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With the rapidly growing interest in using structural timber, a need exists to inspect and assess these structures using non-destructive testing (NDT). This review article summarizes NDT methods for wood inspection. After an overview of the most important NDT methods currently used, a detailed review of Ground Penetrating Radar (GPR) and Ultrasonic Testing (UST) is presented. These two techniques can be applied in situ and produce useful visual representations for quantitative assessments and damage detection. With its commercial availability and portability, GPR can help rapidly identify critical features such as moisture, voids, and metal connectors in wood structures. UST, which effectively detects deep cracks, delaminations, and variations in ultrasonic wave velocity related to moisture content, complements GPR's capabilities. The non-destructive nature of both techniques preserves the structural integrity of timber, enabling thorough assessments without compromising integrity and durability. Techniques such as the Synthetic Aperture Focusing Technique (SAFT) and Total Focusing Method (TFM) allow for reconstructing images that an inspector can readily interpret for quantitative assessment. The development of new sensors, instruments, and analysis techniques has continued to improve the application of GPR and UST on wood. However, due to the hon-homogeneous anisotropic properties of this complex material, challenges remain to quantify defects and characterize inclusions reliably and accurately. By integrating advanced imaging algorithms that consider the material's complex properties, combining measurements with simulations, and employing machine learning techniques, the implementation and application of GPR and UST imaging and damage detection for wood structures can be further advanced. [ABSTRACT FROM AUTHOR]

Acoustic-resolution photoacoustic micro- scopy (AR-PAM) system can provide 3-D images of facial tissues. The lateral resolution of AR-PAM depends on the numerical aperture (NA) of the acoustic lens and the central frequency of the ultrasonic transducer. There is a trade-off between resolution enhancement and imaging depth. The acoustic beam is tight in the acoustic focal plane but expands in the out-of-focus regions, deteriorating the resolution. High-NA AR-PAM has depth-variant resolution. Synthetic aperture focusing technique (SAFT) based on a virtual detector (VD) concept can compensate for the beam shape and improve the lateral resolution via beamforming. Although, beamforming can enhance the resolution but the lateral resolution in the focal plane is still limited by acoustic diffraction. Structured-illumination can shift the spatial spectrum of an image to low frequencies hence high-frequency contents can be reserved to overcome the diffraction limit. Conventional structured-illumination via using a three-phase-shifting method can improve the resolution by two folds. Here, a modified phase-shifting method is used to generate the second harmonic of the fringes and double the spectral shift. In this idea, higher frequency information compared to the three-phase shifting method can fall into the band-limited system response. The modified phase-shifting method expands the spatial bandwidth and increases the lateral resolution by five folds. The mathematical relations and the theory are discussed in the context. Tungsten filament result shows resolution improvement from 44.6 $\mu \text{m}$ to 11.3 $\mu \text{m}$ by the modified structured illumination. In vivo and ex vivo experimental results validate the system performance. [ABSTRACT FROM AUTHOR]

Speckle or multiplicative noise is a critical issue in coherence-based imaging systems, such as synthetic aperture radar and optical coherence tomography. Existence of speckle noise considerably limits the applicability of such systems by degrading their performance. On the other hand, the sophistications that arise in the study of multiplicative noise have so far impeded theoretical analysis of such imaging systems. As a result, the current acquisition technology relies on heuristic solutions, such as oversampling the signal and converting the problem into a denoising problem with multiplicative noise. This paper attempts to bridge the gap between theory and practice by providing the first theoretical analysis of such systems. To achieve this goal the log-likelihood function corresponding to measurement systems with speckle noise is characterized. Then employing compression codes to model the source structure, for the case of under-sampled measurements, a compression-based maximum likelihood recovery method is proposed. The mean squared error (MSE) performance of the proposed method is characterized and is shown to scale as $O\left({\sqrt {\frac{k \log n }{ m}}}\right)$ , where $k$ , $m$ and $n$ denote the intrinsic dimension of the signal class according to the compression code, the number of observations, and the ambient dimension of the signal, respectively. This result, while in contrast to imaging systems with additive noise in which MSE scales as $O\left({{\frac{k \log n }{ m}}}\right)$ , suggests that if the signal class is structured (i.e., $k \ll n$), accurate recovery of a signal from under-determined measurements is still feasible, even in the presence of speckle noise. Simulation results are presented that suggest image recovery under multiplicative noise is inherently more challenging than additive noise, and that the derived theoretical results are sharp. [ABSTRACT FROM AUTHOR]

Top-orthogonal-to-bottom electrode (TOBE) arrays, also known as row–column arrays, have shown great promise as an alternative to fully wired 2-D arrays, owing to a considerable reduction in channels. Novel imaging schemes with bias-switchable TOBE arrays were previously shown to offer promise compared with previous nonbias-switchable row–column imaging schemes and compared with previously developed explososcan methods, however, they required significant coherent compounding. Here, we introduce ultrafast orthogonal row–column electronic scanning (uFORCES), an ultrafast coded synthetic aperture imaging method. Unlike its FORCES predecessor, uFORCES can achieve coherent compounding with only a few transmit events and may, thus, be more robust to tissue motion. We demonstrate through simulations that uFORCES can potentially offer improved resolution compared with the matrix probes having beamformers constrained by the paraxial approximation. Also, unlike current matrix probe technology incorporating microbeamforming, uFORCES with bias-switchable TOBE arrays can achieve ultrafast imaging at thousands of frames per second using only row and column addressing. We also demonstrate the experimental implementation of uFORCES using a fabricated $128 \times 128$ electrostrictive TOBE array on a crossed 25- $\mu \text{m}$ gold wire phantom and a tissue-mimicking phantom. The potential for improved resolution and ultrafast imaging with uFORCES could enable new essential imaging capabilities for clinical and preclinical ultrasound. [ABSTRACT FROM AUTHOR]

