Numerical Simulation and Experimental Analysis of Small Drone Rotor Blade Polarimetry Based on RCS and Micro-Doppler Signature

Li, Tengmingyang; Wen, Biyang; Tian, Yingwei; Li, Ziyan; Wang, Sijie

doi:10.1109/lawp.2018.2885373

Cited by 38 publications

(14 citation statements)

References 14 publications

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“…6(b), these peaks are under-sampled when T r = 5 ms. The rotating speed f rot can be retrieved by the non-aliasing sampling of the first pair of Doppler peaks in RD spectrum [15]. But in practice, in order to counter the wind and maintain a stable posture, it is impossible for m-UAVs to maintain a steady rotating speed for a long time.…”

Section: Spectral Spread In Doppler Dimensionmentioning

confidence: 99%

“…Previous studies on the electromagnetic scattering of m-UAVs were mainly focused on S band and above, and numerical simulation and measurement are two common methods [8]- [14]. In addition, it is feasible to monitor m-UAVs using VHF/UHV band under horizontal-horizontal polarization [15]. Therefore, the optimized radar waveform parameters design for drone detection based on m-UAVs echo modeling in VHF band is significant.…”

Section: Introductionmentioning

confidence: 99%

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Optimized Radar Waveform Parameter Design for Small Drone Detection Based on Echo Modeling and Experimental Analysis

Wen

Tian

et al. 2019

IEEE Access

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Monitoring small drones is significant for security requirements, but it is challenging because of small drones' low radar cross section (RCS) and hovering ability. In order to analyze the effect of radar waveform on the echo spectra and optimize the waveform design, an analytical expression of the rotor's temporal RCS is desired. Integral model, a widely used radar echo model of the rotor's temporal RCS, does not involve the electromagnetic scattering, thus it cannot be applied to all frequency bands. The method of moments (MoM) is a strictly numerical method based on the Maxwell's equations, but cannot obtain the analytical expression. Hence, this paper proposes a new method combing the integral model and MoM to model the rotor's temporal RCS in very high frequency (VHF) band. The linear frequency modulation (LFM) signal which has a high Doppler tolerance and a large gain bandwidth product is adopted in optimizing waveform parameters design. Based on the new method, the analytical expression of LFM echo is also derived. Moreover, the spectral spread over range and Doppler dimension caused by the rotating rotors is analyzed in detail. A criterion for optimizing the LFM waveform parameters for small drone detection is presented. Field experiments confirm the validity of the echo model and waveform parameters optimization criterion, and the full Acrylonitrile Butadiene Styrene small drone is successfully detected in VHF band. In addition, experiments are implemented to verify the applicability of the echo model and waveform parameters optimization method to other drones with different size.INDEX TERMS Small drone detection, electromagnetic scattering, method of moments (MoM), numerical simulation, linear frequency modulation (LFM) signal.

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Section: Spectral Spread In Doppler Dimensionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Optimized Radar Waveform Parameter Design for Small Drone Detection Based on Echo Modeling and Experimental Analysis

Wen

Tian

et al. 2019

IEEE Access

Self Cite

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“…Despite the ex-istence of many such studies, the RCS level-based method still has difficulties in distinguishing drones from airborne organisms [2]. To solve this problem, methods based on the signature extracted from the RCS of a target rather than the simple RCS level have been studied [3][4][5][6][7][8][9][10][11][12][13]. Inverse synthetic aperture radar (ISAR) images of small drones were investigated in [4].…”

Section: Introductionmentioning

confidence: 99%

Dynamic RCS Estimation according to Drone Movement Using the MoM and Far-Field Approximation

Lee

Seo

2021

J Electromagn Eng Sci

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Micro-Doppler signatures from the rotating propellers of a drone can be utilized to distinguish the drone from clutter or airborne organisms with similar radar cross section (RCS) levels, such as birds and bats. To obtain the micro-Doppler signatures of a drone, calculation or measurement of the electric field scattered from the rotating propellers is essential. In this paper, using the relative angle concept and far-field approximation, we propose a way to rapidly estimate the dynamic RCS of a drone with several propellers according to its movement. In addition, based on the fact that the shape of the propeller does not change even if it rotates, we construct an impedance matrix only once and apply the matrix to the method of moments instead of the iterative process of calculating the impedance matrix and inverse matrix for each rotation angle of the propeller. Finally, by using the Fourier transform of the results from the proposed method, the rotation frequencies of the propellers according to the movement of the drone can be obtained.

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“…The ability to model and predict the electromagnetically (EM) induced currents coupled to UAV frames and wires, which propagate to their sense and/or control components, as it is in other modern electronic equipment, is a grand challenge to fully mitigate. To attack the full problem, there are too many input and state variables to treat computationally, especially when using brute force full-wave simulations [10], [11].…”

Section: Introductionmentioning

confidence: 99%

Prediction of Experimental Electromagnetic Coupling to a UAV Model Using Characteristic Mode Analysis

Hamdalla¹,

Bissen²,

Hunter³

et al. 2021

Preprint

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<p>In this work, we study the current coupled to a simplified Unmanned Aerial Vehicle (UAV) model using a dual computational and experimental approach. The surrogate structure reduced the computational burden and facilitated the experimental measurement of the coupled currents. For a practical system, a wide range of simulations and measurements must be performed to analyze the induced current variations with respect to the incident excitation properties such as the frequency, angle of incidence, and polarization. To simplify this analysis, Characteristic Mode Analysis (CMA) was used to compute the eigen-currents of the UAV model and predict where and under which RF excitation conditions, the coupled current is maximized. We verified these predictions using direct experimental measurement of the coupled currents. The presented simulations and measurements show the usefulness of CMA for studying electromagnetic coupling to practical systems. </p>

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Numerical Simulation and Experimental Analysis of Small Drone Rotor Blade Polarimetry Based on RCS and Micro-Doppler Signature

Cited by 38 publications

References 14 publications

Optimized Radar Waveform Parameter Design for Small Drone Detection Based on Echo Modeling and Experimental Analysis

Optimized Radar Waveform Parameter Design for Small Drone Detection Based on Echo Modeling and Experimental Analysis

Dynamic RCS Estimation according to Drone Movement Using the MoM and Far-Field Approximation

Prediction of Experimental Electromagnetic Coupling to a UAV Model Using Characteristic Mode Analysis

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