Browsing by Author "Carotenuto, Vincenzo"

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    Performance prediction of the coherent radar detector on measured UAVs data
    (Institution of Engineering and Technology (IET), 2022-10-27) Rosamilia, Massimo; Aubry, Augusto; Balleri, Alessio; Carotenuto, Vincenzo; De Maio, Antonio
    This paper presents measurements of Radar Cross Section (RCS) of five Unmanned Aerial Vehicles (UAVs), comprising both consumer grade and professional small drones, collected in a semi-controlled environment as a function of azimuth aspect angle, polarization and frequency in the range 8.2-18 GHz. A first-order statistical analysis of the measured RCSs is firstly reported prior to assessing the radar detection performance on both measured and bespoke simulated data (leveraging the results of the developed statistical analysis), including, as benchmark terms, the curves for non-fluctuating and Rayleigh fluctuating targets.
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    Radar detection performance prediction using measured UAVs RCS data
    (IEEE, 2022-12-12) Rosamilia, Massimo; Balleri, Alessio; De Maio, Antonio; Aubry, Augusto; Carotenuto, Vincenzo
    This paper presents measurements of Radar Cross Section (RCS) of five Unmanned Aerial Vehicles (UAVs), comprising both consumer grade and professional small drones, collected in a semi-controlled environment as a function of azimuth aspect angle, polarization and frequency in the range 8.2-18 GHz. The experimental setup and the data pre-processing, which include coherent background subtraction and range gating procedures, are illustrated in detail. Furthermore, a thorough description of the calibration process, which is based on the substitution method, is discussed. Then, a first-order statistical analysis of the measured RCSs is provided by means of the Cramér-von Mises (CVM) distance and the Kolmogorov-Smirnov (KS) test. Finally, radar detection performance is assessed on both measured and bespoke simulated data (leveraging the results of the developed statistical analysis), including, as benchmark terms, the curves for non-fluctuating and Rayleigh fluctuating targets.
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    Radar detection performance via frequency agility using measured UAVs RCS data
    (IEEE, 2023-08-22) Rosamilia, Massimo; Aubry, Augusto; Balleri, Alessio; Carotenuto, Vincenzo; De Maio, Antonio
    This paper addresses radar detection performance prediction (via measured data) for drone targets using a frequency agility-based incoherent (square-law) detector. To this end, a preliminary statistical analysis of the integrated Radar Cross Section (RCS) resulting from frequency agile pulses is carried out for drones of different sizes and characteristics, using data acquired in a semi-controlled environment for distinct frequencies, angles, and polarizations. The analysis involves fitting the integrated RCS measurements with commonly used one-parametric and two-parametric probability distributions and leverages the Cramér-von Mises distance and the Kolmogorov Smirnov test. Results show that the Gamma distribution appears to accurately model the resulting fluctuations. Hence, the impact of integration and frequency agility on the RCS fluctuation dispersion is studied. Finally, detection performance of the incoherent square-law detector is assessed for different target and radar parameters, using both measured and simulated data drawn from a Gamma distribution whose parameters follow the preliminary RCS statistical analysis. The results highlight a good agreement between simulated and measurement-based curves.
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    RCS measurements of UAVs and their statistical analysis
    (IEEE, 2022-06-29) Rosamilia, Massimo; Aubry, Augusto; Balleri, Alessio; Carotenuto, Vincenzo; De Maio, Antonio
    This paper deals with Radar Cross Section (RCS) measurements of five small Unmanned Aerial Vehicles (UAVs) in a semi-controlled environment as a function of azimuth aspect angle, polarization, and frequency in the range 8.2-18 GHz. The experimental setup and the data pre-processing, which include coherent background subtraction, range gating procedures, and calibration, are presented. Then, a thorough statistical analysis of the measured RCSs is provided by means of the Cram´er–von Mises (CVM) distance and the Kolmogorov–Smirnov (KS) test.