Multi-channel ARMA Signal Covariance Intersection Fusion Kalman Predictor
Peng Zhang, Wenjuan Qi, Zili Deng · Procedia Engineering · 2012
For multi-channel ARMA signal with two sensors and unknown cross-covariances between the local Kalman predicting errors, based on the transformation of ARMA signal model to the state space model, a covariance intersection (CI) fusion steady-state Kalman signal predictor is presented. The accuracy comparison of CI Kalman signal fuser with the Kalman fuser weighted by matrices, diagonal matrices, and scalars is given. The geometric interpretation of accuracy relations is given by the covariance ellipses. Its accuracy is higher than that of each local Kalman predictor, and lower than that of optimal Kalman predictor weighted by matrices. A Monte-Carlo simulation results show its effectiveness and its actual accuracy is close to that of the optimal fuser weighted by matrices.