Browsing by Author "Fioranelli, Francesco"

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    Estimation of drone intention using trajectory frequency defined in radar's measurement phase planes
    (Institution of Engineering and Technology (IET), 2023-06-13) Yun, Joongsup; Anderson, David; Fioranelli, Francesco
    This paper presents a radar-based algorithm for autonomous estimation of drone intention. The algorithm is based on radar's kinematic measurements, providing fast and robust intention estimation for multiple targets. The core idea of the proposed algorithm is to build intention-specific features for each intention in advance and use them in actual drone surveillance situations. To effectively depict the trajectory characteristics of various intentions, the trajectory frequency is computed on multiple phase planes through Monte Carlo Simulations. Finally, a naive Bayes classifier is applied to integrate the trajectory likelihood in different phases and ultimately compute the intention likelihood of all intentions concerned. Numerical simulations for the three candidate intentions of image acquisition, smuggling, and kamikaze attack demonstrated the performance of the presented method. The simulation results show that one can estimate the true intention of a specific drone by comparing the value of each intention likelihood.
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    Experimental analysis of multistatic multiband radar signatures of wind turbines
    (Institution of Engineering and Technology (IET), 2016-05-23) Balleri, Alessio; Fioranelli, Francesco; Ritchie, Matthew; Griffiths, Hugh D.
    This study presents the analysis of recent experimental data acquired using two radar systems at S-band and X-band to measure simultaneous monostatic and bistatic signatures of operational wind turbines near Shrivenham, UK. Bistatic and multistatic radars are a potential approach to mitigate the adverse effects of wind farm clutter on the performance of radar systems, which is a well-known problem for air traffic control and air defence radar. This analysis compares the simultaneous monostatic and bistatic micro-Doppler signatures of two operational turbines and investigates the key differences at bistatic angles up to 23°. The variations of the signature with different polarisations, namely vertical transmitted and vertical received and horizontal transmitted and horizontal received, are also discussed.
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    Experimental analysis of multistatic wind turbine radar clutter statistics
    (Institution of Engineering and Technology (IET), 2023-02-01) Fioranelli, Francesco; Ritchie, Matthew; Balleri, Alessio; Griffiths, Hugh D.
    This Letter presents preliminary results of the analysis of amplitude statistics of wind turbine clutter as extracted from multistatic radar data. It is shown that the T-location-scale distribution provides good fitting of the experimental data, and that there are combinations of bistatic angle and polarisations where the bistatic clutter has more favourable statistics for target detection than the simultaneous monostatic clutter.
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    Practical investigation of multiband mono- and bistatic radar signatures of wind turbines
    (Institution of Engineering and Technology (IET), 2017-03-17) Fioranelli, Francesco; Ritchie, Matthew; Balleri, Alessio; Griffiths, Hugh D.
    The negative effects wind farm clutter has on the performance of radar systems for Air Traffic Control and Air Surveillance is well-known in the radar research community and several mitigation techniques have been proposed to address this problem. These include bistatic and multistatic radar systems providing multiple views of the area under surveillance, and hence potential additional information that can be used to improve the receiver performance. This paper presents the analysis of a set of experimental data collected simultaneously by two radar systems, one operating at S-band and one at X-band, of echoes from an operational wind farm in the UK near Oxford. This analysis presents several parameters extracted from the time domain data and the Doppler spectra, such as Doppler centroid and bandwidth of the micro-Doppler signature as well as amplitude statistics of the time domain returns. These parameters are characterised using data recorded at monostatic and bistatic nodes, as well as at different polarisation combinations.