系统工程与电子技术 ›› 2018, Vol. 40 ›› Issue (2): 409-416.doi: 10.3969/j.issn.1001-506X.2018.02.24

• 制导、导航与控制 • 上一篇    下一篇

基于理想弹道鲁棒容积卡尔曼滤波视线角估计

刘振亚, 高敏, 程呈   

  1. 陆军工程大学导弹工程系, 河北 石家庄 050003
  • 出版日期:2018-01-25 发布日期:2018-01-23

Line-of-sight angle estimation algorithm based on ideal trajectory robust cubature Kalman filter

LIU Zhenya, GAO Min, CHENG Cheng   

  1. Department of Missile Engineering, Army Engineering University, Shijiazhuang 050003, China
  • Online:2018-01-25 Published:2018-01-23

摘要: 针对惯性元件在低成本全捷联制导弹药中应用难度大的问题,设计了一种利用理想弹道弹体运动参数代替惯性元件测量值的弹目视线角滤波估计方法。根据坐标系转换关系及弹目视线几何关系,将理想弹道参数作为系统不确定性参数,建立非线性滤波系统;针对具有参数不确定性的非线性系统滤波问题,提出了一种基于理想弹道的鲁棒容积卡尔曼滤波(ideal trajectory robust cubature Kalman filter,ITRCKF)算法,将具有不确定性系统的滤波问题转化为带参数κ的误差协方差上界最小化问题;最终利用导引头探测器测量得到弹体视线角,结合ITRCKF对非线性系统状态进行估计。实验结果表明:在小扰动条件下,ITRCKF偏角估计最大误差值较容积卡尔曼滤波(cubature Kalman filter,CKF)下降了85.57%,误差均方根(root mean square error, RMSE)下降了81.93%;在大扰动条件下,ITRCKF倾角估计值最大误差较CKF下降了31.64%,误差均方根下降了46.39%。所提方法对弹目视线角的估计值满足精度要求,并且相对于CKF估计值具有较好的鲁棒性能。

Abstract: Considering that applying the inertial measurement unit (IMU) to low-cost strapdown guided munitions is quite difficult, a line-of-sight (LOS) angle estimation algorithm with ideal trajectory parameters replacing values measured by IMU is designed. According to coordinate transformation and LOS geometrical relationship, ideal trajectory parameters are regarded as uncertain parameters to build the nonlinear filter system. An ideal trajectory robust cubature Kalman filter (ITRCKF) algorithm is proposed to the solve nonlinear system filter problem with uncertain parameters. The filter problem with uncertain system is converted into minimizing the upper bound of covariance error with parameter κ, utilizing the angle of sight with body from the seeker detector and the ITRCKF to estimate states of nonlinear systems. The experimental results show that under the condition of small disturbance, the max error of declination and the root mean square of error (RMSE) by ITRCKF are reduced by 85.57% and 81.93% respectively, compared with the cubature Kalman filter (CKF). And under the condition of large disturbance, the max error of declination and the RMSE by ITRCKF are reduced by 31.64% and 46.39% respectively. The estimated angles of LOS by the proposed algorithm meet requirements for acceptable accuracy, and have a better robust performance than CKF.

中图分类号: