GNSS Multipath Mitigation Method Based on K-means Classification in Urban Environment

Multipath effect occurs when using the Global Navigation Satellite System (GNSS) in urban environments. Multipath effect means that when the GNSS antenna receives satellite signals, it not only receives direct signals on the direct path, but also signals from the indirect path reflected or diffracted by surrounding objects. Multipath leads to measurement deviation, which leads to inaccurate estimated position. In order to improve positioning accuracy, this paper uses k -means clustering and multipath mitigation methods to reduce multipath errors. Among them, the k -means clustering method is to classify the direct signal and the multipath signal, and uses a multipath suppression algorithm, in which the model coefficient of code deviation is estimated by the combination of least squares and self-regression, and the multipath delay is constructed with a solution. Experiments show that the k -means algorithm can distinguish 96% of direct signals and 85% of multipath signals. Compared with RBF and Liner, the classification accuracy is increased by 43% and 41%, respectively. The multipath mitigation algorithm used greatly improves the positioning accuracy.