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GPS/SINS Positioning Method Based on Robust UKF

机译:基于鲁棒UKF的GPS / SINS定位方法

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摘要

As an improved Unscented Kalman Filtering (UKF) Algorithm, the robust UKF is proposed to solve the positioning accuracy problem of GPS/SINS integrated navigation system used in dynamic environment. The robust estimation theory is applied to the standard UKF algorithm to solve the estimation-error problem in the satellite integrated navigation system. This problem is mainly caused by observation gross-error and the error model uncertainty. Therefore, this new algorithm introduces equivalent covariance matrix based on M-estimated principle. The state equation and observation equation of the system are established to be the mathematical model. The experimental results indicate that the robust UKF can ensure the quality the observation information, as well as improve the accuracy and reliability of the GPS/SINS positioning solution. Besides, it can also improve the receiver's location performance at the presence of gross errors.
机译:作为一种改进的无味卡尔曼滤波(UKF)算法,提出了鲁棒的UKF来解决动态环境下GPS / SINS组合导航系统的定位精度问题。将鲁棒估计理论应用于标准UKF算法,以解决卫星组合导航系统中的估计误差问题。这个问题主要是由观测误差和误差模型的不确定性引起的。因此,该新算法引入了基于M估计原理的等效协方差矩阵。建立系统的状态方程和观测方程作为数学模型。实验结果表明,鲁棒的UKF可以确保观测信息的质量,并提高GPS / SINS定位解决方案的准确性和可靠性。此外,在存在严重错误的情况下,它还可以改善接收机的定位性能。

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