Terahertz Synthetic Aperture Radar Research Articles

A Two-Step Motion Compensation Method for Polar Format Images of Terahertz SAR Based on Echo Data

A Two-Step Motion Compensation Method for Polar Format Images of Terahertz SAR Based on Echo Data

An Efficient Spectrum Reconstruction Algorithm for Non-Uniformly Sampled Signals and Its Application in Terahertz SAR

An efficient spectrum reconstruction algorithm based on the Tikhonov regularization for terahertz (THz) synthetic aperture radar (SAR) azimuth non-uniform sampling is proposed in this article. The high bandwidth, high azimuth resolution, and high frame rate characteristics of THz SAR contribute to its wide application prospects in both military and civilian remote sensing fields. However, the higher azimuth sampling rate also leads to the more severe non-uniform sampling issues of THz SAR. Traditional methods based on the hardware adjustment of pulse repetition frequency (PRF) and simple interpolation for azimuth resampling struggle to meet the higher imaging quality requirements. The back projection algorithm (BPA) can accurately focus non-uniformly sampled data but requires significant computational resources. The algorithm proposed in this paper, which can reconstruct the wavenumber spectrum of SAR azimuth non-uniformly sampled signals, transforms the spectrum reconstruction problem into a linear equation system and solves it using Tikhonov regularization, thereby exhibiting higher computational efficiency compared to BPA. Furthermore, the proposed algorithm is derived from precise theoretical formulations and controls the solution error by utilizing a regularization parameter, leading to a superior imaging quality compared to the azimuth resampling algorithm. In this paper, an accurate spectrum reconstruction formula of non-uniform sampling signals with a finite length is derived, the influence of noise error on the solution is analyzed, and the THz SAR azimuth non-uniform sampling signals are processed from the wavenumber domain. Finally, simulation and experimental results verify the effectiveness of the proposed algorithm.

Terahertz 3D point cloud imaging for complex targets.

The reconstruction of complex targets using terahertz technology is often hindered by diffraction and interference of electromagnetic waves, leading to the loss of fine target details. In this research article, we have introduced a terahertz synthetic aperture radar (SAR) imaging method that integrates an iterative closest point (ICP) algorithm, referred to as SAR-ICP, to achieve accurate reconstruction of intricate target structures. To accomplish this, multiple sets of point cloud data are acquired by varying the illumination viewpoint. The ICP algorithm is then employed to align and fuse these datasets, resulting in the generation of high-quality three-dimensional (3D) images. The experimental results validate the effectiveness of the proposed SAR-ICP method. The information entropy of the reconstructed 3D image using the SAR-ICP is approximately 0.05 times that of the conventional SAR method, indicating a superior image quality. In the future, we anticipate the widespread application of this method in areas such as security inspection, non-destructive testing, and other complex scenarios.

A Novel 2-D Autofocusing Algorithm for Real Airborne Stripmap Terahertz Synthetic Aperture Radar Imaging

A Novel 2-D Autofocusing Algorithm for Real Airborne Stripmap Terahertz Synthetic Aperture Radar Imaging

Ultra-Wideband Frequency Modulated Continuous Wave Photonic Radar System for Three-Dimensional Terahertz Synthetic Aperture Radar Imaging

Three-dimensional (3D) imaging remains an expensive and challenging task in the THz band. In this study, a frequency-modulated continuous-wave photonic radar system was presented in the 300-GHz band, instead of using electronic-based devices. The proposed system can obtain a 6-dB bandwidth of 120 GHz to achieve a range resolution of ∼1.1 mm. The frequency sweep linearity of a laser source was calibrated with respect to the imaging distance and range resolution, through which a maximum detectable distance of ∼800 mm was achieved with the collimated beam. To obtain the desired 3D information, the synthetic aperture radar (SAR) technique was introduced to the proposed system to achieve 3D imaging, which was not bounded by the fixed focal distance of a focus lens. It can provide a spatial resolution of ∼1.5 mm within a 3D imaging range up to ∼300 mm. The potential and limitations of SAR imaging schemes are discussed based on the theoretical and experimental results.

