| 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. |
| 关键词: 室内定位 高动态环境 加权极速学习机 |
| DOI：10.3969/J.ISSN.100-5137.2017.02.006 |
| 分类号: |
| 基金项目: |
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| Indoor localization algorithm in high dynamic environment based on W-ELM |
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Zhou Shiyue, Zhang Jing
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College of Information, Mechanical and Electrical Engineering, Shanghai Normal University, Shanghai 200234, China
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| Abstract: |
| With increasing needs of people on the indoor location-based services,indoor localization research becomes more and more important.With the developing of smart city,Wi-Fi is getting more popular than before because of its moderate transmission distance.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. |
| Key words: indoor localization high dynamic environment weighted extreme learning machine |
