A Fast Satellite Selection Algorithm for GPS / BD Integrated Navigation System Based on K-means++ Clustering Algorithm

The GPS/BD integrated navigation system improves the positioning accuracy and reliability compared with the single system, but makes the calculation amount increase exponentially. In order to improve the real-time performance of the integrated navigation system, a fast satellite selection algorithm based on K-means++ clustering algorithm is proposed. After preferentially selecting a satellite with the highest elevation angle, the method performs K-means++ clustering algorithm on the remaining satellites, and then selects one satellite in each cluster to obtain the final satellite selection combination. The simulation results show that the probability of GDOP less than 2.5 obtained by this method is approximately 100%, and the probability that the difference between the method and the traditional GDOP satellite selection method less than 0.1 is 94.3%, but the time is reduced by 99.11%. It is proved that the method greatly improves the real-time performance while satisfying the positioning accuracy.