Micro-doppler interference removal via histogram analysis in time-frequency domain

Zhang, Rui; Li, Gang; Zhang, Yimin Daniel

doi:10.1109/taes.2015.150112

Cited by 28 publications

(28 citation statements)

References 28 publications

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“…To eliminate the micromotion components of the echoes in the contaminated range cell, both the method in R. Zhang et al [ 9 ] and the L-statistics-based method utilize the time-frequency representations obtained by the STCS [ 11 ]. However, part of the main body signal in the time-frequency domain is missing due to the discarded pulses, as illustrated in Figure 5 .…”

Section: Experimental Results and Performance Comparisonsmentioning

confidence: 99%

“…Additionally, there is a strong m-D signal which has the shape of sinusoids. As a result, the histogram analysis in R. Zhang et al [ 9 ] could not be used to remove the m-D signal, which might have been mistaken for the main body signal. Figure 6 a shows the imaging result produced by the method in R. Zhang et al [ 9 ].…”

Section: Experimental Results and Performance Comparisonsmentioning

confidence: 99%

“…However, a large amount of STFT entries corresponding to the main body might be removed together with the m-D interference, which leads to a high sidelobe level in the imaging result [ 9 ]. A method based on histogram analysis is proposed in R. Zhang et al [ 9 ], where the STFT entries with a high frequency of occurrence were regarded as the main body components and were preserved to reconstruct the ISAR image. On the other hand, the STFT entries with a low frequency of occurrence were considered to correspond to the m-D interference and suppressed.…”

Section: Introductionmentioning

confidence: 99%

“…On the other hand, the STFT entries with a low frequency of occurrence were considered to correspond to the m-D interference and suppressed. When the m-D effect is severe, the method in R. Zhang et al [ 9 ] cannot remove the m-D signal in the time-frequency domain completely because the m-D components might be mistaken for the main body signal. Consequently, there are some spurious points in the imaging result due to the residual m-D signal.…”

Section: Introductionmentioning

confidence: 99%

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Micro-Doppler Effect Removal in ISAR Imaging by Promoting Joint Sparsity in Time-Frequency Domain

Sun

Chen

2018

Sensors

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For micromotion scatterers with small rotating radii, the micro-Doppler (m-D) effect interferes with cross-range compression in inverse synthetic aperture radar (ISAR) imaging and leads to a blurred main body image. In this paper, a novel method is proposed to remove the m-D effect by promoting the joint sparsity in the time-frequency domain. Firstly, to obtain the time-frequency representations of the limited measurements, the short-time Fourier transform (STFT) was modelled by an underdetermined equation. Then, a new objective function was used to measure the joint sparsity of the STFT entries so that the joint sparse recovery problem could be formulated as a constrained minimization problem. Similar to the smoothed l0 (SL0) algorithm, a steepest descend approach was used to minimize the new objective function, where the projection step was tailored to make it suitable for m-D effect removal. Finally, we utilized the recovered STFT entries to obtain the main body echoes, based on which cross-range compression could be realized without m-D interference. After all contaminated range cells were processed by the proposed method, a clear main body image could be achieved. Experiments using both the point-scattering model and electromagnetic (EM) computation validated the performance of the proposed method.

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Section: Experimental Results and Performance Comparisonsmentioning

confidence: 99%

Section: Experimental Results and Performance Comparisonsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Micro-Doppler Effect Removal in ISAR Imaging by Promoting Joint Sparsity in Time-Frequency Domain

Sun

Chen

2018

Sensors

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“…Due to the smoothing of the window, the fuzzy phenomenon of the time-frequency diagram is greatly reduced, and the interference of other time-frequency curves can be eliminated. The change of microDoppler is better observed [5][6][7].…”

Section: Time-frequency Analysis Of Micro-dopplermentioning

confidence: 97%

Research on micro-Doppler feature of spatial target

Zhang

et al. 2017

J Wireless Com Network

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The micro-Doppler (m-D) effect which is also called micro-motion effect is a kind of physical phenomenon, which is often produced in ISAR imaging of space targets. When the space target has a micro-Doppler effect, it will produce frequency modulation for the radar echo and cause serious interference to ISAR imaging of the target. In this paper, the micro-spin model is modeled, and the echo of micro-spin model scattering point is processed respectively by short-time Fourier transform (STFT), Wigner-Vile Distribution (WVD), and pseudo-Wigner-Vile Distribution (PWV), and the micro-Doppler curve is derived. On this basis, for the space target with spin components, this paper introduces an ISAR imaging algorithm using the micro-Doppler removal based on STFT and proposes an improved algorithm based on rigid body parameter estimation, which can obtain better imaging results.

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Detection and Classification of Helicopter Drive Shaft Faults Using Neuro-Fuzzy Based on Wavelet Power Spectrum Algorithm

Hassan

Habib

Bayoumi

2020

Advances in Asset Management and Condition Monitoring

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Micro-doppler interference removal via histogram analysis in time-frequency domain

Cited by 28 publications

References 28 publications

Micro-Doppler Effect Removal in ISAR Imaging by Promoting Joint Sparsity in Time-Frequency Domain

Micro-Doppler Effect Removal in ISAR Imaging by Promoting Joint Sparsity in Time-Frequency Domain

Research on micro-Doppler feature of spatial target

Detection and Classification of Helicopter Drive Shaft Faults Using Neuro-Fuzzy Based on Wavelet Power Spectrum Algorithm

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