In order to obtain more accurate state estimation from multisensor system, the state estimation with two-level fusion structure is presented. By means of measurement fusion algorithm, the local first-level fusion centers can obtain the globally optimal fused measurement information, and then the local state estimation can be got by classical Kalman filtering. At the second-level fusion center, the fused estimation can be received by applying the covariance intersection fusion algorithm, which avoids the calculation of the correlation among local first-level fusion centers. The simulation example shows the effectiveness and higher accuracy of the presented fusion structure.