应用抗差无迹卡尔曼滤波的再入弹道处理技术
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国家863计划资助项目(2014AA7042018)


Robust unscented Kalman filter for calculating reentry vehicle trajectory
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    摘要:

    针对现有无迹卡尔曼滤波在再入弹道处理中可能出现的异常观测、观测随机误差模型不准确以及动力学模型不合理等问题,在无迹卡尔曼滤波中引入自适应与抗差估计理论,研究适用于再入弹道处理的自适应抗差滤波方法。该方法可以自适应地估计测量噪声等价协方差阵和状态噪声等价协方差阵,并可实现异常值的分离和维纳模型方差的自适应调整。数值仿真结果表明:该方法计算简单,并能有效减弱测量误差和动力学模型误差对弹道处理精度的影响。

    Abstract:

    The difficulties that unscented Kalman filter encounters when it is introduced in reentry vehicle trajectory were investigated. These difficulties include abnormal measurement, the inaccuracy of measurement random error model and dynamic model. The current study uses an adaptive robust filter that can produce the estimation of equivalent weight flexibly according to measurement noise and state noise, can distinguish abnormal measurement from normal measurement, and can estimate the variance of Wiener model self-adaptively. The simulated results testified that the filter is easy to implement and can reduce the bad influences derived from inaccuracy of measurement random error model and dynamic model.

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李蝉,张士峰,张力军.应用抗差无迹卡尔曼滤波的再入弹道处理技术[J].国防科技大学学报,2017,39(1):1-5.
LI Chan, ZHANG Shifeng, ZHANG Lijun. Robust unscented Kalman filter for calculating reentry vehicle trajectory[J]. Journal of National University of Defense Technology,2017,39(1):1-5.

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  • 收稿日期:2015-09-21
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  • 在线发布日期: 2017-03-07
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