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

Li, Yinwei; Ding, Lizhong; Zheng, Qibin; Zhu, Yiming; Sheng, Jialian

doi:10.3390/s20092669

Cited by 15 publications

(10 citation statements)

References 18 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The wavelet multi-resolution analysis in conjunction with the Doppler keystone transform (DKT) and the parametric space projection is presented to estimate the high-frequency vibration [13], [14]. The local fractional Fourier transform (LFrFT) is proposed to estimate and compensate for the high-frequency vibration of the platform [15]. In [16], the adaptive chirplet decomposition is proposed to focus the image for the THz SAR system.…”

Section: Nomenclaturementioning

confidence: 99%

Compensation for High-Frequency Vibration of SAR Imaging in the Terahertz Band Based on Linear Chirplet Transform and Empirical Mode Decomposition

Chen

Wang

Zhang

2023

IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

View full text Add to dashboard Cite

Synthetic aperture radar (SAR) in Terahetz (THz) band is very important and valuable in the field of radar signal processing, and it is much sensitive to the high-frequency vibration of the platform due to the short wavelength. In this paper, the high-frequency vibration is characterized as multi-component sinusoidal frequency modulated (SFM) signal, and the parameters estimation method based on the linear chirplet transform (LCT) and empirical mode decomposition (EMD) is proposed to compensate the high-frequency vibration errors. This method can extract the instantaneous frequency (IF) of the received signal with high precision, and the focused SAR image can be obtained consequently. Results of simulated and real measured data are provided to illustrate the effectiveness of the novel algorithm proposed in this paper.

show abstract

Section: Nomenclaturementioning

confidence: 99%

Compensation for High-Frequency Vibration of SAR Imaging in the Terahertz Band Based on Linear Chirplet Transform and Empirical Mode Decomposition

Chen

Wang

Zhang

2023

IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

View full text Add to dashboard Cite

show abstract

“…The azimuth phase can be inferred from the stationary phase point. The azimuth phase of stationary targets is given by (24), and the azimuth phase of rotating targets is given by (25). Therefore, the stationary phase point offset produces a difference in the azimuth phase.…”

Section: A Signal Model and Influence Of Rotation After Rcmcmentioning

confidence: 99%

High-Resolution SAR Imaging Characteristics for Multiple Scattering of Rotating Targets

Wang,

Qiu,

Wen

2024

IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

View full text Add to dashboard Cite

The rotation of targets in high-resolution synthetic aperture radar (SAR) images results in complex and nonlinear micro-Doppler modulation of SAR returns, exhibiting distinct and diverse imaging characteristics under different conditions. This poses challenges to image interpretation, target detection and recognition. This study establishes signal models for single and multiple scattering of rotating targets in high-resolution spaceborne SAR and, in conjunction with the processing procedures of range doppler algorithm (RDA), derives the azimuth bandwidth and the conditions for azimuth frequency aliasing caused by rotation. Quantitative analysis of the errors introduced by target rotation in various signal domains is performed, takeing into account the stationary phase point offset, the rotationinduced range migration correction error (RMCE), and the change of azimuth phase in detail. Additionally, representative signatures of these influences in SAR images are simulated and interpreted and more accurate theoretical models of imaging results are derived. The processing and analysis of both simulation and real measured data validate the correctness of the theoretical derivation in this study and provide support for the interpretation and information extraction of high-resolution SAR rotating targets.

show abstract

“…However, the device is difficult to miniaturize, and the flexible connection between the radar and the platform may make the positioning of the radar inaccurate. Thus, the adaptive chirplet decomposition and local fractional Fourier transform (LFrFT) are applied to estimate highfrequency vibration parameters in [10][11][12][13][14][15][16]. Using advanced time-frequency representation approaches, these methods can improve the accuracy of azimuth instantaneous chirp rate (ICR) estimation and realize novel compensation of single harmonic vibration errors.…”

Section: Introductionmentioning

confidence: 99%

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

Hao

Sun

et al. 2022

Remote Sensing

View full text Add to dashboard Cite

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).

show abstract

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

Cited by 15 publications

References 18 publications

Compensation for High-Frequency Vibration of SAR Imaging in the Terahertz Band Based on Linear Chirplet Transform and Empirical Mode Decomposition

Compensation for High-Frequency Vibration of SAR Imaging in the Terahertz Band Based on Linear Chirplet Transform and Empirical Mode Decomposition

High-Resolution SAR Imaging Characteristics for Multiple Scattering of Rotating Targets

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

Contact Info

Product

Resources

About