卫星导航信号可变间距采样的多径估计方法

Multipath estimation algorithm using various spacing sampling in satellite navigation signal

为了提高卫星导航信号多径估计的精度,提出一种可变间距采样的多径估计方法.使用一组本地复现码相位由卡尔曼滤波器控制的相关器对相关峰进行可变间距采样,使采样位置尽可能接近直达信号和多径的峰值以提高采样的有效性,从而提高了多径参数的估计精度.分析了卡尔曼滤波器的设计方法和关键参数的选取,并进行了测试.测试证明了在相同相关器数量下,可变间距采样估计比传统固定间距采样估计可以获得更精确的多径参数,同时取得更好的多径消除性能.

An algorithm using various spacing sampling was proposed in order to improve the accuracy of multipath estimation. Kalman filter was applied to achievement of various spacing sampling by con- trolling local reference code phase, through that the final sampling position of correlation function will be adjusted as close as possible to the peaks of direct signal and multipath, thereby increasing accuracy of estimation and performance of multipath mitigation. Filter design method and selection of key pa- rameters were analyzed. It is proved that the various spacing sampling can get a more accurate estima- tion of multipath parameters and achieve better multipath mitigation performance than conventional fixed spacing sampling with the same number of correlators.