Time‐varying three‐dimensional interferometric imaging for space rotating targets with stepped‐frequency chirp signal

Sun, Yan; Luo, Ying; Zhang, Qun; Hu, Jian; Huo, Wenjun

doi:10.1049/iet-rsn.2017.0009

Cited by 15 publications

(5 citation statements)

References 23 publications

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“…The greatest strength of the proposed method is to prove a method for the radar network to reconstruct the 3D image of the spinning target, and the anisotropy problem which is caused when the radars in the network observe the target from the different perspectives is overcome in the proposed method. At present, interferometric technique is regarded as an effective method to reconstruct the 3D image with high precision, and there are several novel and cutting-edge papers [10,11,14,20,30] which study the interferometric technique to reconstruct the 3D target image. In the interferometric 3D imaging method, L-shaped three-antenna configuration or the Bistatic radar configuration is necessary to generate the interferometric signal and calculate the interferometric phase.…”

Section: Discussionmentioning

confidence: 99%

“…Bai et al proposed a nonparametric 3D-imaging method based on scattering center trajectory association [13], and the matrix completion method based on the Riemannian manifold optimization was designed. Sun et al proposed a time-varying interferometric 3D imaging method for space rotating targets based on stepped-frequency chirp signal [14]. In addition, the parametric methods for forming 3D image of micromotion target mainly include 3D imaging of spinning targets based on the fixed scattering center model and imaging of smooth precession cones based on the sliding scattering center model [15][16][17][18].…”

Section: Introductionmentioning

confidence: 99%

“…On the other hand, there is bare minimum of available real radar data acquired by the radar network in the field of the space target imaging research currently, especially the space spinning target 3D imaging research. In current work [13][14][15], the simulation data is usually used to verify the space target imaging method. Future work must be focused on constructing the real radar network experimental platform and verifying the proposed method in using real radar data.…”

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confidence: 99%

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Reconstruction of Three-Dimensional Images Based on Estimation of Spinning Target Parameters in Radar Network

et al. 2018

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A high-resolution three-dimensional (3D) image reconstruction method for a spinning target is proposed in this paper and the anisotropy is overcome by fusing different observation information acquired from the radar network. The proposed method will reconstruct the 3D scattering distribution, and the mapping of the reconstructed 3D image onto the imaging plane is identical to the two-dimensional (2D) imaging result. At first, the range compression and inverse radon transform is employed to produce the 2D image of the spinning target. In addition, the process of mapping the spinning target onto the imaging plane is analyzed and the mapping formulas which are to map the point onto the 2D image plane are derived. After the micro-Doppler signature about which every reconstructed point in 2D imaging result is extracted by the Radon transform, the extended Hough transform is adopted to calculate an important parameter about the micro-Doppler signature, and the 3D image reconstruction model for the spinning target is constructed based on the radar network. Finally, the algorithm for solving the reconstruction model is proposed and the 3D image of the spinning target is obtained. Some simulation results are given to illustrate the effectiveness of the proposed method, and results show that the mean square error (MSE) relatively holds a steady trend when the signal-to-noise ratio (SNR) is higher than −10 dB and the MSE of the reconstructed 3D target image is less than 0.15 when SNR is at the level of −10 dB.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

mentioning

confidence: 99%

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Reconstruction of Three-Dimensional Images Based on Estimation of Spinning Target Parameters in Radar Network

et al. 2018

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“…In reference [12], the crazy‐climber algorithm is used to separate time‐frequency ridges of different signals. In reference [13], the echo trajectories of scatteres are extracted by the vector association method in the RTP.…”

Section: Introductionmentioning

confidence: 99%

Radar backscattering modelling and micro‐motion parameter estimation method for quadcopter

Mao

Zhu

et al. 2021

IET Radar Sonar & Navi

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Due to the high-speed rotors and overlapped propellers, it is still a challenge to extract the micro-motion parameters of the quadcopter. In this work, the authors establish a radar backscattering model of the quadcopter based on the flight control theory and radar backscattering characteristics. Then, the improved template matching method and peak grouping method are proposed to capture the periodic information for overlapped propellers on a range-time profile and extract the rotation speeds of rotors. By simulating the nine types of quadcopter movements, the relative error of the rotation speeds is estimated to be lower than 1.4% for each rotor with a signal-to-noise ratio of 15 dB.

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“…Nowadays, the 3D distribution reconstruction of scattering centre of the spinning target has been studied by many researchers. A time‐varying interferometric 3D imaging method for space rotating targets is proposed based on stepped‐frequency chirp signal [4]. A non‐parametric 3D imaging method based on scattering centre trajectory association has been reported in [5].…”

Section: Introductionmentioning

confidence: 99%

3D image reconstruction of spinning cone‐shaped target

Liu

et al. 2019

J. eng.

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Time‐varying three‐dimensional interferometric imaging for space rotating targets with stepped‐frequency chirp signal

Cited by 15 publications

References 23 publications

Reconstruction of Three-Dimensional Images Based on Estimation of Spinning Target Parameters in Radar Network

Reconstruction of Three-Dimensional Images Based on Estimation of Spinning Target Parameters in Radar Network

Radar backscattering modelling and micro‐motion parameter estimation method for quadcopter

3D image reconstruction of spinning cone‐shaped target

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