An improved satellite selection algorthm based on fuzzy comprehensive evaluation method and the entropy method for determining the weight of evaluation indicators

In Global Navigation Satellite Systems (GNSS), the satellite selection algorithm is very important for increasing navigation location precision, in which visible satellite geometry is the most crucial factor. There are two algorithms for selecting stars: one is by calculating GDOP such as classical optimal algorithm, best GDOP algorithm and so on. However, it requires a long time for the computing procedure and must reselect stars to compute every 15 minutes. By comparison, the other is fuzzy selecting star algorithm, which has an advantage on a shorter computing time and almost the same performance as classical optimal algorithm. But it refers to the determination of weight of evaluating indicators which always takes the experience value but doesn´t have the religious mathematical model as a support. Based on fuzzy selecting star algorithm, this paper proposes an improved algorithm by using the Entropy method for determination of weight of evaluating indicators. Simulation results indicate that the algorithm in this paper has almost the same performance as the previous algorithm, but less time-consuming and better position accuracy.