Numerical RCS and micro-Doppler investigations of a consumer UAV

Schröder, Arne; Aulenbacher, Uwe; Renker, Matthias; Böniger, Urs; Oechslin, R.; Murk, Axel; Wellig, Peter

doi:10.1117/12.2241298

Cited by 7 publications

(9 citation statements)

References 6 publications

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“…These numerical methods include the Method of Moments (MoM), which approximates surface currents, and the Finite Element Method (FEM), which approximates volumetric currents, both of which are relevant at lower frequencies (in the Rayleigh and resonant scatter regimes). Schröder et al developed a full-body micro-Doppler simulation of a DJI Phantom 2 using MoM at 10 GHz [16]. Speirs et al used MoM and FEM to generate spectrograms of a DJI Phantom 2 at X-band [17].…”

Section: Micro-doppler For Drone Classificationmentioning

confidence: 99%

A new simulation methodology for generating accurate drone micro‐Doppler with experimental validation

Moore,

Robertson,

Rahman

2023

IET Radar Sonar & Navi

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Unmanned Aerial Vehicles, or drones, pose a significant threat to privacy and security. To understand and assess this threat, classification between different drone models and types is required. One way in which this has been demonstrated experimentally is through this use of micro‐Doppler information from radars. Classifiers capable of exploiting differences in micro‐Doppler spectra will require large amounts of data but obtaining such data experimentally is expensive and time consuming. The authors present the methodology and results of a drone micro‐Doppler simulation framework which uses accurate 3D models of drone components to yield detailed and realistic synthetic micro‐Doppler signatures. This is followed by the description of a purpose‐built validation radar that has been developed specifically to gather high‐fidelity experimental drone micro‐Doppler data with which is used to validate the simulation. Detailed comparisons between the experimental and simulated micro‐Doppler spectra from three models of drones with differently shaped propellers are given, showing very good agreement. The aim is to introduce the simulation methodology. Validation using single propeller micro‐Doppler is provided, although the simulation can be extended to multiple propellers. The simulation framework offers the potential to generate large quantities of realistic drone micro‐Doppler signatures for training classification algorithms.

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Section: Micro-doppler For Drone Classificationmentioning

confidence: 99%

A new simulation methodology for generating accurate drone micro‐Doppler with experimental validation

Moore,

Robertson,

Rahman

2023

IET Radar Sonar & Navi

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“…To study the accuracy of the theoretical simulation analysis results and expand the data sources, the electromagnetic simulation software FEKO was used to simulate the flicker features of the drone. References [15,27] built a simplified 3D model of the drone as shown in Figure 3. The simulation was divided into a fuselage component multi-attitude simulation and blade multi-attitude dynamic simulation.…”

Section: Theoretical Simulation Analysis Of Flicker Mechanism and Ele...mentioning

confidence: 99%

“…In addition, some researchers use electromagnetic simulations to obtain echo data to obtain more reliable simulation data [14]. Arne Schröder et al [15,16] used the electromagnetic simulation software HFSS to conduct a detailed study on the electromagnetic characteristics of the multi-rotor drone. The results show that the multi-rotor drone body component only increases the contribution of the spectral zero-frequency component of the echo signal.…”

Section: Introductionmentioning

confidence: 99%

A Multi-Rotor Drone Micro-Motion Parameter Estimation Method Based on CVMD and SVD

Yang

Liang

et al. 2022

Remote Sensing

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It is of great significance to detect drones in airspace due to the substantial increase and regrettable misuse in the consumer market. In this paper, we establish a micro-motion theoretical model of a drone and analyze the micro-Doppler signature of rotor targets and the flicker mechanisms of the multi-rotor targets. Hence, for the target recognition problem of multi-rotor drones, a multi-rotor target micro-Doppler parameter estimation method is proposed. Firstly, a signal frequency domain segmentation method is proposed based on the complex variational mode decomposition (CVMD) to separate the high-frequency part of the high-frequency flicker in the frequency domain. Secondly, for the signal after frequency domain segmentation, a flicker time domain position method based on singular value decomposition (SVD) is proposed. Finally, by integrating CVMD frequency domain segmentation and SVD time domain positioning, the reconstruction of multi-rotor target scintillation at different speeds is realized, and the micro-motion parameters of rotor blades are successfully estimated. The simulation results show that the method has high accuracy in estimating the micro-motion parameters of a multi-rotor, which makes up for the shortage of the traditional method in estimating the micro-motion parameters of the multi-rotor target.

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“…However, the applicability of integral model has not been further studied. 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].…”

Section: Introductionmentioning

confidence: 99%

“…In order to reduce the computational complexity, Pouliguen et al [10] excluded the interactions between the airframe and the rotors. Schröder [14] numerically analyzed the time-frequency spectra of four rotating rotors, one rotating rotors and a full DJI Phantom Vision 2 assembled with four rotating rotors, respectively. The simulated time-frequency spectra indicated that the airframe only increased the contribution of zero-frequency component and multiple rotors resulted in the superposition of different initial rotation angles.…”

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

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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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Numerical RCS and micro-Doppler investigations of a consumer UAV

Cited by 7 publications

References 6 publications

A new simulation methodology for generating accurate drone micro‐Doppler with experimental validation

A new simulation methodology for generating accurate drone micro‐Doppler with experimental validation

A Multi-Rotor Drone Micro-Motion Parameter Estimation Method Based on CVMD and SVD

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

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