Distributed fusion estimation for multi sensor non uniform sampling systems with correlated noises and packet dropouts
In this paper, an optimal distributed fusion estimation algorithm is presented for multi sensor non uniform sampling systems with the correlated process noise and measurement noises at the same time and network induced packet dropouts. First, the non uniform sampling problem is first transformed to a single rate synchronous sampling problem. Then, local optimal filters and the filtering error cross covariance matrices between any two local filters are derived. Finally, the optimal distributed fusion filter is presented by using the matrix weighted fusion algorithm in the linear minimum variance sense. Simulation results show the effectiveness of the proposed fusion approach.
2017 36th Chinese Control Conference (CCC)