Distributed Lattice Smooth Variable Structure Filter for Target Tracking Under Model Uncertainty

The conventional filters algorithm cannot provide a stable and precise state estimation for target tracking in Air Traffic Control (ATC) with motion model uncertainty. In this paper, the new filter and distributed fusion strategies are proposed. First, a Lattice Smooth Variable Structure Filter (LSVSF) is proposed for nonlinear system with model uncertainty, which avoids the calculation of Jacobi matrices. Then, the distributed lattice smooth variable structure filter Distributed Lattice Smooth Variable Structure Filter (MW-LSVSF) is proposed, and the cross-covariance of local estimators is calculated by lattice sampling. Finally, the state estimation accuracy and robustness are verified by ATC scenarios.