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

作　　者：吴汉洲[1] 宋卫东[1] 徐敬青[2] 

机构地区：[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

出　　处：《计算机应用》2016年第5期1455-1457,1463,共4页journal of Computer Applications

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。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.

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 

分 类 号：TP301[自动化与计算机技术—计算机系统结构]