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

Li, Yinwei; Wu, Qi; Wu, Jiawei; Li, Ping; Zheng, Qibin; Ding, Lizhong

doi:10.1109/access.2020.3047856

Cited by 15 publications

(20 citation statements)

References 29 publications

(25 reference statements)

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“…To verify the effectiveness of the high-frequency vibration parameter estimation method proposed in this paper, simulation experiments were carried out on the multi-component high-frequency vibration error estimation and compensation of airborne THz-SAR, and the result of the proposed method (Chirplet-LSSE-SRT) is compared with the parameter estimation method based on FrFT combined with QML and SANSAC (FrFT-QML-SANSAC) in [21]. Firstly, the imaging simulation of a point target was carried out to verify the influence of high-frequency vibration on imaging.…”

Section: Simulation Results and Discussionmentioning

confidence: 99%

“…It can be seen that LS sequential estimators have high accuracy. We compared our method with the existing approach FrFT-QML-RANSAC [21], and the estimation results of the two methods are shown in Table 3. It can be seen that the Chirplet-LSSE-SRT method is more accurate than the FrFT-QML-RANSAC method.…”

Section: Simulation Results Of Point Targetsmentioning

confidence: 99%

“…Then, the task is transformed to estimate the ICR of the echo signal and its parameters. In [21], the ICR of the signal is estimated based on fractional Fourier transform (FrFT) combined with quasi-maximum likelihood (QML) and random sample consensus (RANSAC). Then, the parameters of high-frequency vibration can be estimated by employing the discrete Fourier transform (DFT) and a least square (LS) estimator.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Estimation of High-Frequency Vibration Parameters for Airborne Terahertz SAR Using Chirplet Decomposition and LS Sequential Estimators

Hao

Sun

et al. 2022

Remote Sensing

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Due to the short wavelength of the terahertz wave, airborne terahertz synthetic aperture radar (THz-SAR) suffers from echo phase errors caused by the high-frequency vibration of the platform. These errors will result in defocusing and the emergence of ghost targets, which will degrade the quality of the image. Therefore, it is necessary to compensate for phase errors in order to bring the image into focus. This paper proposes a multi-component high-frequency vibration parameter estimation method based on chirplet decomposition and least squares (LS) sequential estimators, which differs from other methods that can only be applied to simple harmonic vibrations. In particular, we first obtain the instantaneous chirp rate (ICR) of the signal by chirplet decomposition. Then, we employ the LS sequential estimators in conjunction with separable regression technique (SRT) to estimate vibration parameters. The estimated parameters are subsequently used to re-establish the ICR components for each vibration component and these parameters are further re-estimated to improve their accuracy. Based on the estimated parameters, phase compensation functions can be constructed to suppress the defocusing and ghost targets in airborne THz-SAR imaging. Simulated results on point targets and distributed imaging scenes demonstrate that the proposed method is accurate and reliable even at low signal-to-noise ratios (SNRs).

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Section: Simulation Results and Discussionmentioning

confidence: 99%

Section: Simulation Results Of Point Targetsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Estimation of High-Frequency Vibration Parameters for Airborne Terahertz SAR Using Chirplet Decomposition and LS Sequential Estimators

Hao

Sun

et al. 2022

Remote Sensing

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“…THz radar, as essential research in target detection, has been receiving increasing attention among these applications. Compared with the microwave radar, THz radar systems have a higher carrier frequency, larger absolute bandwidth, higher data rate, and smaller dimension [6][7][8]. However, because of the huge difference between the size of targets and the wavelength in the submillimeter wave band, the scattered near-field region of the target is up to tens of kilometers in size.…”

Section: Introductionmentioning

confidence: 99%

Generalized Radar Range Equation Applied to the Whole Field Region

Xiao

Xie

Gao

et al. 2022

Sensors

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Most terahertz (THz) radar systems can only work in the near-field region, because the THz source power is limited and the size of the target scattered near field is up to tens of kilometers. Such conditions will result in the conventional radar range equation being unsuitable. Therefore, the near-field radar cross section (RCS) formula is given according to the numerical simulation on different targets. By modifying the parameters in the near field, including the gain of radar antennas and the RCS of targets, the generalized radar range equation is proposed. The THz radar working efficiency in the whole range and the simulation of the near-field RCS simulation model were employed to validate its effectiveness. Through comparison with the radar range equation, it can be concluded that the calculation results of the proposed equation are smaller in the near field, and the outcomes in the far field are identical. The proposed generalized radar range equation can be applied to the whole radiation area including the near field and the far field. Furthermore, more complicated real targets are calculated according to the generalized radar range equation and it can be extended from the submillimeter wave band to a much wider band range. Finally, the near-field radar theory is established, which shows its potential application to the radar cross section estimation in the extremely high frequency and fine design of THz radar systems.

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“…However, it inevitably results in large estimation errors because of the convergence to a local minimum. In [24], an improved DFrFT-based estimation method is proposed to estimate multi-component vibration parameters. However, there exists a great correlation between the method accuracy and the window width.…”

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

Cited by 15 publications

References 29 publications

Estimation of High-Frequency Vibration Parameters for Airborne Terahertz SAR Using Chirplet Decomposition and LS Sequential Estimators

Estimation of High-Frequency Vibration Parameters for Airborne Terahertz SAR Using Chirplet Decomposition and LS Sequential Estimators

Generalized Radar Range Equation Applied to the Whole Field Region

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

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