Abstract
In this paper, the state-space representation of generalized complimentary filter is proposed. Complementary filter has the suitable structure to merge information from sensors whose frequency regions are complementary. First, the basic concept and structure of complementary filter is introduced. And then the structure of the generalized filter and its state-space representation are proposed. The state-space representation of complementary filter is able to design the complementary filter by applying modern filtering techniques like Kalman filter and $H_{\infty}$ filter. To show the usability of the proposed state-space representation, the design of Inertial Navigation System(INS) vertical channel damping loop using Global Positioning System(GPS) is described. The proposed GPS/INS damping loop lends the structure of Baro/INS(Barometer/INS) vertical channel damping loop that is an application of complementary filter. GPS altitude error has the non-stationary statistics although GPS offers navigation information which is insensitive to time and place. Therefore, $H_{\infty}$ filtering technique is selected for adding robustness to the loop. First, the state-space representation of GPS/INS damping loop is acquired. And next the weighted $H_{\infty}$ norm proposed in order to suitably consider characteristics of sensor errors is used for getting filter gains. Simulation results show that the proposed filter provides better performance than the conventional vertical channel loop design schemes even when error statistics are unknown.