|
|
 |
| |
|
|
|
Multichannel ARMA signal covariance intersection fusion Wiener filter for the two-sensor system with time-delayed measurements |
|
|
|
PP: 497-507 |
|
|
|
Author(s) |
|
|
|
Peng Zhang,
Zili Deng,
|
|
|
|
Abstract |
|
|
| For the two-sensor, multi-channel autoregressive moving average (ARMA) signals with measurement delays, the system
with measurement delays is converted into the system without measurement delays by the measurement transformation method. When
the filtering error cross-covariances are known, by the Kalman filtering method, based on the white noise Wiener filters and measurement
Wiener predictors, the optimal fusion Wiener signal filters weighted by matrices, diagonal matrices and scalars are presented.
When the filtering error cross-covariances are unknown, by the covariance intersection (CI) fusion method, the CI fusionWiener signal
filter is presented. It is rigorously proven that the actual accuracy of the CI Wiener signal fuser is higher than that of each local Wiener
signal filter, and is lower than that of the optimalWiener signal fuser with the matrix weights. The geometric interpretation of the above
accuracy relations are presented based on the covariance ellipses. A Monte-Carlo simulation example shows that the actual accuracy of
the CI fuser is close to that of the fuser with the matrix weights, so that it has higher accuracy and good performance. |
|
|
|
|
|
|
|
