Searched for: author%3A%22Fioranelli%2C+F.%22
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Ahmad, Bashar I. (author), Rogers, Colin (author), Harman, Stephen (author), Dale, Holly (author), Jahangir, Mohammed (author), Antoniou, Michael (author), Baker, Chris (author), Newman, Mike (author), Fioranelli, F. (author)
Automatic target classification or recognition is a critical capability in noncooperative surveillance with radar in several defence and civilian applications. It is a well-established research field and numerous techniques exist for recognizing targets, including miniature unmanned air systems or drones (i.e., small, mini, micro, and nano...
journal article 2024
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Vishwakarma, Shelly (author), Chetty, Kevin (author), Le Kernec, Julien (author), Chen, Qingchao (author), Adve, Raviraj (author), Gurbuz, Sevgi Zubeyde (author), Li, Wenda (author), Ram, Shobha Sundar (author), Fioranelli, F. (author)
contribution to periodical 2024
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Bouwmeester, W. (author), Fioranelli, F. (author), Yarovoy, Alexander (author)
Incoherent backscattering of mm-waves from natural rough surfaces is considered. A novel method is proposed to determine the statistical properties of surface scattering from range profile measurements. The method is based on modeling the road surface as a grid of uncorrelated scattering elements, described by normalized scattering matrices....
journal article 2024
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Guendel, R.G. (author), Kruse, N.C. (author), Fioranelli, F. (author), Yarovoy, Alexander (author)
In this study, the problem of multipath in radar sensor networks for human activity recognition (HAR) has been examined. Traditionally considered as a source of additional clutter, the multipath is being investigated for its potential to be exploited through the creation of virtual radar nodes. These virtual nodes are conceptualized to...
journal article 2024
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Aubry, Augusto (author), Carotenuto, Vincenzo (author), Maio, Antonio De (author), Fioranelli, F. (author)
The design of bespoke adaptive detection schemes relying on the joint use of multistatic/polarimetric measurements requires a preliminary statistical inference on the clutter interference environment. This is of paramount importance to develop an analytic model for the received signal samples, which is mandatory for the synthesis of radar...
journal article 2024
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Aubry, Augusto (author), Carotenuto, Vincenzo (author), De Maio, Antonio (author), Fioranelli, F. (author)
This article deals with the statistical inference of simultaneously recorded co- and cross-polarized bistatic coherent sea-clutter returns at S-band. This study is conducted employing appropriate statistical learning tools, involving the complex envelope of data, to assess the compliance of the available measurements with the spherically...
journal article 2023
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Ullmann, Ingrid (author), Guendel, Ronny (author), Kruse, N.C. (author), Fioranelli, F. (author), Yarovoy, Alexander (author)
Radar-based human motion and activity recognition is currently a topic of great research interest, as the aging population increases and older individuals prefer an independent lifestyle. This technology has a wide range of applications, such as fall detection in assisted living, gesture recognition for human-machine interfaces, and many more....
journal article 2023
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Zhu, S. (author), Yarovoy, Alexander (author), Fioranelli, F. (author)
The problem of instantaneous ego-motion estimation with mm-wave automotive radar is studied. DeepEgo, a deep learning-based method, is proposed for achieving robust and accurate ego-motion estimation. A hybrid approach that uses neural networks to extract complex features from input point clouds and applies weighted least squares (WLS) for...
journal article 2023
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Bouwmeester, W. (author), Fioranelli, F. (author), Yarovoy, Alexander (author)
A novel approach based on the entropy-alpha-anisotropy decomposition, also known as the $H\alpha A$ decomposition, for the recognition of road surface conditions using automotive radar is presented. To apply the $H\alpha A$ decomposition to automotive radar data, a dedicated signal processing pipeline has been developed. To investigate its...
journal article 2023
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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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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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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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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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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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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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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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Carotenuto, V. (author), Aubry, A. (author), De Maio, A. (author), Fioranelli, F. (author)
The design of bespoke adaptive detection schemes relying on the joint use of multistatic/polarimetric measurements requires a preliminary statistical inference on the clutter interference environment. This is fundamental to develop an analytic model for the received signal samples, which is used to synthesize the radar detector. In this...
conference paper 2023
document
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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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
Searched for: author%3A%22Fioranelli%2C+F.%22
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