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F. Fioranelli

127 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 ...
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 ...

Speeding up imaging over BP for automotive radar

High-resolution algorithm with multi-frame data

One of the key problems in automotive radar is its limited cross-range resolution, despite many approaches developed to address this. Conventional high-resolution algorithms in synthetic aperture radar (SAR) can provide good resolution imaging ability but suffer from high computa ...
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 ...

A Review of Automatic Classification of Drones Using Radar

Key Considerations, Performance Evaluation and Prospects

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 unman ...
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 ...
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 ...
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 ...
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 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 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 ...

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 ...
In this paper, the problem of formulating effective processing pipelines for indoor human tracking is investigated, with the usage of a Multiple Input Multiple Output (MIMO) Frequency Modulated Continuous Wave (FMCW) radar. Specifically, two processing pipelines starting with det ...
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 ...
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 ...
This paper focuses on the challenge of estimating the 2D instantaneous ego -motion of vehicles equipped with an automotive radar. To further improve our previous study based on the weighted least squares (wLSQ) method and purpose-designed neural networks (NNs), this work proposes ...
The problem of 3D ego-motion velocity estimation using multichannel Frequency Modulated Continuous Wave (FM CW) radar sensors has been studied. Special attention is given to presence of moving targets in the scene. These targets are first distinguished by the difference between t ...
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 sc ...