基于有色噪声卡尔曼滤波的GPS多径估计研究

GPS Multipath Estimation Based on Colored Noise Kalman Filtering

  • 摘要: 在最大似然多径估计技术的基础上,提出了一种新的基于有色噪声卡尔曼滤波的全球定位系统(GPS)多径信号估计技术. 建立了GPS多径信号的卡尔曼滤波估计模型,推导了观测噪声为有色噪声的卡尔曼滤波的状态方程和观测方程,阐述了有色噪声的形成过程,推导了卡尔曼滤波的递推公式. 实验结果表明,提出的设计技术可以在20dB·Hz的载噪比条件下对多个GPS多径信号进行较精确的估计.

     

    Abstract: Making use of the theory of maximum likelihood estimation (MLE), a new multipath estimation method based on colored noise Kalman filter to estimate GPS multipath signal is put forward. A linear model of correlation outputs for multipath estimation based on Kalman filtering was built. The state equation and observation equation of Kalman filter were deduced when the observed noise was colored noise, and the generation process of colored noise was explained. The recursive formula of Kalman filter was deduced, which was used to execute iterative filtering of MLE output. Experimental results show that the new design has better performance than MLE, and it can get the precise estimation of multipath signal under 20dB·Hz of CNR.

     

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