非视线传播
基站
计算机科学
鉴定(生物学)
指纹(计算)
算法
人工智能
计算机网络
电信
无线
植物
生物
标识
DOI:10.1109/lcomm.2024.3352826
摘要
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 ${W}$ iFi- ${A}$ ided ${U}$ WB ${L}$ 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.
科研通智能强力驱动
Strongly Powered by AbleSci AI