Non-Line-of-Sight Identification Without Channel Statistics
作者
Bruno Silva,Gerhard P. Hancke
标识
DOI:10.1109/iecon43393.2020.9255110
摘要
Identifying non-line-of-sight (NLOS) conditions is important to discard, or improve, any location estimates that have been estimated with NLOS ranges. Typically, NLOS identification relies on channel statistics that have been collected for both LOS and NLOS channels. We investigate NLOS identification using distance residuals instead. The results show that distance residuals can be used to identify location estimates with NLOS ranges with very high accuracy, and that in some cases, individual NLOS ranges can also be identified.