Envelope Correction of Micro-Motion Targets Based on Multi-Layer Perceptron During THz-ISAR Sensing

Yang, Qi; Zeng, Yifan; Zhang, Ye; Wang, Hongqiang; Deng, Bin; Qin, Yuliang

doi:10.1109/access.2019.2929065

Cited by 8 publications

(4 citation statements)

References 18 publications

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“…Therefore, the range cell migration caused by high-frequency vibration error can be ignored. After performing the range cell migration correction through interpolation in the range-doppler domain, (7) can be expressed as…”

Section: Thz-sar Imaging Model With High-frequency Vibration Errormentioning

confidence: 99%

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A Novel High-Frequency Vibration Error Estimation and Compensation Algorithm for THz-SAR Imaging Based on Local FrFT

Ding

Zheng

et al. 2020

Sensors

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Compared with microwave synthetic aperture radar (SAR), terahertz SAR (THz-SAR) is easier to achieve ultrahigh-resolution image due to its higher frequency and shorter wavelength. However, higher carrier frequency makes THz-SAR image quality very sensitive to high-frequency vibration error of motion platform. Therefore, this paper proposes a novel high-frequency vibration error estimation and compensation algorithm for THz-SAR imaging based on local fractional Fourier transform (LFrFT). Firstly, the high-frequency vibration error of the motion platform is modeled as a simple harmonic motion and THz-SAR echo signal received in each range pixel can be considered as a sinusoidal frequency modulation (SFM) signal. A novel algorithm for the parameter estimation of the SFM signal based on LFrFT is proposed. The instantaneous chirp rate of the SFM signal is estimated by determining the matched order of LFrFT in a sliding small-time window and the vibration acceleration is obtained. Hence, the vibration frequency can be estimated by the spectrum analysis of estimated vibration acceleration. With the estimated vibration acceleration and vibration frequency, the SFM signal is reconstructed. Then, the corresponding THz-SAR imaging algorithm is proposed to estimate and compensate the phase error caused by the high-frequency vibration error of the motion platform and realize high-frequency vibration error estimation and compensation for THz-SAR imaging. Finally, the effectiveness of the novel algorithm proposed in this paper is demonstrated by simulation results.

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Section: Thz-sar Imaging Model With High-frequency Vibration Errormentioning

confidence: 99%

“…However, recent research results show that the THz gap has great development potential and application value due to its unique electromagnetic wave band [1,2]. In recent years, THz waves have been widely used in explosives detection, drug detection, imaging, radar and wireless broadband communication [3][4][5][6][7].…”

Section: Introductionmentioning

confidence: 99%

A Novel High-Frequency Vibration Error Estimation and Compensation Algorithm for THz-SAR Imaging Based on Local FrFT

Ding

Zheng

et al. 2020

Sensors

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“…photonics [1], [2]. Due to its special characteristics different from microwave and infrared radiation, THz wave has been used in many applications [3]- [8]. Among the numerous applications of THz wave, THz radar imaging technique has been receiving more and more attention in the modern radar imaging fields.…”

Section: Introductionmentioning

confidence: 99%

Estimation of High-Frequency Vibration Parameters for Terahertz SAR Imaging Based on FrFT With Combination of QML and RANSAC

et al. 2021

IEEE Access

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High-frequency vibration of motion platform leads to paired echo for synthetic aperture radar (SAR) imaging, especially in terahertz band due to its shorter wave length. Different from most existing parameters estimation methods only considering single component high-frequency vibration, in this paper a novel method considering multi-components vibration model is proposed based on fractional Fourier transform (FrFT) with combination of quasi-maximum likelihood (QML) and random sample consensus (RANSAC). Based on the model establishment of high-frequency vibration error in the echo, its instantaneous chirp rate (ICR) is firstly estimated by FrFT in sliding sub-aperture, followed which the vibration parameters are coarsely obtained through spectrum analysis and least square (LS) regression. To further refine the parameters estimates, QML is developed for compensating the deviation both caused by the frequency spectrum leakage and the error propagation effects by one-dimensional search over the vibration frequency. Meanwhile, RANSAC is adopted for avoiding the outlier of the ICR estimates in LS regression, especially at low signal-to-noise ratio (SNR). Thus, the refinement strategy based on the combination of QML and RANSAC is developed, whose utilization improves the estimation accuracy of vibration parameters. Finally, the paired echo in terahertz SAR (THz-SAR) imaging is effectively suppressed by the proposed method, and the high-quality THz-SAR imaging results are achieved. Both simulations of single component and multi-components high-frequency vibration are used to verify the validity of the proposed method. The simulation results show that the proposed method has higher estimation accuracy even at low SNR.INDEX TERMS Fractional Fourier transform (FrFT), high-frequency vibration, quasi-maximum likelihood (QML), random sample consensus (RANSAC), terahertz synthetic aperture radar (THz-SAR).

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“…In addition, when it penetrates the human body, THz radiation is harmless due to its lower photon energy. These unique characteristics allow THz imaging to be used in many fields [3][4][5][6][7].…”

Section: Introductionmentioning

confidence: 99%

A High-Frequency Vibration Error Compensation Method for Terahertz SAR Imaging Based on Short-Time Fourier Transform

Jiang

et al. 2021

Applied Sciences

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High-frequency vibration error of a moving radar platform easily introduces a non-negligible phase of periodic modulation in radar echoes and greatly degrades terahertz synthetic aperture radar (THz-SAR) image quality. For solving the problem of THz-SAR image-quality degradation, the paper proposes a multi-component high-frequency vibration error estimation and compensation approach based on the short-time Fourier transform (STFT). To improve the robustness of the method against noise effects, STFT is used to extract the instantaneous frequency (IF) of a high-frequency vibration error signal, and the vibration parameters are coarsely obtained by the least square (LS) method. To reduce the influence of the STFT window widths, a method based on the maximum likelihood function (MLF) is developed for determining the optimal window width by a one-dimensional search of the window widths. In the case of high noise, many IF estimation values seriously deviate from the true ones. To avoid the singular values of IF estimation in the LS regression, the random sample consensus (RANSAC) is introduced to improve estimation accuracy. Then, performing the STFT with the optimal window width, the accurate vibration parameters are estimated by LS regression, where the singular values of IF estimation are excluded. Finally, the vibration error is reconstructed to compensate for the non-negligible phase of the platform-induced periodic modulation. The simulation results prove that the error compensation method can meet THz-SAR imaging requirements, even at a low signal-to-noise ratio (SNR).

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Envelope Correction of Micro-Motion Targets Based on Multi-Layer Perceptron During THz-ISAR Sensing

Cited by 8 publications

References 18 publications

A Novel High-Frequency Vibration Error Estimation and Compensation Algorithm for THz-SAR Imaging Based on Local FrFT

A Novel High-Frequency Vibration Error Estimation and Compensation Algorithm for THz-SAR Imaging Based on Local FrFT

Estimation of High-Frequency Vibration Parameters for Terahertz SAR Imaging Based on FrFT With Combination of QML and RANSAC

A High-Frequency Vibration Error Compensation Method for Terahertz SAR Imaging Based on Short-Time Fourier Transform

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