Micro-Doppler Feature Extraction of Inverse Synthetic Aperture Imaging Laser Radar Using Singular-Spectrum Analysis

Zhu, Mingzhe; Zhou, Xianda; Zang, Bo; Yang, Binsheng; Xing, Mengdao

doi:10.3390/s18103303

Cited by 9 publications

(11 citation statements)

References 15 publications

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“…ISAIL imaging is the mapping of target echoes in the distance-Doppler plane. The model of the ISAIL m-D effect is described as Figure 1 [16]. Assuming the echo density function of the target is ρ (x,y) , the radar echo signal can be expressed as: The distance R(t) and rotation angle θ(t) of the instantaneous target can be determined by the initial position R 0 and θ 0 ,the initial velocity V 0 and initial angular velocity ω 0 , the initial acceleration a 0 and initial angular acceleration α 0 and other high-order terms.…”

Section: The Principle Of Isail Time-frequency Imagingmentioning

confidence: 99%

“…In order to verify the effectiveness of the proposed algorithm, it was tested with numerical simulation and real ISAIL m-D data. Simultaneously, compared with the use of singular-spectrum analysis extraction micro-Doppler features [16]. Simulation 1, the ISAIL data was simulated on the helicopter miniaturization model.…”

Section: Simulationmentioning

confidence: 99%

“…However, it can still be seen that the helicopter body imaging results are significantly disturbed. Figure 5d shows the result of imaging the helicopter main body after separating the micro-Doppler information by the singular-spectrum analysis [16] and Figure 5e is by the RANSAC method. It can be seen from the figure that the separated target features using the RANSAC algorithm are more obvious.…”

Section: Simulationmentioning

confidence: 99%

“…Figure 6b shows the separated micro-Doppler component. In Figure 6c, the data processed by the singular-spectrum analysis [16] is shown and Figure 6d is the data processed by the RANSAC algorithm. It all separates the rigid body portion from the micro-Doppler portion such as a propeller.…”

Section: Simulationmentioning

confidence: 99%

“…In recent years, the micro-Doppler effect on laser radar has gradually attracted attention in the field of radar. Inverse synthetic aperture imaging laser (ISAIL) [16] is such a coherent laser radar, the micron-size working wavelength makes a sensitive detection of the m-D effect of target. The impact of the micro-Doppler effect on ISAIL imaging is mainly reflected in two aspects.…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

Application of S-Transform Random Consistency in Inverse Synthetic Aperture Imaging Laser Radar Imaging

et al. 2019

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Under the same principle, laser radar could be more sensitive to the micro-Doppler (m-D) effect due to its wave length, as the characteristic of multi-resolution, S transform could reduce the influence of the micro-Doppler component and enhance the imaging effect. This paper presents a method for micro-Doppler feature extraction in Inverse Synthetic Aperture Imaging Laser Radar (ISAIL) imaging. It is accessible and comprehensive, applying Random Sample Consensus (RANSAC) for the separation and reconstruction of micro-Doppler and rigid body signals. Experiments show that the method can effectively remove the micro-Doppler information and obtain a clear target distance-instantaneous Doppler image.

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Section: The Principle Of Isail Time-frequency Imagingmentioning

confidence: 99%

Section: Simulationmentioning

confidence: 99%

Section: Simulationmentioning

confidence: 99%

Section: Simulationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Application of S-Transform Random Consistency in Inverse Synthetic Aperture Imaging Laser Radar Imaging

et al. 2019

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Detection and identification technology of rotor unmanned aerial vehicles in 5G scene

Hong

Zhao

et al. 2019

International Journal of Distributed Sensor Networks

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In the 5G era, integration between different networks is required to realize a new world of Internet of things, the most typical model is Space–Air–Ground Internet of things. In the Space–Air–Ground Internet of things, unmanned aerial vehicle network is widely used as the representative of air-based networks. Therefore, a lot of unmanned aerial vehicle “black flying” incidents have occurred. UAVs are a kind of “low, slow and small” artificial targets, which face enormous challenges in detecting, identifying, and managing them. In order to identify the “black flying” unmanned aerial vehicle, combined with the advantages of 5G millimeter wave radar and machine learning methods, the following methods are adopted in this article. For a one-rotor unmanned aerial vehicle, the radar echo data are a single-component sinusoidal frequency modulation signal. The echo signal is conjugated first and then is subjected to a short-time Fourier transform, while the micro-Doppler has a double effect. For a multi-rotor unmanned aerial vehicle, the radar echo data are a multi-component sinusoidal frequency modulation signal, the k-order Bessel function base and the signal are used for integral projection processing, which better identifies the micro-Doppler characteristics such as the number of rotors or the rotational speed of each rotor. The noise interference is added to verify that the algorithm has better robustness. The micro-Doppler characteristics of rotor unmanned aerial vehicles are extracted by the above algorithm, and the data sets are built to train the model. Finally, the classification of unmanned aerial vehicle is realized, and the classification results are given. The research in this article provides an effective solution to solve the problem of detecting and identifying unmanned aerial vehicle by 5G millimeter wave radar in the Internet of Things, which has high practical application value.

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Pose Measurement and Motion Estimation of Space On-Orbit CubeSats Based on Micro-Doppler Effect Using Laser Coherent Radar

Zhang

Han

et al. 2022

Applied Sciences

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The pose measurement and motion estimation of long-distance space CubeSats is a difficult problem for autonomous rendezvous and track maintenance. In this work, an approach is proposed for the pose estimation of CubeSat based on the micro-Doppler effect by a laser radar system. Parameters such as spin rate and attitude angle can be estimated using data extracted from the returned signal. By utilizing threshold processing, edge extraction of time-frequency (TF) images can be achieved effectively. When the target size is unknown, the double edge ratio method (DERM) is suggested to obtain the attitude angle. The simulation results show that when the noise is not too high, the spin rate and the attitude angle can be acquired precisely. Our experiment indicates that the error for the estimation of spin and pose by our approach fulfills the demand in practice.

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Micro-Doppler Feature Extraction of Inverse Synthetic Aperture Imaging Laser Radar Using Singular-Spectrum Analysis

Cited by 9 publications

References 15 publications

Application of S-Transform Random Consistency in Inverse Synthetic Aperture Imaging Laser Radar Imaging

Application of S-Transform Random Consistency in Inverse Synthetic Aperture Imaging Laser Radar Imaging

Detection and identification technology of rotor unmanned aerial vehicles in 5G scene

Pose Measurement and Motion Estimation of Space On-Orbit CubeSats Based on Micro-Doppler Effect Using Laser Coherent Radar

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