中文摘要：

提出了一种基于增广参数Kalman滤波的多路径效应系统误差估计方法，将系统误差作为状态参数，并对其建立一阶AR模型，同时利用多路径重复性特性，更新多路径误差改正模型，在一定程度上解决了固定多路径误差模型随着时间推移重复性减小而有效性降低的问题，并利用16d实测数据例证了本方法具有一定的可行性和有效性。

英文摘要：

In the high-precision positioning with GPS, when the environment of the surveying point keep little changed, the multipath effect has strong repeatability. With this character- istic establishing the error correction model is an effective method to weaken the multipath effect influence. But as the time interval goes on, its repeatability decreases, and the corre- sponding effectiveness of this method drastically reduces. Therefore, based on augmented parameters Kalman filtering this paper proposes a multipath effect system error estimation method with state matrix augmentation, taking the systematic errors as state parameters and establishing AR model of first class, meanwhile using multipath repeatability characteristics to update multipath error correction model. With this method, the problem of that as the time goes on the repeatability decrease and the corresponding effectiveness of fix multipath error correction model reduces has been resolved to a certain extent. Finally, an example with 16 days GPS observation data has proved that this method has a certain feasibility and effectiveness.