A satellite selection method based on maturity factor mapping in multi-GNSS positioning

In the process of selecting satellites, the geometric dilution of precision (GDOP) is commonly utilized to identify a group of satellites that can provide high solution accuracy. However, traditional satellite selection method usually relies on traversal, which often leads to large amounts of computation when there are many visible satellites. Conventional genetic algorithms usually fix the crossover and mutation probabilities, resulting in unnecessary time consumption. To address these problems, this paper proposes a dual-system satellite selection genetic algorithm based on maturity factor mapping to quickly find an acceptable solution. Compared with other existing genetic algorithms for satellite selection, this paper proposes maturity factor to reflect the monotonicity of the current population gene pool. Adjusting the crossover and mutation probabilities by the maturity factor not only mitigates the risk of falling into local optimality in the long term but also reduces computation time.