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.
This paper is concerned with the fusion estimation problem for multi-sensor discrete time-invariant linear systems with multiple time delays and colored measurement noise. In order to transform those systems into systems with correlated white noise, a system transformation method is introduced. A sequential covariance intersection (SCI) fusion Kalman filter is given based on the local optimal recursive...
This paper is concerned with the fusion estimation problem for multi-sensor discrete time-invariant linear systems with multiple time delays and colored measurement noise. A fast sequential covariance intersection (SCI) fusion Kalman filter is given based on the augmented Kalman filter in the linear minimum variance sense, which avoids the calculation of the cross covariance matrices between local...
For the multi-sensor systems with correlated input and measurement noises, under the Linear Unbiased Minimum Variance criterion, the centralized and the weighted measurement fusion structures are derived. Applying the left-coprime factorization algorithm based on modern time series analysis method, the fused ARMA innovation models are obtained, and then by the universal Wiener estimators, the corresponding...
In order to obtain more accurate state estimation from multisensor system, the state estimation with two-level fusion structure is presented. By means of measurement fusion algorithm, the local first-level fusion centers can obtain the globally optimal fused measurement information, and then the local state estimation can be got by classical Kalman filtering. At the second-level fusion center, the...
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.