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基于加权极速学习机室内高动态环境的定位算法

Indoor localization algorithm in high dynamic environment based on W-ELM
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摘要 随着人们对室内基于位置服务的需求越来越大,室内定位的研究变得越来越重要.Wi-Fi由于其传输距离适中,在智慧城市发展的推动下,热点的覆盖也非常多.因此基于Wi-Fi的定位技术成为众多室内定位技术中最具有可行性的.面对室内无线环境高动态变化的情况,提出了基于加权极速学习机(W-ELM)的定位方法,实验证明该方法能够有效提高定位精度. With increasing needs of people on the indoor location-based services,indoor localization research becomes more andmore important. With the developing of smart city,Wi-Fi is getting more popular than before because of its moderate transmissiondistance. Thus, Wi-Fi based location method is the most feasible technology among many other types of indoor location methods. For the problem of signal changes dynamically in indoor environment, we proposed a weighted extreme learning machine ( W-ELM ) -based indoor localization algorithm to build a stable model, and experiment results show that this method can effectively improve the positioning accuracy.
作者 周世悦 张静
出处 《上海师范大学学报(自然科学版)》 2017年第2期206-212,共7页 Journal of Shanghai Normal University(Natural Sciences)
关键词 室内定位 高动态环境 加权极速学习机 indoor localization high dynamic environment weighted extreme learning machine
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  • 1张友德,涂时亮,陈章龙.MC68HC08系列单片机原理与应用[M].上海:复旦大学出版社,2001. 被引量:1

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