Optimal-Switched H_∞ Robust Tracking for Maneuvering Space Target

For maneuvering target tracking problem, robust filtering is an effective way to gain fast and accurate target trajectory in real time. The H_∞ filter (H_∞F) is a conservative solution with infinite-horizon robustness, leading to excessive cost of filtering optimality and reduction of estimation precision. In order to retrieve the filtering optimality sacrificed by conservativeness of the H_∞F design, in this paper, an optimal-switched filtering mechanism is developed and established on the standard H_∞F to propose an optimal-switched H_∞ filter (OSH_∞F). The optimal-switched mechanism adopts a switched structure that switches filtering mode between optimal and H_∞ robust by setting a switching threshold, and introduces an optimality-robustness cost function (ORCF) to on-line optimize the threshold such that the switching structure can be optimized. In the ORCF, a non-dimensional weight factor (WF) is used to quantify the ratio of the filtering robustness and optimality. As the only tunable parameter in the filter, when the WF is given, the proposed OSH_∞F can obtain the optimal state estimates with filtering optimality and robustness kept at the WF-determined ratio. With the conservativeness of the H_∞F optimized, the developed OSH_∞F can be used as a generalized H_∞F form. A simulation example of space target tracking has demonstrated the superior estimation performance of the OSH_∞F compared with that of Kalman filter and other typical H_∞ filters.