986 research outputs found
Target Classification through ISAR for Autonomous Vehicles based on Federated Learning
No full textThis study explores the use of Federated Learning (FL) in classifying ISAR images for autonomous driving. Automotive radar systems, operating at millimeter-wave frequencies, offer critical safety features. ISAR images are powerful for target recognition but pose challenges in real-world scenarios. FL, a decentralized training approach, is employed for data privacy while maintaining competitive accuracy. Our findings reveal that FL achieves commendable performance compared to centralized models, ensuring data confidentiality by keeping the information on local devices and centrally sharing only the model weights. In conclusion, this research demonstrates FL's potential in improving ISAR-based target classification for autonomous driving, making it suitable for privacy-sensitive applications
Developments in target micro-doppler signatures analysis: radar imaging, ultrasound and through-the-wall radar
No full textTarget motions, other than the main bulk translation of the target, induce Doppler modulations around the main Doppler shift that form what is commonly called a target micro-Doppler signature. Radar micro-Doppler signatures are generally both target and action speci c and hence can be used to classify and recognise targets as well as to identify possible threats. In recent years, research into the use of micro-Doppler signatures for target classi cation to address many defence and security challenges has been of increasing interest. In this paper, we present a review of the work published in the last 10 years on emerging applications of radar target analysis using micro-Doppler signatures. Speci cally we review micro-Doppler target signatures in bistatic SAR and ISAR, through-the-wall radar and ultrasound radar. This article has been compiled to provide radar practitioners with a unique reference source covering the latest developments in micro-Doppler analysis, extraction and mitigation techniques. The paper shows that this research area is highly active and fast moving and demonstrates that micro-Doppler techniques can provide important solutions to many radar target classification challenges
Multilook polarimetric 3-D interferometric ISAR imaging
No full textThis article introduces polarimetric 3-D interferometric inverse synthetic aperture radar (ISAR) imaging process using multiple phase centers via a spatio-sensor multilook algorithm. This approach enables one to take effective advantage of polarimetric scattering mechanisms in 3-D target representations, which may improve target classification and identification. In addition, the multilook algorithm enhances the accuracy of height estimation in noisy conditions. The 3-D interferometric ISAR (InISAR) imaging process is validated using the backhoe synthetic data released by the Air Force Research Laboratory.</p
International severe asthma registry (ISAR): Protocol for a global registry
No full textBackground: Severe asthma exerts a disproportionately heavy burden on patients and health care. Due to the heterogeneity of the severe asthma population, many patients need to be evaluated to understand the clinical features and outcomes of severe asthma in order to facilitate personalised and targeted care. The International Severe Asthma Registry (ISAR) is a multi-country registry project initiated to aid in this endeavour. Methods: ISAR is a multi-disciplinary initiative benefitting from the combined experience of the ISAR Steering Committee (ISC; comprising 47 clinicians and researchers across 29 countries, who have a special interest and/or experience in severe asthma management or establishment and maintenance of severe asthma registries) in collaboration with scientists and experts in database management and communication. Patients (=18 years old) receiving treatment according to the 2018 definitions of the Global Initiative for Asthma (GINA) Step 5 or uncontrolled on GINA Step 4 treatment will be included. Data will be collected on a core set of 95 variables identified using the Delphi method. Participating registries will agree to provide access to and share standardised anonymous patient-level data with ISAR. ISAR is a registered data source on the European Network of Centres for Pharmacoepidemiology and Pharmacovigilance. ISAR's collaborators include Optimum Patient Care, the Respiratory Effectiveness Group (REG) and AstraZeneca. ISAR is overseen by the ISC, REG, the Anonymised Data Ethics and Protocol Transparency Committee and the ISAR operational committee, ensuring the conduct of ethical, clinically relevant research that brings value to all key stakeholders. Conclusions: ISAR aims to offer a rich source of real-life data for scientific research to understand and improve disease burden, treatment patterns and patient outcomes in severe asthma. Furthermore, the registry will provide an international platform for research collaboration in respiratory medicine, with the overarching aim of improving primary and secondary care of adults with severe asthma globally. © 2020 The Author(s)
Simulation and Analysis of 3-D Polarimetric Interferometric ISAR Imaging
No full textThis paper introduces a polarimetric three-dimensional (3-D) interferometric inverse synthetic aperture radar (ISAR) imaging process using multiple phase-centers. This approach takes effective advantage of polarimetric scattering mechanisms in 3-D target representations, which may improve target classification and identification. A Pauli decomposition scheme is considered to study the role of polarimetry in 3-D Interferometric ISAR (InISAR). The polarimetric 3-D InISAR imaging process is validated using the backhoe synthetic data released by the Air Force Research Laboratory (AFRL).</p
