航空学报 > 2023, Vol. 44 Issue (6): 326817-326817   doi: 10.7527/S1000-6893.2022.26817

预测-五阶容积卡尔曼滤波方法

赵祥丹, 王彪, 王志胜(), 杨忠   

  1. 南京航空航天大学 自动化学院,南京 210016
  • 收稿日期:2021-12-14 修回日期:2021-12-31 接受日期:2022-03-21 出版日期:2023-03-25 发布日期:2022-04-12
  • 通讯作者: 王志胜 E-mail:wangzhisheng@nuaa.edu.cn
  • 基金资助:
    航空科学基金(201928052006);贵州省科技计划项目([2020]2Y044)

Predictive fifth-degree cubature Kalman filter method

Xiangdan ZHAO, Biao WANG, Zhisheng WANG(), Zhong YANG   

  1. College of Automation,Nanjing University of Aeronautics and Astronautics,Nanjing 210016,China
  • Received:2021-12-14 Revised:2021-12-31 Accepted:2022-03-21 Online:2023-03-25 Published:2022-04-12
  • Contact: Zhisheng WANG E-mail:wangzhisheng@nuaa.edu.cn
  • Supported by:
    Aeronautical Science Foundation of China(201928052006);Guizhou Provincial Science and Technology Projects([2020]2Y044)

摘要:

为适用于强非线性、非高斯过程噪声系统,结合预测滤波(PF)与高阶容积卡尔曼滤波(HCKF),提出一种预测-五阶容积卡尔曼滤波(P5thCKF)方法。通过预测滤波方法对系统模型中的过程噪声及其方差阵进行实时调整,进而将新模型代入到五阶容积卡尔曼滤波框架中进行实时递推状态估计。推导了五阶球面单形-径向积分准则,采用五阶球面单形积分准则处理球面积分,广义高斯-拉盖尔积分准则处理径向积分;描述了预测滤波方法并对模型误差调整量进行了推导。通过2个仿真实验验证了本文方法在强非线性、非高斯过程噪声系统中的可行性以及应用于工程实践的可能性。

关键词: 预测滤波, 高阶容积卡尔曼滤波, 预测-五阶容积卡尔曼滤波, 五阶球面单形积分准则, 广义高斯-拉盖尔积分准则

Abstract:

A Predictive fifth-degree Cubature Kalman Filter (P5thCKF) method, which combines the Predictive Filter (PF) and the High-degree Cubature Kalman Filter (HCKF) is proposed for strongly nonlinear and non-Gaussian process noise systems. The PF is used to adjust the process noise and variance matrix in the system model in real time, and then the new model is put into the fifth-degree cubature Kalman filter framework to perform real-time recursive state estimation. The fifth-degree spherical simplex-radial rule is derived and is used to deal with spherical integration, and the generalized Gauss-Laguerre integral rule is used to deal with radial integration. The predictive filtering method is described, and the error adjustment amount of the model derived. The feasibility of the proposed method in strongly nonlinear and non-Gaussian process noise systems and its possible application to engineering practice are verified by two simulation experiments.

Key words: predictive filter, high-degree cubature Kalman filter, predictive fifth-degree cubature Kalman filter, fifth-degree spherical simplex rule, generalized Gauss-Laguerre integral rule

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