捷联导引头视线转率估计的交互式多模型样条滤波算法

针对捷联导引头测量信息的弹目惯性视线转率估计,提出了一种基于交互式多模型算法的样条滤波方法(IMM-SF)。基于体视线和惯性视线的映射关系解算惯性视线角,将其作为虚拟观测量进行滤波,设置多个过程噪声模型,每个模型分别采用样条滤波器进行滤波,IMM-SF滤波器的估值结果为各滤波器估值的加权综合。该方法不必对目标的未知机动建模,应用更加方便,并且可在交互式多模型算法的框架下自适应地调整滤波器的噪声。Monte-Carlo仿真结果表明该方法可有效估计视线转率,并可提高估值精度。

Spline filtering approach based on interacting multiple model for line-of-sight rate estimation in strap-down seeker

A spline filtering approach based on interacting multiple model algorithm (IMM-SF) is proposed to estimate Line-of-sight (LOS) rate in strap-down seeker system. Based on the mapping relation from body LOS angles to inertial LOS angles, the inertial LOS angles are obtained and used as virtual observed data of filters. A set of models of process noise are designed, and every model works based on spline filter independently. The output of IMM-SF is the weighted composition of the outputs of all parallel spline filters. By using this method, the unknown maneuver models of the target are no longer indispensable, which makes the method more convenient to use. In addition, process noise can be adaptively adjusted under the configuration of IMM. Monte-Carlo simulation results show that the LOS rate can be estimated effectively based on SF-IMM, which can also improve the accuracy of estimation.