In this communication, we introduce a channel model for personal radar applications where a millimeter-wave (mm-wave) massive array is required to scan the environment and to reconstruct a map of it. The analysis is based on measurement campaigns, in a corridor and in an office room, performed using mm-wave massive arrays. In such a context, we aim at characterizing the channel from both a temporal and an angular perspective by exploiting a 2D CLEAN-like technique to extrapolate the multipath components and a K-means algorithm for clustering, where centroids statistics depend on the environment contour. The obtained channel model can be exploited for mapping algorithms based on backscattered radar measurements.
A millimeter-wave indoor backscattering channel model for environment mapping
Guidi Francesco;
2017
Abstract
In this communication, we introduce a channel model for personal radar applications where a millimeter-wave (mm-wave) massive array is required to scan the environment and to reconstruct a map of it. The analysis is based on measurement campaigns, in a corridor and in an office room, performed using mm-wave massive arrays. In such a context, we aim at characterizing the channel from both a temporal and an angular perspective by exploiting a 2D CLEAN-like technique to extrapolate the multipath components and a K-means algorithm for clustering, where centroids statistics depend on the environment contour. The obtained channel model can be exploited for mapping algorithms based on backscattered radar measurements.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.