弹丸卫星接收机误差建模与弹道参数估计方法  

Error Modeling and Trajectory Parameter Estimation Method for Satellite Receiver of Projectile

作　　者：杨瑞伟[1] 林子杨 申强[1] 吴永辉 李红云 YANG Ruiwei;LIN Ziyang;SHEN Qiang;WU Yonghui;LI Hongyun(School of Mechatronical Engineering,Beijing Institute of Technology,Beijing 100081,China;School of Aerospace Engineering,Beijing Institute of Technology,Beijing 100081,China)

机构地区：[1]北京理工大学机电学院,北京100081 [2]北京理工大学宇航学院,北京100081

出　　处：《北京理工大学学报》2025年第4期334-343,共10页Transactions of Beijing Institute of Technology

基　　金：装备预研项目(9090102010305);国家自然科学基金资助项目(61973033)。

摘　　要：针对弹道修正弹在弹道环境下状态估计精度差的问题,利用试验过程中的数据,从弹丸记录仪卫星定位和测速数据与雷达数据中分离出弹丸飞行过程中弹道测量误差序列,使用高斯混合模型(GMM)对误差概率分布进行近似拟合,并对其表述形式进行统一.对传统的高斯混合扩展卡尔曼滤波(GMEKF)算法进行改进,考虑噪声在相邻多个时刻之间的相关性,使用AR模型将有色观测噪声解耦并使用状态扩增法、差分法对有色噪声进行白化处理.以修正弹弹道仿真为例进行算法验证及对比,实验结果证明了改进GMEKF算法在提升弹道参数估计精度以及落点精度的有效性.To solve the problem of poor state estimation accuracy of ballistic correction projectiles in ballistic environment,the data during the experimentation was utilized to separate the ballistic measurement error sequence during the projectile’s flight from the satellite positioning and velocity measurement data of the projectile and the radar data.The error probability distribution was approximately fitted using the Gaussian mixture model(GMM),the expression form of which is unified.The traditional Gaussian mixture extended Kalman filter(GMEKF)algorithm was improved by considering the correlation of the noise among multiple adjacent moments.The colored observation noise was decoupled using the AR model and whitened using the state augmentation method and the difference method.Taking the trajectory simulation of the correction projectile as an example for algorithm verification and comparison,the experimental results demonstrate the effectiveness of the improved GMEKF algorithm in improving the estimation accuracy of ballistic parameters and the accuracy of the impact point.

关 键 词：非高斯有色噪声 高斯混合模型 高斯混合扩展卡尔曼滤波 状态估计 

分 类 号：TJ410[兵器科学与技术—火炮、自动武器与弹药工程]