3-D BLE Indoor Localization Based on Denoising Autoencoder.

	3-D BLE Indoor Localization Based on Denoising Autoencoder.
	Xiao, Chao ; Yang, Daiqin ; Chen, Zhenzhong ; Tan, Guang
刊名	IEEE ACCESS
	2017
文献子类	期刊论文
英文摘要	Bluetooth low energy (BLE)-based indoor localization has attracted increasing interests for its low-cost, low-power consumption, and ubiquitous availability in mobile devices. In this paper, a novel denoising autoencoder-based BLE indoor localization (DABIL) method is proposed to provide high-performance 3-Dpositioning in large indoor places. A deep learning model, called denoising autoencoder, is adopted to extract robust fingerprint patterns from received signal strength indicator measurements, and a fingerprint database is constructed with reference locations in 3-D space, rather than traditional 2-D plane. Field experiments show that 3-D space fingerprinting can effectively increase positioning accuracy, and DABIL performs the best in terms of both horizontal accuracy and vertical accuracy, comparing with a traditional fingerprinting method and a deep learning-based method. Moreover, it can achieve stable performance with incomplete beacon measurements due to unpredictable BLE beacon lost.
URL标识	查看原文
语种	英语
内容类型	期刊论文
源URL	[http://ir.siat.ac.cn:8080/handle/172644/12548]
专题	深圳先进技术研究院_数字所
作者单位	IEEE ACCESS
推荐引用方式 GB/T 7714	Xiao, Chao , Yang, Daiqin , Chen, Zhenzhong ,et al. 3-D BLE Indoor Localization Based on Denoising Autoencoder.[J]. IEEE ACCESS,2017.
APA	Xiao, Chao , Yang, Daiqin , Chen, Zhenzhong ,& Tan, Guang.(2017).3-D BLE Indoor Localization Based on Denoising Autoencoder..IEEE ACCESS.
MLA	Xiao, Chao ,et al."3-D BLE Indoor Localization Based on Denoising Autoencoder.".IEEE ACCESS (2017).