Decomposed state-fusion estimation for multisensor data fusion system

Based on matrix theory, a new decomposed state fusion estimation algorithm is presented. The algorithm is optimal for a special data fusion system, in which the covariance matrix of correlated measurement noise is a Pei-Radman matrix and observation matrices are identical. The steady error of decomposed estimation covariance in other general system is decided by measurement matrix and measurement noise covariance matrix.