Searched for: author%3A%22Fioranelli%2C+F.%22
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Yuan, S. (author), Zhu, S. (author), Fioranelli, F. (author), Yarovoy, Alexander (author)
The problem of estimating the 3D ego-motion velocity using multi-channel FMCW radar sensors has been studied. For the first time, the problem of ego-motion estimation is treated using radar raw signals. A robust algorithm using multi-channel FMCW radar sensors to instantly determine the complete 3D motion state of the ego-vehicle (i.e.,...
journal article 2023
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Yang, Shufan (author), Le Kernec, Julien (author), Romain, Olivier (author), Fioranelli, F. (author), Cadart, Pierre (author), Fix, Jeremy (author), Ren, Chengfang (author), Manfredi, Giovanni (author), Letertre, Thierry (author)
journal article 2023
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Ding, Chuanwei (author), Zhang, Li (author), Chen, Haoyu (author), Hong, Hong (author), Zhu, Xiaohua (author), Fioranelli, F. (author)
Radar-based solutions have attracted great attention in human activity recognition (HAR) for their advantages in accuracy, robustness, and privacy protection. The conventional approaches transform radar signals into feature maps and then directly process them as visual images. While effective, these image-based methods may not be the best...
journal article 2023
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Fioranelli, F. (author), Guendel, Ronny (author), Kruse, N.C. (author), Yarovoy, Alexander (author)
Driven by its contactless sensing capabilities and the lack of optical images being recorded, radar technology has been recently investigated in the context of human healthcare. This includes a broad range of applications, such as human activity classification, fall detection, gait and mobility analysis, and monitoring of vital signs such as...
conference paper 2023
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Yuan, S. (author), Fioranelli, F. (author), Yarovoy, Alexander (author)
The ambiguity problem in forward-looking Doppler beam sharpening is considered. Doppler beam sharpening (DBS) has shown its potential to improve cross-range resolution for automotive radar applications. However, it suffers from ambiguities when targets are positioned symmetrically with respect to the vehicle trajectory. A new approach named ...
conference paper 2023
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Bouwmeester, W. (author), Fioranelli, F. (author), Yarovoy, Alexander (author)
A method for extracting fully polarimetric statistical properties of road surface radar cross sections is presented. This method is subsequently applied to extract radar cross section information from an asphalt road surface. Furthermore, an approach is introduced to synthesise the scattered signal of road surface returns as measured by a radar....
conference paper 2023
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Guendel, Ronny (author), Ullmann, I. (author), Fioranelli, F. (author), Yarovoy, Alexander (author)
Radar-based human activity recognition in crowded environments using regression approaches is addressed. Whereas previous research has focused on single activities and subjects, the problem of continuous activity recognition involving up to five individuals moving in arbitrary directions in an indoor area is introduced. To treat the problem, a...
conference paper 2023
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Bouwmeester, W. (author), Fioranelli, F. (author), Yarovoy, Alexander (author)
The convergence of polarimetric scattering parameters and H, α and A features of road surfaces under various conditions is analysed. It is shown that the number of radar measurements used for surface classification can be traded off with accuracy of the estimation of the mean value and covariance of S-parameters and H, α and A features....
conference paper 2023
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Zhu, S. (author), Fioranelli, F. (author), Yarovoy, Alexander (author)
The problem of 2D instantaneous ego-motion estimation for vehicles equipped with automotive radars is studied. To leverage multi-dimensional radar point clouds and exploit point features automatically, without human engineering, a novel approach is proposed that transforms ego-motion estimation into a weighted least squares (wLSQ) problem using...
conference paper 2023
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Kruse, N.C. (author), Fioranelli, F. (author), Yarovoy, Alexander (author)
Due to numerous benefits, radar is considered as an important sensor for human activity classification. The problem of classifying continuous sequences of activities of unconstrained duration has been studied in this work. To tackle this challenge, a radar data processing method utilizing point transformer networks has been proposed. The method...
