熊芝, 岳翀, 薛彬. 基于IAGA的空间测量定位系统测站优化部署[J]. 应用光学, 2016, 37(4): 561-566. DOI: 10.5768/JAO201637.0403001
引用本文: 熊芝, 岳翀, 薛彬. 基于IAGA的空间测量定位系统测站优化部署[J]. 应用光学, 2016, 37(4): 561-566. DOI: 10.5768/JAO201637.0403001
Xiong Zhi, Yue Chong, Xue Bin. Station deployment of workspace measuring and positioning system based on improved adaptive genetic algorithm[J]. Journal of Applied Optics, 2016, 37(4): 561-566. DOI: 10.5768/JAO201637.0403001
Citation: Xiong Zhi, Yue Chong, Xue Bin. Station deployment of workspace measuring and positioning system based on improved adaptive genetic algorithm[J]. Journal of Applied Optics, 2016, 37(4): 561-566. DOI: 10.5768/JAO201637.0403001

基于IAGA的空间测量定位系统测站优化部署

Station deployment of workspace measuring and positioning system based on improved adaptive genetic algorithm

  • 摘要: 空间测量定位系统是一种基于光电扫描的角度交汇测量系统,由于该系统是在多测站协同作用下实现坐标测量,因此测站的布局优化是应用时面临的重要问题。为了解决该问题,提出了一种基于改进自适应遗传算法的测站优化部署方案。以系统定位精度、覆盖度和使用成本作为多目标优化函数;将进化代数衰减因子与自适应遗传算法相结合,根据多目标函数建立改进自适应遗传算法优化流程;对2~4个测站进行仿真优化分析。仿真结果表明,与传统自适应遗传算法相比,该方法能在10~20代内收敛到最优解并获得更优的目标函数值。因此该方法在空间布局优化设计中能有效提高系统的测量性能。

     

    Abstract: Workspace measuring and positioning system (wMPS) is a multistation intersection system based on photoelectric scanning. Since wMPS is dependent on the multistation synergy to achieve the coordinate measuring, the station layout optimization is an important problem. Optimal station topological geometry based on improved adaptive genetic algorithm was proposed. Firstly, the positioning accuracy, coverage area and cost were taken as objectives to establish the multiobjective optimization function. Secondly, through combining evolving algebra attenuation factor with adaptive genetic algorithm, improved adaptive genetic algorithm optimization process was established according to multiobjective function. Finally, simulation analysis for layout optimization algorithm of 2~4 stations was performed. The results show that compared with adaptive genetic algorithm, the proposed method can converge to the optimal solution within 10~20 generations and get better objective function value. Therefore, this method is able to improve wMPS measuring performance in spatial layout design.

     

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