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[Institution of Engineering and Technology 12th European Conference on Antennas and Propagation (EuCAP 2018) - London, UK (9-13 April 2018)] 12th European Conference on Antennas and Propagation (EuCAP 2018) - Remote Vital Sign Recognition through Machine Learning augmented UWB
摘要： This paper describes an experimental demonstration of machine learning (ML) techniques supplementing radar to distinguish and detect vital signs of users in a domestic environment. This work augments an intelligent location awareness system previously proposed by the authors. That research employed Ultra-Wide Band (UWB) radar complemented by supervised machine learning techniques to remotely identify a person’s room location via ?oor plan training and time stamp correlations. Here, the remote breathing and heartbeat signals are analyzed through Short Term Fourier Transformation (STFT) to determine the Micro-Doppler signature of those vital signs in different room locations. Then, Multi-Class Support Vector Machine (MC-SVM) is implemented to train the system to intelligently distinguish between vital signs during different activities. Statistical analysis of the experimental results supports the proposed algorithm. This work could be used to further understand, for example, how active older people are by engaging in typical domestic activities.
关键词： Short Term Fourier Transform (STFT),Breathing,Ultra-Wide Band (UWB),Multi-Class Support Vector Machine (MC-SVM),Heartbeat,Indoor Positioning System (IPS)
更新于2025-09-23 15:22:29
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[IEEE 2019 PhotonIcs & Electromagnetics Research Symposium - Spring (PIERS-Spring) - Rome, Italy (2019.6.17-2019.6.20)] 2019 PhotonIcs & Electromagnetics Research Symposium - Spring (PIERS-Spring) - A Singular Value Decomposition Based Approach for Classifying Concealed Objects in Short Range Polarimetric Radar Imaging
摘要： In current research one of the main challenges in short range synthetic aperture radar (SAR) is electrically small structures and objects, which tend to unclear reinforced or through the wall objects, object orientation angle, and obscure contribution to extract the position of concealed multiple small objects. In this paper, ultra-wide-band (UWB) polarimetric radar was used to study reinforced objects and for estimation of object angle at short range. Electrically small 1D periodic mesh, 2D periodic meshes and di?erently oriented small objects or meshes could not be distinguished in conventional SAR images. A radar system with transmit and receive antennae mounted on a two dimensional scanning grid was used. The aim is non-destructive testing of built structures, in concrete slab manufacturing and for use in the renovation process. UWB short range radar data and images corresponding to di?erent polarization states were analysed by using singular value decomposition (SVD). To perform decomposition, the proposed approach applies SVD to image data matrices produced from the back projection algorithm (BPA) to classify the di?erent objects and identify the object angle. Then, sets of singular-components of di?erent polarization states are analysed to classify objects. Also, the BPA algorithm is performed to construct the object images from the polarimetric radar signals. The object re?ection varied with the polarimetric state of the UWB radar, which contributes to di?erent object signatures (i.e., object intensity) since the object signature depends on the orientation, the size, and the number of objects. Object orientation with respect to the radar system and object anisotropy could be determined from the ratio of the di?erent polarimetric singular-components. This proposed complex data analysis method demonstrates the usefulness of the SVD using BPA in extracting more information about and for classifying an object.
关键词： back projection algorithm (BPA),object classification,ultra-wide-band (UWB) polarimetric radar,Synthetic aperture radar (SAR),singular value decomposition (SVD)
更新于2025-09-19 17:13:59
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[IEEE 2018 9th International Conference on Ultrawideband and Ultrashort Impulse Signals (UWBUSIS) - Odessa (2018.9.4-2018.9.7)] 2018 9th International Conference on Ultrawideband and Ultrashort Impulse Signals (UWBUSIS) - Application of the Industry 4.0 Paradigm to the Design of a UWB Radiolocation System for Humanitarian Demining
摘要： The modern world is characterized by the pervasive use of computers, sensors, robotics, and Internet connectivity. This represents a new industrial revolution, dubbed Industry 4.0. In this paper, we discuss the application of the Industry 4.0 paradigm to creating a robotic search-and-detection platform intended for humanitarian demining. This is based on the combination and interaction of two microwave radars - including a UWB multi-sensor array, and a holographic imager - as well as 3-D optical cameras, remote navigation, and GPS tracking. The concepts introduced by Industry 4.0 represent an important opportunity for the scientific community to adopt new approaches in the design and use of UWB radar systems, and how data from these systems can be shared, archived, and processed in a decentralized manner accessible to the worldwide community
关键词： holographic radar,unexploded ordnance (UXO),computer simulations,georadar,landmine,Industry 4.0,ultra-wide-band (UWB) radar,humanitarian demining,improvised explosive device (IED),robotic platform,detection
更新于2025-09-09 09:28:46