Predictive NLOS Detection for UWB Indoor Positioning Systems Based on the CIR
2018 15th Workshop on Positioning, Navigation and Communications (WPNC)(2018)
摘要
Modern indoor positioning systems are used to track machines or navigate people. Besides localization accuracy, one emerging key requirement is the robustness of a system with regard to changes in the environment. One mechanism to improve this robustness is the detection of Non-line-of-sight (NLOS) situations. In this paper, a novel, predictive NLOS detection concept is introduced. Moving objects induce changes in the Channel Impulse Response. While close-range obstacles are identified by a pulsing first path peak amplitude, objects further away can be detected using a Gabor filter bank. Both features for detection have been investigated in ideal and real-world environments with the results showing clear evidence that our novel method is delivering good-confidence NLOS detection.
更多查看译文
关键词
Gabor filter bank,object detection,close-range obstacle identification,nonline-of-sight detection,machine tracking,people navigation,channel impulse response,localization accuracy,CIR,UWB indoor positioning systems,pulsing first path peak amplitude,predictive NLOS detection concept
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要