关键词:

机动估计；交互式多模型；高阶容积鲁棒滤波；闪烁噪声 ')">">机动估计；交互式多模型；高阶容积鲁棒滤波；闪烁噪声

Abstract:

To cope with the problem of the radar seeker measurement contains glint noise, interacting multiple model and robust filter application in the acceleration estimation of maneuvering target are studied. A novel algorithm named Highdegree Cubature Robust filter is proposed, in which HuberBased filter theory is used to develop Highdegree Cubature Kalman filter. Singer Model, Current Statistical Model, and Constant Acceleration Model are selected as mobile model of target. And the radar seeker measurement model is established. The target acceleration estimation filter is designed, which combines the High degree cubature robust filter with the interactive multiple model algorithm framework. The Monte Carlo simulation results show that the algorithm presented in this paper has a stronger robustness, and better accuracy in comparison with the Gaussian filter for the case of glint noise.

Key words: acceleration estimate')">

acceleration estimate, interacting multiple model, high degree cubature robust filter, glint noise