| Citation: | QIU Ming, YAN Yongjie, SUN Rui, et al. Imperialist competitive optimized dual-objective comprehensive decision algorithm for satellite selection[J]. Journal of Beijing University of Aeronautics and Astronautics, 2021, 47(8): 1646-1655. doi: 10.13700/j.bh.1001-5965.2020.0235(in Chinese)
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With the development of Global Navigation Satellite System(GNSS), the prospect of GNSS has been widely recognized in the world. In particular, the positioning solutions with fast and accuracy calculation are essential for the GNSS receiver design. The most of the current satellite selection algorithms in the GNSS receiver fix the number of satellites in advance, which limits the performance of the algorithm. This paper proposes an Imperialist Competitive Algorithm (ICA) for satellite selection. In order to obtain better geometric configuration of satellite constellation, the prior information (elevation and azimuth of visible satellite) is introduced for prior constraint. The Geometric Dilution of Precision (GDOP) and number of satellites are two objectives of the optimization algorithm. Comprehensive decisions are used to quickly select satellites, making the selection of satellites more flexible, as well as reducing the computational burden of multi-constellation satellite receivers. Experiment results based on simulation and field data showed that, after priori constraints are introduced, at elevation angle 5°, the average number of satellites selected by the algorithm proposed in this paper is 51.8% of the maximum visible satellites based on simulation data and the average number of satellites is 45.4% of the maximum visible satellites based on field data. The average GDOP is decreased by 0.209 2 and 0.248 4 compared to the satellite selection without a priori constraint. At the same time, the average calculation time for once satellite selection is about 0.168 4 s and 0.303 1 s, with an improvement of 95.79% and 92.42% compared to the time consumption (i.e. 4 s) of the traversal method.
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