Device-Free Person Detection and Ranging in UWB Networks

TL;DR

This paper introduces a new device-free person detection and ranging method using UWB networks that detects human presence through low-frequency signal variations without needing prior training data.

Contribution

It presents a novel detection approach leveraging low-frequency variations caused by humans in UWB signals, eliminating the need for template waveform databases.

Findings

High detection probability demonstrated through simulations and experiments

Method effective in indoor environments with off-the-shelf UWB devices

No training database required for operation

Abstract

We present a novel device-free stationary person detection and ranging method, that is applicable to ultra-wide bandwidth (UWB) networks. The method utilizes a fixed UWB infrastructure and does not require a training database of template waveforms. Instead, the method capitalizes on the fact that a human presence induces small low-frequency variations that stand out against the background signal, which is mainly affected by wideband noise. We analyze the detection probability, and validate our findings with numerical simulations and experiments with off-the-shelf UWB transceivers in an indoor environment.