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

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).

Object Recognition in High-Resolution Indoor THz SAR Mapped Environment.

Synthetic aperture radar (SAR) at the terahertz (THz) spectrum has emerging short-range applications. In comparison to the microwave spectrum, the THz spectrum is limited in propagation range but benefits from high spatial resolution. The THz SAR is of significant interest for several applications which necessitate the mapping of indoor environments to support various endeavors such as rescue missions, map-assisted wireless communications, and household robotics. This paper addresses the augmentation of the high-resolution indoor mapped environment for object recognition, which includes detection, localization, and classification. Indoor object recognition is currently dominated by the usage of optical and infrared (IR) systems. However, it is not widely explored by radar technologies due to the limited spatial resolution at the most commonly used microwave frequencies. However, the THz spectrum provides a new paradigm of possible adaptation of object recognition in the radar domain by providing image quality in good compliance to optical/IR systems. In this paper, a multi-object indoor environment is foremost mapped at the THz spectrum ranging from 325 to 500 GHz in order to investigate the imaging in highly scattered environments and accordingly create a foundation for detection, localization, and classification. Furthermore, the extraction and clustering of features of the mapped environment are conducted for object detection and localization. Finally, the classification of detected objects is addressed with a supervised machine learning-based support vector machine (SVM) model.

Vibration Compensation of Airborne Terahertz SAR Based on Along Track Interferometry

In airborne terahertz synthetic aperture radar (THz-SAR), the phase error caused by high-frequency vibration of the platform can result in not only defocusing, but also the emergence of unwanted ghost targets. To tackle this problem, we propose a vibration estimation and compensation method for the dual-channel THz-SAR based on along-track interferometry (ATI). Compared with the state-of-art single-channel-based compensation methods, the proposed method is advantageous in that it can stay effective without isolated dominant scatter points in the scene. This letter first analyzes the relationship between the along-track interferometric phase of the stationary targets’ echo and the instantaneous radial velocity of the platform’s high-frequency vibration. Then, by using the interferometric phase, the phase error caused by vibration is estimated and compensated. Simulation results show that the proposed method can effectively compensate the phase error caused by multicomponents high-frequency vibration without using the information of dominant scatter points.

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

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).

A High Frequency Vibration Compensation Approach For Terahertz SAR Based on Sinusoidal Frequency Modulation Fourier Transform

In this paper, a vibration estimation method for terahertz synthetic aperture radar (THz SAR) is proposed based on the sinusoidal frequency modulation Fourier transform (SFMFT), which directly operates on the phase term of the signal. Small high frequency vibration of the platform will introduce nonlinear phase modulation in radar echoes. To improve the potential of the method for vibration with multiple vibration frequencies, SFMFT is used to extract the vibration spectrum of the platform. When the vibration amplitude exceeds a certain threshold, the phase ambiguity will occur. To improve the range of estimable vibration amplitude, a method based on the conjugate cancellation of the phase errors with sub-band decomposition is introduced to reconstruct a signal with a longer equivalent wavelength. Then the accurate phase errors caused by the platform vibration can be estimated by performing SFMFT on the composite signal. The simulations prove that the proposed method is superior to the time-frequency (TF) analysis methods and can improve the range of estimable vibration amplitude.

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

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.

Study of Phase Error Reconstruction and Motion Compensation for Terahertz SAR With Sparsity-Promoting Parameter Estimation

In this article, a full aperture phase error reconstruction method upon the single range bin data is proposed based on the sparsity-promoting parameter estimation, for the effective motion compensation of synthetic aperture radar (SAR) in terahertz (THz) band. To improve the potential of the method for different forms of motion errors, the motion errors of the SAR platform are generally modeled as variant phase errors in each azimuth sampling points within the full aperture. A sensing matrix including the contribution of the phase errors is successfully derived to sparsely represent the SAR echo. After range compression, an iterative algorithm based on the single range bin data is developed to efficiently estimate the phase errors by updating the reflectivities of the dominant scatterers and the elements of the sensing matrix. Based on the reconstructed phase errors, the motion compensation can be successfully performed for the THz SAR to obtain the highly focused images. For the proof-of-principle experiments, a vehicle-borne SAR at 0.3-THz band with frequency modulation continuous wave transmitter and dechirp heterodyne receiver is developed. The simulation and the experimental results verify the effectiveness of the proposed method.

