Hierarchical adaptive gate array-based Kalman filter for multisensor integrated navigation system

Kalman filter based algorithm is generally used in integrated navigation to provide estimation of the state parameters. But the estimation accuracy is affected by the measurement noise parameters. In multisensor navigation system, a single method based adaptive Kalman filter shows limited improvidence in reducing on dependency on initial noise parameters of different types of sensors. In this paper, a hierarchical adaptive gate array-based Kalman filer is proposed to improve sate estimation. The filter bank is designed by different integrated couples of sensors with a set of adaptive filters. The filter array is generated and updated hierarchically with weights in gating networks. Simulation results prove the feasibility and performance improvement of the proposed approach.