Filtering Of Nonlinear System And Research On Application In Guidance

Currently, Extented Kalman Filtering(EKF) is a important method for estimate the system states in the problem of target tracking or target intercept .But the essence of reseach on such problems is reseach on nonlinear problem. Because EKF necessitate the linearization of the original nonlinear models, the accuracy achieved through using EKF are limited to some extent. In recent years,there have appeared some improved filtering methords for nonlinear system. The Unscented Kalman Filtering(UKF) that directly use the nonlinear model is the optimum filtering method thereof, and it will become a widely and effective filtering method in research on estimation problem of nonlinear system. In target state estimation, since the process noise and/or system noise is unknown, therefore, we need a effective self-adapting filtering method to elimate the effect on estimate of system brought by the uncertainty of noise. Sub-optimun sage-husa self-adapting filtering and Strong track filtering are widely used self adapting filtering methods, but they have drawback of large amount of calculation or low filtering precision.The main purpose of this article is research on UKF and an improved method thereof(SUKF) and their application in space interception, performance of them is then compared with EKF. Another purpose of this article is research on Sub-optimun sage-husa self-adapting filtering and Strong track filtering, a parallel self-adapting filtering method is then designed according to their advantages and drawbacks.On the theroy of nonlinear filtering, the following work had been done:1) Research on EKF and UKF, theoretical analyse is then done on the performance of them. Further more, an improved method is put forward.2) Research on Sub-optimun sage-husa self-adapting filtering and Strong track filtering, an parallel self-adapting filtering method is then put forward according to their advantages and drawbacks.On space interception and maneuver acceleration of target, the following work had been done:1) Flat portion of space interception model is built, observability of it is then analysed. Further more, a newly guidance law that can enhance observability is put forward.2) Filtering estimation is done on the model using EKF and UKF method ,the performance of them is then compared.3) Filtering estimation is done on high-order differetial estimation model of line-of-sight using parallel self-adapting filtering method based on the estimated line-of-sight.4) maneuver acceleration of target is estimated using acceleration model of maneuver target based on pre-estimated high-order differetial of line-of-sight and coherent states.