Motion Compensation for Terahertz Synthetic Aperture Radar Based on Subaperture Decomposition and Minimum Entropy Theorem

In this paper, a motion compensation method based on subaperture decomposition and minimum entropy theorem is proposed for terahertz (THz) synthetic aperture radar (SAR). The full aperture is decomposed into a series of subapertures and the motion errors of the platform are parameterized with constant azimuth velocity and the radial acceleration in each subaperture. Motion parameters estimation based on the minimization of the image entropy for each subaperture is developed in an iterative fashion. With the estimated motion parameters, the phase errors caused by the non-ideal movement of the platform over the full aperture can be reconstructed, and the compensation of the motion errors can be successfully accomplished for the THz SAR to obtain the well-focused images. Simulation and the experimental results based on a 0.3THz vehicle borne SAR verify the effectiveness of the proposed method for THz SAR motion compensation.

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

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.

Confocal terahertz SAR imaging of hidden objects through rough-surface scattering.

Terahertz (THz) radar imaging has gained great interests in various applications due to its capability of deep penetration in some specific contents such as plastic and non-conductive materials without water. However, the image quality would be highly degraded by the scattering of the rough surfaces, which remains a challenge in the area. Here, we propose a confocal terahertz synthetic aperture radar (SAR) to alleviate the scattering issues with both improved signal-to-noise ratio (SNR) and resolution. Inspired by the confocal non-line-of-sight imaging in visible wavelength, a convex lens is added into the conventional SAR system to localize the effect of scattering within each spatial sampling point by the confocal configuration. Then, the random phase aberration caused by scattering could be corrected through a simple shift in temporal domain. The performance of the proposed method under different roughness occlusions is evaluated through experiments. All the results demonstrate great enhancements in both resolution and SNR over the conventional methods.

Indoor THz SAR Trajectory Deviations Effects and Compensation With Passive Sub-mm Localization System

In radar remote sensing, the Terahertz (THz) spectrum is presently being investigated worldwide with focus on short-range indoor and outdoor applications. The spectrum broadens the unmanned aerial vehicle (UAV) based synthetic aperture radar (SAR) applications to indoor room profiling with sub-mm resolution and material characterization as many materials have unique fingerprints at this spectrum. SAR technique requires precise localization information of the mobile radar sensor, which in conventional SAR is achieved using an existing localization infrastructure, such as a global positioning system (GPS) and inertial measurement unit (IMU). For the indoor THz SAR, the GPS does not provide coverage in indoor complex environments, and also the state-of-art compact IMU does not provide the required sub-mm accuracy. These limitations can be overcome by utilizing an indoor localization system. Therefore, this paper presents an indoor THz simultaneous localization and mapping (SLAM) system. The system comprises of passive tags based radio frequency identification (RFID) localization system and SAR that provides the UAV localization and mapping of the in-room objects. Another challenge for the UAV based indoor THz SAR that is addressed in this paper is motion compensation (MOCO). At the THz, MOCO requires special consideration due to very small trajectory deviation is in the range of carrier wavelength. Therefore, to study the effects of the sub-mm translational errors, a testbed has been set up, and measurement results are presented in this paper along with the 3D electromagnetic simulation results for a carrier frequency of 275 GHz and bandwidth of 50 GHz. Further, to compensate these errors, the sub-mm localization system is used and the results are presented to validate the proposed solution for indoor THz SAR MOCO.

Three-Dimensional Imaging of Terahertz Circular SAR with Sparse Linear Array.

