Citation: | SHI T,ZHUANG X B,LIN Z J,et al. Satellite selection based on parallel genetic algorithm for high orbit autonomous satellite navigation[J]. Journal of Beijing University of Aeronautics and Astronautics,2023,49(12):3528-3536 (in Chinese) doi: 10.13700/j.bh.1001-5965.2022.0118 |
After the BeiDou-3 navigation satellite system was finished, the performance of high-orbit autonomous navigation was improved, but it also occasionally resulted in the redundancy of visible satellites. In order to reduce the arithmetic operations to ensure the real-time performance, based on a multiple-population parallel genetic algorithm (PGA), a new method to quickly select the optimal combination of visible satellites was proposed. The algorithm chooses the weighted dilution of precision (WDOP) as the fitness function, uses sub-populations in coarse-grained to speed up the search, and improves the searchability through the differential setting of mutation factors and the information exchange between sub-populations. The simulation experiments result of 7 or more satellite selection tasks in several typical high orbit environments show that the average absolute error between the PGA-based selection algorithm solution and the optimal solution obtained by the ergodic method is less than 0.1, and the maximum relative error is less than 1%. The outcomes demonstrate that, when the receiver employs the four-system integrated navigation in a typical high-orbit environment, the algorithm can efficiently execute the task of choosing satellites for the specified number of satellites fast and precisely.
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