conference paper 2023
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Yuan, S. (author), Fioranelli, F. (author), Yarovoy, Alexander (author)
The problem of high-resolution direction-of-arrival (DOA) estimation based on a limited amount of snapshots in automotive multiple-input multiple-output (MIMO) radar has been studied. The number of snapshots is restricted to minimize target spread/migration in range and/or Doppler domains. A computationally efficient approach for side-looking...
journal article 2023
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Assabumrungrat, Rawin (author), Kumchaiseemak, N. (author), Wang, J. (author), Wang, D. (author), Punpeng, Phoom (author), Fioranelli, F. (author), Wilaiprasitporn, Theerawit (author)
We present a deep learning-based approach called DipSAR for reconstructing millimeter-wave synthetic aperture radar (SAR) images from sparse samples. The primary challenge lies in the requirement of a large training dataset for deep learning schemes. To overcome this issue, we employ the deep image prior (DIP) technique, which eliminates the...
conference paper 2023
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Roldan Montero, I. (author), Fioranelli, F. (author), Yarovoy, Alexander (author)
A novel framework to enhance the angular resolution of automotive radars is proposed. An approach to enlarge the antenna aperture using artificial neural networks is developed using a self-supervised learning scheme. Data from a high angular resolution radar, i.e., a radar with a large antenna aperture, is used to train a deep neural network...
journal article 2023
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Corradi, Federico (author), Fioranelli, F. (author)
The advent of consumer and industrial Unmanned Aerial Vehicles (UAVs), commonly referred to as drones, has opened business opportunities in many fields, including logistics, smart agriculture, inspection, surveillance, and construction. In addition, the autonomous operations of UAVs reduce risks by minimizing the time spent by human workers...
conference paper 2022
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Zhu, S. (author), Guendel, Ronny (author), Yarovoy, Alexander (author), Fioranelli, F. (author)
Unconstrained human activities recognition with a radar network is considered. A hybrid classifier combining both convolutional neural networks (CNNs) and recurrent neural networks (RNNs) for spatial–temporal pattern extraction is proposed. The 2-D CNNs (2D-CNNs) are first applied to the radar data to perform spatial feature extraction on the...
journal article 2022
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Guendel, Ronny (author), Fioranelli, F. (author), Yarovoy, Alexander (author)
Continuous Human Activity Recognition (HAR) in arbitrary directions is investigated in this paper using a network of five spatially distributed pulsed Ultra-Wideband radars. While activities performed continuously and in unconstrained trajectories provide a more realistic and natural scenario for HAR, the network of radar sensors is proposed...
journal article 2022
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Guendel, Ronny (author), Fioranelli, F. (author), Yarovoy, Alexander (author)
Continuous Human Activity Recognition (HAR) in arbitrary directions is investigated using 5 spatially distributed pulsed Ultra-Wideband (UWB) radars. Such activities performed in arbitrary and unconstrained trajectories render a more natural occurrence of Activities of Daily Living (ADL) to be recognized. An innovative signal level fusion method...
conference paper 2022
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Svenningsson, P.O. (author), Kruse, N.C. (author), Fioranelli, F. (author), Yarovoy, Alexander (author)
Cognitive radar frameworks rely on the ability to quantify and reason on future uncertainty, which allows for the selection of an optimal decision policy. These methods require that the uncertainty estimates provided by the underlying statistical model are well-calibrated, i.e. consistent with true uncertainty. In this work, the utilization of...
conference paper 2022
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Roldan Montero, I. (author), Fioranelli, F. (author), Yarovoy, Alexander (author)
Poor angular resolution is one of the main disadvantages of automotive radars, and the reason why lidar technology is widely used in the automotive industry. For a fixed frequency, the angular resolution of a conventional Multiple-Input Multiple-Output (MIMO) radar is limited by the number of physical antennas, and therefore improve the...
conference paper 2022
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Yuan, S. (author), Fioranelli, F. (author), Yarovoy, Alexander (author)
A method exploiting the movement of the vehicle to boost the cross-range resolution of automotive radar by forming a larger virtual array is proposed. Initial simulated results show that the proposed method with the traditional Digital beamforming (DBF) algorithm can separate targets that cannot be otherwise recognized by the traditional MIMO...
conference paper 2022
Searched for: author%3A%22Fioranelli%2C+F.%22
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