自适应无迹卡尔曼滤波算法在地磁导航中的应用

An Adaptive UKF Algorithm and Its Application to Geomagnetic Navigation

  • 摘要: 考虑到地磁导航过程中,无迹卡尔曼滤波(UKF)受初始值误差、系统噪声不确定性和环境磁异常扰动这些因素的影响,将自适应估计原理引入到UKF算法,提高UKF算法的收敛性和地磁导航系统的稳定性.计算结果表明,在地磁导航系统数据处理中,UKF算法略优于扩展卡尔曼滤波(EKF),自适应UKF算法优于自适应EKF算法,自适应UKF算法能够很好地抑制初始化误差、系统噪声不确定性和环境磁异常扰动对导航解的影响,进一步提高地磁导航系统的定位精度和可靠性.

     

    Abstract: In the process of geomagnetic navigation,UKF(unscented Kalman filter) are influenced by initial biases,uncertainness of system noises and environmental magnetic abnormal disturbances.Considering these factors,the adaptive estimation principle is incorporated into UKF to improve the convergence of UKF and stability of the geomagnetic navigation system.The calculation result shows that in data processing of geomagnetic navigation system,EKF(extended Kalman filter) algorithm is better than UKF,and adaptive UKF is superior to adaptive EKF algorithm.Adaptive UKF can inhibit initial biases,uncertainness of systemic noises and environment magnetic abnormal disturbances influence on geomagnetic navigation and furthermore improve positioning accuracy and reliability of geomagnetic navigation system.

     

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