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基于NSGA-II算法的多目标快速选星方法

Multi-Objective and Fast Satellite Selection Method Based on the NSGA-II Algorithm

  • 摘要: 全球卫星导航系统多系统选星问题能够转化为有约束条件的多目标优化问题求解,可以同时优化几何精度因子和选星数目这两个目标,从而在减少接收机运算量的同时获得良好的定位精度。提出了一种基于NSGA-Ⅱ算法的多目标快速选星方法,该方法利用选星问题的序贯性生成初始种群,改进了约束处理方法,并选取合适的遗传算子和效用函数做出选星决策。通过仿真,证实该选星方法具有良好的可靠性和实时性,且不依赖于卫星的几何位置分布,可适用于有障碍或者遮挡的复杂情况。

     

    Abstract: For multi-Global Navigation Satellite System constellations, satellite selection can be considered as a constrained multi-objective optimization problem to optimize the Geometric Dilution of Precision (GDOP) and number of selected satellites simultaneously, as a result reduce computation of the receiver and improve positioning accuracy. Here we describe a method based on the NSGA-Ⅱ algorithm, which utilizes the sequential characteristic of satellite selection to generate the initial population, as well as improves constraint handling, appropriate genetic operatorand utility function to achieve fast satellite selection.The simulation results show that the proposed method has high reliability and real-time performance and does not rely on the geometric distribution of satellites, making it suitable for complex environments with obstacles and shelters.

     

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