航空学报 > 2017, Vol. 38 Issue (12): 321410-321410   doi: 10.7527/S1000-6893.2017.321410

七阶正交容积卡尔曼滤波算法

孟东, 缪玲娟, 邵海俊, 沈军   

  1. 北京理工大学 自动化学院, 北京 100081
  • 收稿日期:2017-05-12 修回日期:2017-08-20 出版日期:2017-12-15 发布日期:2017-08-20
  • 通讯作者: 缪玲娟 E-mail:miaolingjuan@bit.edu.cn
  • 基金资助:
    国家自然科学基金(61153002,61473039)

A seventh-degree cubature quadrature Kalman filter

MENG Dong, MIAO Lingjuan, SHAO Haijun, SHEN Jun   

  1. College of Automation, Beijing Institute of Technology, Beijing 100081, China
  • Received:2017-05-12 Revised:2017-08-20 Online:2017-12-15 Published:2017-08-20
  • Supported by:
    National Natural Science Foundation of China (61153002, 61473039)

摘要: 在高斯滤波框架下,阶次越高,近似精度越高。为提高滤波精度,通过提高阶次,提出了七阶正交容积卡尔曼滤波(CQKF)算法。在传统CQKF算法的基础上,该算法扩展了线性积分的近似阶次,提出了七阶球面积分的确定性采样方法;进而扩展了球-半径准则,提高了滤波估计精度。飞行器目标跟踪的仿真实验证明了该算法的有效性,证明了七阶CQKF比五阶CQKF、三阶容积卡尔曼滤波器(CKF)和无迹卡尔曼滤波器(UKF)有更高的滤波精度。

关键词: 高阶正交滤波器, CKF, 飞行器目标跟踪, 七阶CQKF, UKF

Abstract: In the Gaussian filter frame, the higher the order, the higher the accuracy of the approximation. To improve the filtering accuracy, a seventh-degree Cubature Quadrature Kalman Filter (CQKF) algorithm is proposed by improving the degree. Based on the traditional CQKF, the algorithm extends the approximate degree of linear integrals, and proposes a deterministic sampling method for the seven-degree spherical integral. Then the spherical-radial rule is extended to improve the accuracy of the filter. The simulation results of the aircraft target tracking demonstrate the effectiveness of the algorithm. It is proved that the seventh-degree CQKF is more accurate than the fifth-CQKF, third-degree Cubature Kalman Filter (CKF) and Unscented Kalman Filter (UKF).

Key words: high-degree orthogonal filter, CKF, aircraft target tracking, seventh-degree CQKF, UKF

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