基于NSGA-Ⅱ算法的地基伪卫星定位系统布站方法研究

Base station distribution method of ground-based pseudolite system based on NSGA-Ⅱ algorithm

在地基伪卫星定位系统独立组网时,可将其布站问题转换为多目标优化问题求解,以提高系统信号覆盖率、优化基站几何布局为目标,从而达到减少基站数量同时保证良好定位精度的目的。提出了基于带精英策略的非支配排序遗传(NSGA-Ⅱ)算法的伪卫星系统多目标布站方法,通过可视域分析技术确定系统信号覆盖率,并采用一种多矩阵相乘的加权水平精度因子计算方法衡量基站几何布局,最后利用NSGA-Ⅱ算法求解两个优化目标的非支配最优解集。以张家界某山区地形进行仿真,结果显示只需28个基站系统信号覆盖率就可以达到90%,同时能保证系统基站几何布局较优,性能优于普通遗传算法,在实际工程布站应用中有一定的指导意义。

When the ground-based pseudolite positioning system is independent networking,distribution of base station is a multi-objective optimization problem to improve the system signal coverage and optimize the geometric layout of the base stations,thereby reduces the number of base stations and ensures positioning accuracy. This paper proposed the pseudolite base station distribution method based on the non-dominated sorting genetic algorithm( NSGA-Ⅱ) with elite strategy. The method used the visual domain analysis technology to calculate the system signal coverage and evaluate the geometric layout of the base stations by a weighted geometric precision factor of multi-matrix multiplication. Finally,the NSGA-Ⅱ algorithm searched the non-dominated optimal solution set of two optimization targets. The simulation of a mountainous area in Zhangjiajie shows only28 base stations can ensure the system signal coverage reach 90%. At the same time,base station geometry is also good,the performance is better than the traditional genetic algorithm,it has certain guiding significance in practical engineering applications.