火箭飞行测控数据野值处理及其UKF算法

In this paper, a new method of Kalman filter based on unscented transform, which is used in nonlinear system, is proposed on the basis of improving precision of rocket flight data processing. The new method is unscented Kalman filter algorithm with Outlier detection, which will estimate location and track about the aim in rocket flight control system. The algorithm uses a few sampling point to represent distribution of random variable by means of nonlinear system propagation and adjustment to filter gain real-timely, then eliminating outliers in the detection data. The new method is applied into launch vehicle control system. The result of Monte Carlo simulation proves that the effect of detection data processing can be eliminated effectively and improves filtering accuracy.