wouters algorithm with dead band, the information fusion estimators of model parameters and noise variances are presented. They have strong consistence. Then substituting them into the optimal...
For the multisensor systems with correlated measurement noises, different measurement matrices and unknown noise variances, based on the autoregressive moving average (ARMA) model and the reduced dimension measurement fusion algorithm, using the correlated method, a self-tuning reduced dimension measurement fusion Kalman filter is obtained, and its convergence in a realization is proved by the dynamic...
For the multisensor system with different measurement matrices, correlated measurement noises and unknown noise variances, by correlated method, the online identifiers of the noise variances are obtained. Based on ARMA innovation model, a self-tuning weighted measurement fusion Kalman filter is presented, which avoids Lyapunov and Riccati equations, reduces the computational burden and is suitable...
For the multisensor systems with unknown noise variances, using correlation method and least squares fusion criterion, information fusion noise variance estimators are presented by the average of local noise variance estimators, which have the consistence. Substituting the fused noise variance online estimators into the optimal Riccati equation and the optimal weighted measurement fusion Kalman filter,...
For the multisensor system with identical measurement matrix and correlated measurement noise, by the correlation method, the online estimators of the noise statistics are obtained. Based on modern time series analysis method, a self-tuning weighted measurement fusion Kalman filter is presented, which avoids Lyapunov and Riccati equations, reduces the computational burden and is suitable for real...
For the multisensor linear discrete time-invariant systems with correlated measurement noises and with different measurement matrices, based on the weighted least squares (WLS) method, applying the orthogonal transformation, two weighted measurement fusion Kalman filters are presented. Using the information filter, it is proved that they are functionally equivalent to the centralized fusion Kalman...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.