A Linear Fusion of the Local Kalman Estimates

We extend our obtained fusion formula yielding an optimal mean square combination of unbiased estimates on the case of an arbitrary number of biased estimates and apply it to fusion of multisensor local estimates. The suboptimal two-stage filter for linear dynamic systems is designed: the local optimal Kalman estimates computed at the first stage are linearly fused at the second stage. Its realization needs a lower memory demand than the optimal Kalman filter. The example exhibits the effect of noise on the performance of fusion of the state estimates based on measurements from different sensors.