基于多项式拟合的扩展卡尔曼滤波算法

doi:10.11772/j.issn.1001-9081.2016.05.1455

计算机应用 ›› 2016, Vol. 36 ›› Issue (5): 1455-1457.DOI: 10.11772/j.issn.1001-9081.2016.05.1455

基于多项式拟合的扩展卡尔曼滤波算法

吴汉洲¹, 宋卫东¹, 徐敬青²

1. 军械工程学院火炮工程系, 石家庄 050003;
2. 军械工程学院弹药工程系, 石家庄 050003

收稿日期:2015-07-16 修回日期:2015-08-20 出版日期:2016-05-10 发布日期:2016-05-09
通讯作者: 吴汉洲
作者简介:吴汉洲(1989-),男,山东日照人,硕士研究生,主要研究方向:弹箭弹道;宋卫东(1964-),男,河北大名人,教授,博士,主要研究方向:弹道学、弹箭飞行力学;徐敬青(1983-),男,山东青岛人,讲师,博士,主要研究方向:制导弹药。

Extended Kalman filtering algorithm based on polynomial fitting

WU Hanzhou¹, SONG Weidong¹, XU Jingqing²

1. Department of Guns Engeering, Ordnance Engineering College, Shijiazhuang Hebei 050003, China;
2. Department of Ammunition Engineering, Ordnance Engineering College, Shijiazhuang Hebei 050003, China

Received:2015-07-16 Revised:2015-08-20 Online:2016-05-10 Published:2016-05-09

摘要/Abstract

摘要： 弹道修正弹内的弹载计算机必须实时对卫星定位接收机获取的弹丸状态数据进行滤波降噪,用于预测弹丸落点,传统滤波方法滤波时间长,滤波实时性差,提出一种基于多项式拟合的方法。通过适当降低卫星定位接收机数据更新频率,并用多项式拟合插值出的数据代替数据更新时间间隔内的弹丸状态数据。仿真实验表明,该算法在不降低滤波效果的前提下,较普通扩展卡尔曼滤波时间降低7/8,提高了滤波实时性,对于弹道修正弹关键技术的研究提供了重要参考。同时该方法可推广应用到其他滤波算法当中,具有很强的可移植性。

关键词: 滤波算法, 多项式拟合, 弹道修正弹, 卫星定位数据, 滤波误差

Abstract: The data acquired by the satellite positioning receiver in the trajectory correction projectile must be filtered in real-time to predict the point. The calculation of traditional filtering method is time-consuming, and is difficult to meet the requirements of real-time filtering. A kind of extended Kalman filtering algorithm based on polynomial fitting was proposed. The data of projectile flight in the time interval was replaced by the fitting interpolation data. In this way the filter frequency could be reduced. Simulation results show that the computation time of the proposed method can be reduced by 7/8 compared to traditional extended Kalman filtering without reducing the filtering precision, and the real-time performance is improved. This method can provide important reference for the research of key technology of trajectory correction projectile. At the same time, the method can be applied to other filtering algorithms, and has a strong portability.

Key words: filtering algorithm, polynomial fitting, trajectory correction projectile, satellite positioning data, filtering error

中图分类号:

TP301

吴汉洲, 宋卫东, 徐敬青. 基于多项式拟合的扩展卡尔曼滤波算法[J]. 计算机应用, 2016, 36(5): 1455-1457.

WU Hanzhou, SONG Weidong, XU Jingqing. Extended Kalman filtering algorithm based on polynomial fitting[J]. Journal of Computer Applications, 2016, 36(5): 1455-1457.

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[12] 申强, 葛腼, 彭博, 等.基于GPS弹道测量的卡尔曼滤波参数估计算法[J].北京理工大学学报, 2009, 29(12):1048-1051. (SHEN Q, GE M, PENG B, et al. Parameters estimation algorithm by Kalman filtering based on GPS measurement for projectile trajectory[J]. Transactions of Beijing Institute of Technology, 2009, 29(12):1048-1051.) BackgroundWU Hanzhou, born in 1989, M. S. candidate. His research interests include projectile trajectory.SONG Weidong, born in 1964, Ph. D., professor. His research interests include ballistics theory, flight mechanics of projectile.XU Jingqing, born in 1983, Ph. D., lecture. His research interests include guided munition.

基于多项式拟合的扩展卡尔曼滤波算法

Extended Kalman filtering algorithm based on polynomial fitting

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