基于多模型的再入弹道目标跟踪算法

发布时间：2018-01-13 04:31

本文关键词：基于多模型的再入弹道目标跟踪算法　出处：《空军预警学院学报》2015年06期 　论文类型：期刊论文

【摘要】：再入弹道导弹目标的跟踪和识别是反导防御体系中最关键的问题.针对传统的跟踪方法不能适用于不同类型的再入弹道目标的跟踪和真假弹头的识别问题,提出一种基于多模型的再入段弹道目标跟踪算法.该算法采用多模型的结构,适用于跟踪不同类型的再入弹道目标,可有效地提高跟踪精度;同时对于弹道系数的估计具有很快的收敛速度和较好的估计精度.仿真结果表明,与传统的EKF算法相比较,本文算法大幅提高了目标跟踪的精度,特别在弹道系数估计上精度较高,具有一定的识别真假弹头的能力和鲁棒的跟踪性能.
[Abstract]:The tracking and recognition of reentry ballistic missile targets is the most important problem in the anti-missile defense system. The traditional tracking methods can not be applied to the different types of reentry ballistic targets tracking and the identification of real and false warheads. A multi-model based reentry trajectory target tracking algorithm is proposed. The algorithm adopts multi-model structure and is suitable for tracking different types of reentry ballistic targets, which can effectively improve the tracking accuracy. At the same time, the estimation of trajectory coefficient has a fast convergence rate and better estimation accuracy. The simulation results show that compared with the traditional EKF algorithm, the algorithm greatly improves the accuracy of target tracking. Especially in the estimation of trajectory coefficient, it has a high accuracy and has a certain ability to identify true and false warheads and robust tracking performance.
【作者单位】：中国电子科技集团公司第38研究所;数字阵列技术重点实验室;智能情报处理重点实验室;
【分类号】：TN953
【正文快照】： 3.智能情报处理重点实验室,合肥230088)再入弹道目标的跟踪是一个典型的非线性滤波问题.传统的非线性滤波方法有:1一阶、二阶扩展卡尔曼滤波算法(EKF)[1];2采用确定采样的非线性滤波方法,不敏滤波算法[2-4];3针对非线性非高斯环境的序贯蒙特卡罗方法(粒子滤波)[5].综合考虑滤

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