A Satellite Selection Method based on Multi-Constellation GNSS Geometry

Recently, visible GNSS satellites have increased considerably resulting in improved positioning accuracy and reliability. However, the increase caused a substantial computational burden for advanced algorithms such as satellite selection, integer ambiguity resolution, and fault detection. As widely known, the optimal satellite selection method requires so large computational burden that its real-time implementation is practically impossible. In addition, any quasi-optimal satellite selection method suffers from the local minimum problem deviating from the global optimum. To solve this problem, this paper proposes an efficient satellite selection method for the multi-constellation GNSS environment. The proposed method is a geometric assignment method that prevents unacceptable computational burden. To avoid the local optimum problem in a multi-constellation GNSS environment that has not been considered in previous works, the inter-system biases are considered. Through experiments, the proposed selection method is compared with the two well-known quasi-optimal methods.