一种改进的弹道导弹状态和参数联合估计方法  

Improved method for joint estimation of state and parameters of ballistic missile

作　　者：武慧勇 任清安[1,2] 邵俊伟[1,2] 钮俊清[1,2] WU Huiyong;REN Qingan;SHAO Junwei;NIU Junqing(No. 38 Research Institute, China Electronic Technology Group Corporation, Hefei 230088, China;Key Lab of Aperture Array and Space Application, Hefei 230088, China)

机构地区：[1]中国电子科技集团公司第38研究所,合肥230088 [2]孔径阵列与空间探测安徽省重点实验室,合肥230088

出　　处：《空军预警学院学报》2016年第6期414-417,共4页Journal of Air Force Early Warning Academy

摘　　要：针对常用的目标运动模型无法很好地描述弹道导弹再入段发生机动情况的问题,提出一种改进的状态和参数联合估计方法.通过在运动模型中引入Singer模型,充分考虑了目标再入段的机动性,并兼顾了自由段建模的精确性;考虑质阻比慢变的性质,引入一阶Markov模型对质阻比建模,改善了质阻比的估计效果;同时,采用自适应强的强跟踪无迹卡尔曼滤波器进行状态和参数的联合估计.仿真结果表明,所提方法收敛速度快,估计精度高,具有良好的工程意义.In view of the problem that the common target motion model is not appropriate to describe themaneuvering condition of the reentry segment of the ballistic missile, an improved method for joint estimation ofstate and parameters of the missile is proposed in this paper. By introducing the Singer model into the motionmodel, the maneuverability of the target reentry segment is fully considered, and the accuracy of the free segment’s modeling is also taken into account. By considering the properties of the slow variation of mass-to-drag ratio, thefirst-order Markov model can be introduced to the modeling of the mass-to-drag ratio, thus improving this ratio’sestimation effect. Meanwhile, the joint estimation of state and parameters is done by using the strong trackingKalman filter with the strong adaptivity. Simulation results show that the proposed method is of fast convergenceand high estimation accuracy, having a preferable engineering significance.

关 键 词：弹道导弹 质阻比 Singer模型 MARKOV模型 强跟踪 

分 类 号：TN957[电子电信—信号与信息处理]