ISAR motion compensation based on a new Doppler parameters estimation procedure
No full textThe work addresses the problem of compensating the distor- tion effects induced by the translational motion of moving targets in Inverse Synthetic Aperture Radar (ISAR) imaging systems. The ISAR motion compensation is the most crucial step in the Autofocusing ISAR technique; this task is typi- cally solved by implementing exhaustive search algorithms by adopting proper functionals based f.i. on image entropy or contrast. In this work, we discuss an innovative and fast mo- tion compensation procedure that is based on the estimation of two Doppler key Parameters: the Doppler Centroid and the Doppler Rate, which are related to the target motion pa- rameters. The effectiveness of the proposed method is tested on real data acquired by a static Frequency Modulated Con- tinuous Wave radar with an azimuth wide beamwidth; the radar is installed near the inner harbor of La Spezia (Italy) and it owned to the Centre for Maritime Research and Exper- imentation of the North Atlantic Treaty Organization (NATO- CMRE)
Target Motion Estimation and Imaging with a Multistatic ISAR System
No full textIn this article we present the realization of an experimental multistatic inverse synthetic aperture radar (M-ISAR) system. The primary focus of this work is to utilize the multistatic geometry to estimate the motion of a maneuvering ground target. We propose solutions to all experimental challenges that go along with such a setup, including hardware development, synchronization, and signal processing. Results from real data show that images of reasonable quality can be obtained without making strong assumptions on the target trajectory. On the basis of these results, benefits and drawbacks of the multilateration approach to motion estimation are discussed, critical elements of the processing chain are highlighted, and phenomenological experience is shared.</p
Array passive ISAR adaptive processing (APIS) project: an overview
No full textThis paper presents a recently built passive radar demonstrator, called the Array Passive ISAR adaptive processing (APIS).. This work has been supported by the European Defence Agency (EDA) in the framework of the Defence R&T Joint Investment Programme on Innovative Concepts and Emerging Technologies (JIP-ICET). The system is able to detect targets and generate ISAR (Inverse Synthetic Aperture Radar) images for classification purposes, by exploiting DVB-T transmitters. The basic system concept and the results are presented in this paper
A Fully Automatic Autofocusing Algorithm for Post-processing ISAR Imaging based on Image Entropy Minimization
No full textAutofocus is a technique for improving inverse synthetic aperture radar (ISAR) imaging. In this paper, a novel autofocusing method is developed for high-resolution stepped-frequency ISAR. Non-uniform rotational motion is compensated through the proposed post-processing methodology. In this way, the computational cost of polar reformatting process can be circumvented. The proposed CPI-split autofocusing process results in well-focused ISAR images for high angular acceleration periods. Finally, ISAR image entropy dependencies are thoroughly examined through various simulation results, leading to an acceptable range of entropy values for the autofocusing process. Ill. 7, bibl. 9, tabl. 3 (in English; abstracts in English and Lithuanian).http://dx.doi.org/10.5755/j01.eee.110.4.305</jats:p
International severe asthma registry (ISAR): protocol for a global registry
No full textBackground: Severe asthma exerts a disproportionately heavy burden on patients and health care. Due to the heterogeneity of the severe asthma population, many patients need to be evaluated to understand the clinical features and outcomes of severe asthma in order to facilitate personalised and targeted care. The International Severe Asthma Registry (ISAR) is a multi-country registry project initiated to aid in this endeavour.
Methods: ISAR is a multi-disciplinary initiative benefitting from the combined experience of the ISAR Steering Committee (ISC; comprising 47 clinicians and researchers across 29 countries, who have a special interest and/or experience in severe asthma management or establishment and maintenance of severe asthma registries) in collaboration with scientists and experts in database management and communication. Patients (≥18 years old) receiving treatment according to the 2018 definitions of the Global Initiative for Asthma (GINA) Step 5 or uncontrolled on GINA Step 4 treatment will be included. Data will be collected on a core set of 95 variables identified using the Delphi method. Participating registries will agree to provide access to and share standardised anonymous patient-level data with ISAR. ISAR is a registered data source on the European Network of Centres for Pharmacoepidemiology and Pharmacovigilance. ISAR's collaborators include Optimum Patient Care, the Respiratory Effectiveness Group (REG) and AstraZeneca. ISAR is overseen by the ISC, REG, the Anonymised Data Ethics & Protocol Transparency Committee and the ISAR operational committee, ensuring the conduct of ethical, clinically relevant research that brings value to all key stakeholders.
Conclusions: ISAR aims to offer a rich source of real-life data for scientific research to understand and improve disease burden, treatment patterns and patient outcomes in severe asthma. Furthermore, the registry will provide an international platform for research collaboration in respiratory medicine, with the overarching aim of improving primary and secondary care of adults with severe asthma globally.</p
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