Multisensor state fusion estimation with correlated measurement noise

Based on matrix theory, a new decomposed state fusion estimation algorithm is presented, and the covariance matrix of correlated measurement noise is successfully parallel decomposed. 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.