Indoor localization algorithm in high dynamic environment based on W-ELM

• Main Authors: Zhou Shiyue, Zhang Jing
• Format: Article
• Language: English
• Published: Academic Journals Center of Shanghai Normal University 2017-04-01
• Series: Journal of Shanghai Normal University (Natural Sciences)
• Subjects: indoor localization; high dynamic environment; weighted extreme learning machine
• Online Access: http://qktg.shnu.edu.cn/zrb/shsfqkszrb/ch/reader/view_abstract.aspx?file_no=20170206&flag=1

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.