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F. Fioranelli

129 records found

Monitoring gait symmetry reliably is crucial, as it is an early indicator of Parkinson's disease (PD). In this work, a method is presented to analyze gait asymmetries using a 24-GHz frequency-modulated continuous-wave (FMCW) multiple-input-multiple-output (MIMO) radar in a noncli ...
Traditional target tracking using monostatic radar systems typically rely on centralized or decentralized architectures, where all data is transmitted to a fusion center for estimating the position and velocity of mobile agents. This approach introduces a single point of failure ...
This article presents the first subject-specific head pose estimation approach using only one frequency-modulated continuous wave radar data frame. Specifically, the proposed method incorporates a deep learning framework to estimate head pose rotation and orientation frame-by-fra ...
The role of radar for building situation awareness in (semi)autonomous vehicles is severely restricted by its low angular resolution. The physical size of the radar, which determines its antenna aperture size and thus the radar angular resolution, is often a subject of stringent ...
In this article, the classification of dynamic vulnerable road users (VRUs) using polarimetric automotive radar is considered. To this end, a signal processing pipeline for polarimetric automotive MIMO radar is proposed, including a method to enhance angular resolution by comb ...
This paper presents an approach based on Doppler beam sharpening (DBS) to enhance the resolution of multiple ‘dynamic’ targets in automotive driving scenarios. The ambiguity inherent to the forward-looking DBS and the coupling between azimuth and elevation angles are jointly addr ...
The application of distributed radar to human motion monitoring is considered. A novel sensor fusion method has been proposed that yields a two-dimensional map of reflection intensity and a vector field of reconstructed velocities in lieu of conventional Doppler spectrograms or r ...
A new modification to a method to determine the normalised radar cross section of road surfaces is proposed, so that the radar cross section of anisotropic pavement materials can also be considered. This method is applied to two types of brick pavements with different bond patter ...
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 s ...
The problem of detection and localization of multiple people using a network of Ultra-Wide Band (UWB) radar nodes in the cabin of a vehicle is addressed in this paper. Specifically, an algorithm for decentralized vital signs detection is proposed, based on the analysis of a novel ...
In this paper the problem of tracking multiple people in an indoor environment is formulated and analyzed with the usage of a Multiple Input Multiple Output (MIMO) Frequency Modulated Continuous Wave (FMCW) radar. The objective is to evaluate the performance of FMCW MIMO radar wi ...
The effect of different time-frequency (TF) resolution values is analyzed in the context of Human Activity Recognition (HAR) using multiple radars distributed in a network. Specifically, different spectrograms computed with various Short-Time Fourier Transform (STFT) window lengt ...
A feasibility study to detect the respiratory rate and heart rate of primates using non-invasive contactless radar sensors and a dedicated processing pipeline is performed. The proposed approach is validated using measurement data from an individual bonobo, simultaneously collect ...
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 virtu ...
In this paper, an algorithm to generate a sparse linear antenna array for Direction of Arrival (DoA) estimation that works well in combination with Bayesian Compressive Sensing (BCS) is proposed. The proposed algorithms rely on the provided information inherent to BCS, i.e., the ...
This paper examines how training data affects machine learning-assisted antenna pattern prediction under mutual coupling. For demonstration, a neural network-based approach is used to predict the embedded pattern of a central patch antenna element near randomly distributed patche ...
A neural network (NN) based multi-frame classification approach is proposed to solve the problem of classification of tracked objects. Initially, a baseline tracker is implemented that uses the classification output of an object detection network for classification. Afterwards, t ...
A novel ensemble prediction technique is introduced to enhance the accuracy of far-field embedded element pattern (EEP) prediction under mutual coupling (MC) effects, while relaxing the training data size challenge in neural network (NN)-based algorithms. The proposed method inte ...

See Further Than CFAR

A Data-Driven Radar Detector Trained by Lidar

In this paper, we address the limitations of traditional constant false alarm rate (CFAR) target detectors in automotive radars, particularly in complex urban environments with multiple objects that appear as extended targets. We propose a data-driven radar target detector exploi ...