WMF information filter for multisensor descriptor system with same measurement matrix and correlated noises

For the multisensor linear stochastic descriptor system with same measurement matrix and correlated noises, the weighted measurement fusion information filter is presented, based on the weighted measurement fusion algorithm and the Kalman information filtering theory. This information filtering is a new repression of Kalman filtering based on information matrix, which can reduce computational burden and has important application in many theory analysis. And the presented weighted measurement fusion information filter has global optimality, and can avoid computing these cross-variances of the local Kalman filters, compared with the state fusion method. A simulation example about 3-sensors stochastic descriptor system verifies the effectiveness.