Estimation with Applications to Tracking and Navigation
Estimation with Applications to Tracking and Navigation
Brief paper: Optimal Kalman filtering fusion with cross-correlated sensor noises
Automatica (Journal of IFAC)
Technical Communique: The optimality for the distributed Kalman filtering fusion with feedback
Automatica (Journal of IFAC)
New approach to information fusion steady-state Kalman filtering
Automatica (Journal of IFAC)
Multi-sensor optimal information fusion Kalman filter
Automatica (Journal of IFAC)
Optimal linear estimation fusion .I. Unified fusion rules
IEEE Transactions on Information Theory
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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 filter, i.e. the corresponding two weighted measurement fusion Kalman filters are numerically identical to the centralized fusion Kalman filter, so that they have the global optimality. Compared with the centralized fusion Kalman filter, they can obviously reduce the computational load. Two numerical simulation examples in the tracking systems verify their functional equivalence and compare their computational load.