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ZHOU Hongping, LI Rui, LI Liuling, et al. Micromotions parameter extraction of birds and rotary-wing unmanned aerial vehicles based on vortex radar[J]. Journal of Radars, in press. doi: 10.12000/JR25164
Citation: ZHOU Hongping, LI Rui, LI Liuling, et al. Micromotions parameter extraction of birds and rotary-wing unmanned aerial vehicles based on vortex radar[J]. Journal of Radars, in press. doi: 10.12000/JR25164
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Micromotions Parameter Extraction of Birds and Rotary-wing unmanned aerial vehicles Based on Vortex Radar

DOI: 10.12000/JR25164 CSTR: 32380.14.JR25164

  • School of Computer and Information, Hefei University of Technology, Hefei 230009, China

Funds:  The National Natural Science Foundation of China (61775050)
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  • Corresponding author: GUO Zhongyi, guozhongyi@hfut.edu.cn
  • Received Date: 2025-09-01
    Available Online: 2026-02-10
    Abstract
  • To address the urgent need to identify birds and rotary-wing unmanned aerial vehicles (UAVs), this paper proposes a vortex radar–based method for extracting micromotion parameters of targets. The study focused on target parameter acquisition and systematically extended target modeling and parameter extraction strategies. First, mathematical models were developed for the body motion and wing flapping behavior of birds as well as for the rotor movement characteristics and body structure of rotary-wing UAVs. Further, analytical expressions for the radial and rotational Doppler frequency shifts at scattering points were derived, and micro-Doppler features were extracted from radar echo signals to enable target parameter inversion. For bird targets, the radial Doppler frequency was estimated by extracting the spectral peak of the echo signal to obtain the flight velocity. In addition, by combining the rotational Doppler frequency shifts of the scattering points and analyzing the variations of the rotational Doppler frequency using the short-time Fourier transform (STFT), the wing-flapping length was estimated. Even under low signal-to-noise ratio (SNR) conditions, the estimation error of the wing-flapping length remained within 0.03 m. For rotary-wing UAV targets, an echo signal model was first constructed, and the analytical relationship between the radial and rotational components of the micro-Doppler frequency shift was derived. Using the reconstructed Doppler information and through range–time domain analysis, six structural and motion parameters were retrieved, including the Euler angles rotor rotational speed, rotor length, and the distance between the UAV body and rotor. The estimation errors for all parameters were significantly lower than those obtained with conventional approaches based on individual Doppler features, with all parameters remaining within 2%. Simulation results demonstrated that the proposed vortex radar–based parameter extraction method enables accurate multiparameter estimation for birds and rotary-wing UAVs. The method also exhibits stable and reliable performance under low SNR conditions, confirming its effectiveness and applicability in practical engineering scenarios.

     

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