现针对近年来室内定位的需求,为提高整体的定位精度,提出一种基于 sine混沌映射与正余弦优化蛇优化(Snake Optimization,SO)算法的超宽带(Ultra-Wide Band,UWB)室内定位技术,并结合一种自适应的测距值调整策略将测距值作为 SO算法适应度函数的参数.SO是一种元启发式,模仿蛇觅食加交配行为的新型智能优化算法.为提高优化方法寻优能力,在 SO种群初始化阶段引入混沌映射,增加种群个体的多样性.在雄性个体和雌性个体位置更新之后,为协调算法的全局探索和局部探索的性能,再进行一次正弦余弦算法(Sine and Cosine Algorithm,SCA).实验结果表明,对于室内环境,该方法能够有效提高定位精度且性能良好.对比传统的智能算法,其算法精度和收敛效率都得到了显著的提高.
Application of Improved Snake Optimization Algorithm in Indoor UWB Positioning
To meet the need of indoor positioning in recent years and increase the overall positioning accuracy,a Ultra-Wide Band(UWB)indoor positioning technology based on a Snake Optimization(SO)with sine chaotic mapping and sine cosine optimization is proposed,which is combined with an adaptive measuring value adjustment strategy and takes the ranging values as parameters of SO's fitness function.SO is a new metaheuristic and intelligent algorithm which imitates the foraging behavior and mating behavior of snake.To improve optimization ability of the algorithm,the chaotic map is introduced into the population initialization of SO to increase individuals'diversity.After location updating of males and females,combine the updated locations with Sine and Cosine Algorithm(SCA)to coordinate global exploration and local exploration.The experiment results show that under the indoor environment,the method can increase positioning accuracy effectively and its performance is good.Compared to other traditional intelligent algorithms,the positioning accuracy and convergence efficiency of improved SO algorithm has significant improvement.
indoor positioningSOUWBchaotic mappingsine and cosine optimization algorithm
国家科技期刊平台
NSTL
万方数据
维普