Due to the non-contact detection ability of radar and the harmlessness of terahertz waves to the human body, three-dimensional (3D) imaging using terahertz synthetic aperture radar (SAR) is an efficient method of security detection in public areas. To achieve high-resolution and all aspect imaging, circular trajectory movement of radar and linear sensor array along the height direction were used in this study. However, the short wavelength of terahertz waves makes it practically impossible for the hardware to satisfy the half-wavelength spacing condition to avoid grating lobes. To solve this problem, a sparse linear array model based on the equivalent phase center principle was established. With the designed imaging geometry and corresponding echo signal model, a 3D imaging algorithm was derived. Firstly, the phase-preserving algorithm was adopted to obtain the 2D image of the ground plane for each sensor. Secondly, the sparse recovery method was applied to accomplish the scattering coefficient reconstruction along the height direction. After reconstruction of all the range-azimuth cells was accomplished, the final 3D image was obtained. Numerical simulations and experiments using terahertz radar were performed. The imaging results verify the effectiveness of the 3D imaging algorithm for the proposed model and validate the feasibility of terahertz radar applied in security detection.

Millimeter Wave and Terahertz Synthetic Aperture Radar for Locating Metallic Scatterers Embedded in Scattering Media

A rail-mounted synthetic aperture radar has been constructed to operate at W-band (75-110 GHz) and a terahertz (THz) band (325-500 GHz) in order to ascertain its ability to detect and locate isolated small, visually obscured metallic scatterers embedded in highly scattering dielectric hosts that are either semitransparent or opaque. A “top view” two-dimensional (2-D) algorithm was used to reconstruct scenes from the acquired data, locating metallic scatterers at W-band with high-range and crossrange resolution of 4.3 and 16 mm, respectively, improved to 0.86 and 5 mm at the THz band. Millimeter-sized metallic scatterers were easily located when embedded in semitransparent, highly scattering target hosts of polystyrene and polyethylene packing foam but were more difficult to locate when embedded in relatively opaque, highly scattering polyisocyanurate insulation panels. Although the THz band provided the expected greater spatial resolution, it required the target to be moved closer to the rail and had a more limited field of view that prevented some targets from being identified. Techniques for improving the signal-to-noise ratio are discussed. This paper establishes a path for developing techniques to render a complete 3-D reconstruction of a scene rapidly.

Enhancement of Azimuth Focus Performance in High-Resolution SAR Imaging Based on the Compensation for Sensors Platform Vibration

The high-frequency vibration of radar sensors platform, whose influence is generally negligible in traditional synthetic aperture radar (SAR) imaging, has a significant influence on the high-frequency band, such as the terahertz (THz) band SAR imaging. In this paper, the high-frequency vibration of sensors platform model of THz SAR imaging is established and the effect of it is analyzed. For the vibration of platform can be viewed as a simple harmonic motion, the received signal of THz SAR in each range bin can be considered as sinusoid frequency modulation (SFM) signal. This will cause the images to be defocused in the azimuth processing. A novel algorithm for the parameters estimation of SFM signal based on the discrete sinusoid frequency modulation transform is proposed in this paper, and the simulated annealing algorithm is used to reduce the computational load simultaneously. Then, the phase errors induced by the sensors platform vibration can be compensated by the estimated parameters. The numerical results demonstrate the effectiveness of the novel algorithm proposed in this paper.

Compensation for High-Frequency Vibration of Platform in SAR Imaging Based on Adaptive Chirplet Decomposition

For synthetic aperture radar (SAR) imaging with the high-frequency band, such as the terahertz band, the platform vibration influence cannot be neglected. In general, the vibration of the platform can be viewed as a simple harmonic motion, and thus, the received signal in each range bin can be considered as a sinusoid frequency modulation (SFM) signal for the terahertz SAR imaging. This will introduce the images to be defocused in the azimuth processing. In this letter, a novel algorithm for the analysis of the SFM signal based on the adaptive chirplet decomposition is proposed. This algorithm is accurate, efficient, and easy to be implemented. Then, the high-frequency vibration of the platform can be compensated by the corresponding signal decomposition results. The simulated results demonstrate the effectiveness of the novel algorithm proposed in this letter.