Two-stage line of sight (los)/non-line of sight (nlos) classifier

Abstract

A multi-environment LOS/NLOS classifier for a UWB ranging device includes an environment classifier and an LOS/NLOS classifier. The environment classifier uses a convolutional neural network (CNN) fed by channel impulse response (CIR) of a received radio signal, cascaded with a multilayer perceptron (MLP) fed by a set of statistical characteristics extracted from the CIR. The environment classifier provides an environment class to the LOS/NLOS classifier, typically an MLP also receiving as input the output of the CNN and another set of statistical and physical characteristics extracted from the CIR. The environment class may form a model input to the MLP operating as an LOS/NLOS classifier, or it may be a modulation parameter of the MLP, typically a bias or weight modification factor of the MLP.

Dependencies are inferred from the claim text.