WiFi-Aided Ultra Wideband Localization in Indoor NLoS Environment
Qiankun Kong
Abstract
The Non-Line-of-Sight (NLoS) base station is the main factor making Ultra Wideband (UWB) localization accuracy decrease. To handle this issue, we propose a <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">${W}$ </tex-math></inline-formula> iFi- <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">${A}$ </tex-math></inline-formula> ided <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">${U}$ </tex-math></inline-formula> WB <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">${L}$ </tex-math></inline-formula> ocalization (WAUL) system in this letter, including 1) NLoS base station identification algorithm, 2) fusion localization algorithm combining WiFi fingerprint-based and UWB range-based localization results. Specifically, the proposed identification algorithm first divides the ranging results of different UWB base stations into a few of subsets, and obtains different location estimated results by these subsets, then identifies NLoS base stations and filters them out before a location decision is made, hence maintaining localization accuracy under NLoS environment. Furthermore, WiFi fingerprint-based localization technology is leveraged in WAUL to calibrate the localization results obtained from UWB for providing a accurate result. Experimental results in a real scenario show that WAUL can effectively identify the NLoS base stations and enable to enhance localization accuracy.