| 基于改进IMM-UKF的弹道导弹再入段跟踪数据滤波 |
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| 引用本文： | 李相民,;颜骥,;刘丙杰,;代进进. 基于改进IMM-UKF的弹道导弹再入段跟踪数据滤波[J]. 情报指挥控制系统与仿真技术, 2014, 0(6): 10-14 |
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| 作者姓名： | 李相民, 颜骥, 刘丙杰, 代进进 |
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| 作者单位： | [1]海军航空工程学院,山东 烟台264001; [2]解放军91352部队,山东 威海264208 |
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| 基金项目： | 国防预研基金（40108040402） |
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| 摘 要： | 针对弹道系数未知的弹道导弹再入段跟踪雷达测量数据滤波这类非线性强的滤波问题，提出可变多模型无迹卡尔曼滤波算法。利用无迹卡尔曼滤波逼近精度高，计算量小，适应于任意非线性模型的特点，将其作为多模型的基本滤波器；滤波算法根据各模型正确描述目标状态的概率，动态地改变多模型数量和模型参数。上述方法的综合运用，提高对目标状态估计精度，降低了计算的复杂度，仿真实验验证了方法的有效性。
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| 关 键 词： | 弹道导弹跟踪 可变多模型 交互多模型 无迹卡尔曼滤波 |
Reentry-P hase Tracking of Unknown Ballistic Missiles Based on Improved IMM-UKF |
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| Affiliation: | LI Xiangmin, YAN Ji, LIU Bingjie, DAI Jinjin (1.Naval Aeronautical and Astronautical University, Yantai 264001; 2. The Unit 91352 of PLA, Weihai 264208, China) |
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| Abstract: | Radar tracking of a ballistic target in reentry phase with unknown ballistic coefficient is a problem of nonlinear estimation, a variablestructure multiple mode based on Unscented Kalman filter has been proposed for it. UKF has been used as the basic filter for its more accurate, easier to implement, and uses the same order of calculations as linearization. The mode coefficients and IMM mode set is adaptively changed and then subsumes the true dynamic model according to the real time estimation of object state. Simulation shows it improves tracking precision effectively and makes computational complexity lower. |
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| Keywords: | ballistic target tracking variable-structure multiple mode interact multiple mode unscented Kalman filtering |
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