The Transfer Function of Non-Stationary Indoor Channels and its Relationship to System Functions of LFMCW Radars

This paper studies the relationship between the time-variant (TV) channel transfer function (CTF) of non-stationary indoor channels and the system functions of linear frequency modulated continuous waves (LFMCW) radars. To do so, we consider a moving person/object in indoor environments, which is modelled by a cluster of moving point scatterers. It is shown that the TVCTF can be obtained from the beat signal of LFMCW radar systems. Analytical expressions are derived for the TV demodulated radar response, the complex channel gain, and the TV Doppler-delay profile. A relationship between the presented results and existing non-stationary indoor channel models assuming pulsed wave systems is al…

CORMORANT

People own and carry an increasing number of ubiquitous mobile devices, such as smartphones, tablets, and notebooks. Being small and mobile, those devices have a high propensity to become lost or stolen. Since mobile devices provide access to their owners' digital lives, strong authentication is vital to protect sensitive information and services against unauthorized access. However, at least one in three devices is unprotected, with inconvenience of traditional authentication being the paramount reason. We present the concept of CORMORANT, an approach to significantly reduce the manual burden of mobile user verification through risk-aware, multi-modal biometric, cross-device authentication…

A Trajectory-Driven 3D Non-Stationary mm-Wave MIMO Channel Model for a Single Moving Point Scatterer

This paper proposes a new non-stationary three-dimensional (3D) channel model for a physical millimeter wave (mm-Wave) multiple-input multiple-output (MIMO) channel. This MIMO channel model is driven by the trajectory of a moving point scatterer, which allows us to investigate the impact of a single moving point scatterer on the propagation characteristics in an indoor environment. Starting from the time-variant (TV) channel transfer function, the temporal behavior of the proposed non-stationary channel model has been analyzed by studying the TV micro-Doppler characteristics and the TV mean Doppler shift. The proposed channel model has been validated by measurements performed in an indoor e…

ActRec: A Wi-Fi-Based Human Activity Recognition System

In this paper, we develop a Wi-Fi-based activity recognition system called ActRec, which can be used for the remote monitoring of elderly. ActRec comprises two parts: radio-frequency (RF) sensing and machine learning. In the RF sensing part, two laptops act as transmitter and receiver to record the channel transfer function of an indoor environment. This RF data is collected in the presence of seven human participants performing three activities: walking, falling, and sitting. The RF data containing the fingerprints of user activity is then pre-processed with various signal processing algorithms to reduce noise effects and to estimate the mean Doppler shift (MDS) of each data sample. We pro…

Wi-Sense: a passive human activity recognition system using Wi-Fi and convolutional neural network and its integration in health information systems

AbstractA human activity recognition (HAR) system acts as the backbone of many human-centric applications, such as active assisted living and in-home monitoring for elderly and physically impaired people. Although existing Wi-Fi-based human activity recognition methods report good results, their performance is affected by the changes in the ambient environment. In this work, we present Wi-Sense—a human activity recognition system that uses a convolutional neural network (CNN) to recognize human activities based on the environment-independent fingerprints extracted from the Wi-Fi channel state information (CSI). First, Wi-Sense captures the CSI by using a standard Wi-Fi network interface car…

On the Estimation of the Radial Distance of a Moving Person in Indoor Environments from the Demodulated Response of LFMCW Radars

WiWeHAR: Multimodal Human Activity Recognition Using Wi-Fi and Wearable Sensing Modalities

Robust and accurate human activity recognition (HAR) systems are essential to many human-centric services within active assisted living and healthcare facilities. Traditional HAR systems mostly leverage a single sensing modality (e.g., either wearable, vision, or radio frequency sensing) combined with machine learning techniques to recognize human activities. Such unimodal HAR systems do not cope well with real-time changes in the environment. To overcome this limitation, new HAR systems that incorporate multiple sensing modalities are needed. Multiple diverse sensors can provide more accurate and complete information resulting in better recognition of the performed activities. This article…

The Influence of Human Walking Activities on the Doppler Characteristics of Non-stationary Indoor Channel Models

This paper analyzes the time-variant (TV) Doppler power spectral density of a 3D non-stationary fixed-to-fixed indoor channel simulator after feeding it with realistic trajectories of a walking person. The trajectories of the walking person are obtained by simulating a full body musculoskeletal model in OpenSim. We provide expressions of the TV Doppler frequencies caused by these trajectories. Then, we present the complex channel gain consisting of fixed scatterers and a cluster of moving scatterers. After that, we use the concept of the spectrogram to analyze the TV Doppler power spectral density of the complex channel gain. Finally, we present expressions of the TV mean Doppler shift and …

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 Anc…

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

A robust and unobtrusive human activity recognition system is essential to a multitude of applications, such as health care, active assisted living, robotics, sports, and tele-immersion. Existing well-performing activity recognition methods are either vision- or wearable sensor-based. However, they are not fully passive. In this paper, we develop WiHAR—an unobtrusive Wi-Fi-based activity recognition system. WiHAR uses the Wi-Fi network interface card to capture the channel state information (CSI) data. These CSI data are effectively processed, and then amplitude and phase information is used to obtain the spectrogram. In the subsequent step, the time-variant mean Doppler shift (MDS) caused …