Application of fuzzy adaptive unscented Kalman filter in spacecraft celestial navigation

To solve the problem of unscented Kalman filter(UKF) filtering under uncertain measurement noises during spacecraft autonomous celestial navigation, an adaptive UKF algorithm based on fuzzy logic is presented. According to the ratio between the actual residual and filter residual, the filter process is divided into two modes: normal mode and adaptive mode. The fuzzy membership functions are established separately to the two modes. Through fuzzy inference rule, the adaptive revise factor is obtained to real-time revise the measurement noise covariance so that the actual noise covariance is tracked. Accordingly, the filter could converge effectively even the measurements are suffered from uncertain noises. The fuzzy adaptive UKF algorithm is applied in directly sensing horizon celestial navigation system, and simulation results under different noise levels show that the algorithm is adaptive to uncertain measurement noises.