An RF-Based Positioning Method for Tracing a Cluster of Moving Scatterers in Non-Stationary Indoor Environments

Author's accepted manuscript© 2021 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.This letter presents a novel iterative positioning method for tracing the body segments of a person moving indoors using radio-frequency (RF) signals. The indoor space is equipped with a multiple-input multiple-output (MIMO) communication system. The person is modelled by a cluster of moving point scatterers, playing the role of moving body segments. The proposed technique estimates the time-variant (TV) positions of the moving scatterers by fitting the TV channel transfer function (TVCTF) of the channel model as close as possible to the TVCTF of the measured channels. Numerical results are presented to demonstrate the accuracy of this method.acceptedVersio

WiHAR : From Wi-Fi Channel State Information to Unobtrusive Human Activity Recognition

Author's accepted manuscript.© 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.acceptedVersio

Doppler Power Characteristics Obtained from Calibrated Channel State Information for Human Activity Recognition

Author's accepted manuscript.© 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.acceptedVersio

Human activity signatures captured under different directions using SISO and MIMO radar systems

In this paper, we highlight and resolve the shortcomings of single-input single-output (SISO) millimeter wave (mm-Wave) radar systems for human activity recognition (HAR). A 2 × 2 distributed multiple-input multiple-output (MIMO) radar framework is presented to capture human activity signatures under realistic conditions in indoor environments. We propose to distribute the two pairs of collocated transmitter–receiver antennas in order to illuminate the indoor environment from different perspectives. For the proposed MIMO system, we measure the time-variant (TV) radial velocity distribution and TV mean radial velocity to observe the signatures of human activities. We deploy the Ancortek SDR-KIT 2400T2R4 mm-Wave radar in a SISO as well as a 2 × 2 distributed MIMO configuration. We corroborate the limitations of SISO configurations by recording real human activities in different directions. It is shown that, unlike the SISO radar configuration, the proposed MIMO configuration has the ability to obtain superior human activity signatures for all directions. To signify the importance of the proposed 2 × 2 MIMO radar system, we compared the performance of a SISO radar-based passive step counter with a distributed MIMO radar-based passive step counter. As the proposed 2 × 2 MIMO radar system is able to detect human activity in all directions, it fills a research gap of radio frequency (RF)-based HAR systems.publishedVersio

A Trajectory-Driven 3D Channel Model for Human Activity Recognition

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A non-stationary relay-based 3D MIMO channel model with time-variant path gains for human activity recognition in indoor environments

Extensive research showed that the physiological response of human tissue to exposure to low-frequency electromagnetic fields is the induction of an electric current in the body segments. As a result, each segment of the human body behaves as a relay, which retransmits the radio-frequency (RF) signal. To investigate the impact of this phenomenon on the Doppler characteristics of the received RF signal, we introduce a new three-dimensional (3D) non-stationary channel model to describe the propagation phenomenon taking place in an indoor environment. Here, the indoor space is equipped with a multiple-input multiple-output (MIMO) system. A single person is moving in the indoor space and is modelled by a cluster of synchronized moving point scatterers, which behave as relays. We derive the time-variant (TV) channel transfer function (CTF) with TV path gains and TV path delays. The expression of the TV path gains is obtained from the instantaneous total received power at the receiver side. This TV total received power is expressed as the product of the TV power of the RF signal initially transmitted and received by a body segment and the TV received power of the redirected signal. These TV powers are determined according the free-space path-loss model. Also, a closed-form approximate solution to the spectrogram of the TVCTF is derived. Here, we analyse the effect of the motion of the person and the validity of the relay assumption on the spectrogram, the TV mean Doppler shift (MDS), and the TV Doppler shift (DS) of the TVCTF. Simulation results are presented to illustrate the proposed channel model.publishedVersio

On the influence of walking people on the Doppler spectral characteristics of indoor channels

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On the Influence of Walking People on the Doppler Spectral Characteristics of Indoor Channels

Author´s accepted manuscript© 2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.When modelling mobile radio channels with moving scatterers, it is generally assumed that the angles of departure (AODs), angles of arrival (AOAs), and the speed of the scatterers are time-invariant. However, this assumption is violated as the AODs and AOAs vary with the positions of the moving scatterers. Also, the speed of the moving scatterers might vary with time due to acceleration/deceleration. In this paper, we model the time-variant Doppler frequencies by taking into account the time-variant AODs, AOAs, and the variations of the speed of the moving scatterers. Furthermore, the complex channel gain of non-stationary single-input-single-output (SISO) fixed-to-fixed (F2F) indoor channels with moving and fixed scatterers is presented. The spectrogram of the complex channel gain using a Gaussian window is provided. The correctness of the analytical solutions is confirmed by simulations. The contribution of this paper paves the way towards the development of a passive in-home activity tracking system.acceptedVersio

The Impact of Human Walking on the Time-Frequency Distribution of In-Home Radio Channels

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