Guidance Systematic Error Separation Method Based on Nonlinear Combinatorial Model

Abstract

In order to improve the attack accuracy about sea-based missiles, an accurate separation of the guidance systematic errors including the instrumentation errors and the initial errors, is the key problem. However, the environmental matrix in traditional linear model is ill-conditioning as some systematic errors are coupling. Here we provide a nonlinear combinatorial model by making use of trajectory tracking data, and give a parameter estimation method to separate the guidance systematic errors under launch coordinate. In this study, we give the Bayesian Maximum a posterior (MAP) estimation, and apply this method to separate the guidance instrumentation errors and the initial errors simultaneously combining with trajectory tracking data fusion model. The simulation result shows that the precision of nonlinear combinatorial guidance systematic errors separation is higher than that of the traditional linear model.