Row–column (RC) arrays have the potential to yield full 3-D ultrasound imaging with a greatly reduced number of elements compared to fully populated arrays. They, however, have several challenges due to their special geometry. This review article summarizes the current literature for RC imaging and demonstrates that full anatomic and functional imaging can attain a high quality using synthetic aperture (SA) sequences and modified delay-and-sum beamforming. Resolution can approach the diffraction limit with an isotropic resolution of half a wavelength with low sidelobe levels, and the field of view can be expanded by using convex or lensed RC probes. GPU beamforming allows for three orthogonal planes to be beamformed at 30 Hz, providing near real-time imaging ideal for positioning the probe and improving the operator’s workflow. Functional imaging is also attainable using transverse oscillation and dedicated SA sequence for tensor velocity imaging for revealing the full 3-D velocity vector as a function of spatial position and time for both blood velocity and tissue motion estimation. Using RC arrays with commercial contrast agents can reveal super-resolution imaging (SRI) with isotropic resolution below $20~ \mu \text{m}$. RC arrays can, thus, yield full 3-D imaging at high resolution, contrast, and volumetric rates for both anatomic and functional imaging with the same number of receive channels as current commercial 1-D arrays. [ABSTRACT FROM AUTHOR]

In a recent study, we proposed a technique to correct aberration caused by the skull and reconstruct a transcranial B-mode image with a refraction-corrected synthetic aperture imaging (SAI) scheme. Given a sound speed map, the arrival times were calculated using a fast marching technique (FMT), which solves the Eikonal equation and, therefore, is computationally expensive for real-time imaging. In this article, we introduce a two-point ray tracing method, based on Fermat’s principle, for fast calculation of the travel times in the presence of a layered aberrator in front of the ultrasound probe. The ray tracing method along with the reconstruction technique is implemented on a graphical processing unite (GPU). The point spread function (PSF) in a wire phantom image reconstructed with the FMT and the GPU implementation was studied with numerical synthetic data and experiments with a bone-mimicking plate and a sagittally cut human skull. The numerical analysis showed that the error on travel times is less than 10% of the ultrasound temporal period at 2.5 MHz. As a result, the lateral resolution was not significantly degraded compared with images reconstructed with FMT-calculated travel times. The results using the synthetic, bone-mimicking plate, and skull dataset showed that the GPU implementation causes a lateral/axial localization error of 0.10/0.20, 0.15/0.13, and 0.26/0.32 mm compared with a reference measurement (no aberrator in front of the ultrasound probe), respectively. For an imaging depth of 70 mm, the proposed GPU implementation allows reconstructing 19 frames/s with full synthetic aperture (96 transmission events) and 32 frames/s with multiangle plane wave imaging schemes (with 11 steering angles) for a pixel size of $200~\mu \text{m}$. Finally, refraction-corrected power Doppler imaging is demonstrated with a string phantom and a bone-mimicking plate placed between the probe and the moving string. The proposed approach achieves a suitable frame rate for clinical scanning while maintaining the image quality. [ABSTRACT FROM AUTHOR]

Objective: Two-dimensional (2D) photoacoustic (PA) imaging based on array transducers provide high spatial resolution in the lateral direction by adopting receive dynamic focusing. However, the quality of PA image is often deteriorated by poor elevational resolution which is achieved by an acoustic lens. To overcome this limitation, we present a three-dimensional (3D) image reconstruction method using a commercial one-dimensional (1D) array transducer. Methods: In the method, the elevational resolution is improved by applying synthetic aperture focusing (SAF) technique along the elevational direction. For this, a commercially available 1D array transducer with an acoustic lens is modeled and appropriate synthetic focusing delay that can minimize the effect of the acoustic lens is derived by mathematical analysis. Results: From the simulation and experiment results, it was demonstrated that the proposed method can enhance the image quality of PA imaging, i.e., elevational resolution and signal-to-noise ratio (SNR). Conclusion: 3D PA images with improved elevational resolution were achieved using a clinical 1D array transducer. Significance: The presented method may be useful for clinical application such as detecting microcalcification, imaging of tumor vasculature and guidance of biopsy in real time. [ABSTRACT FROM AUTHOR]

Microwave photonic synthetic aperture radar (MWP-SAR) offers a larger signal bandwidth than conventional SAR, and its theoretical resolution can be improved to centimeter level. To achieve same order of magnitude resolution in the azimuth direction, long synthetic aperture is always required, which results in extremely high requirements for the accuracy of imaging procedure. Compared with the conventional SAR imaging algorithms, two major problems should be considered: 1) the scattering characteristics of target might vary from the frequency of signal and the angle of incidence, which seriously affects the coherence of received echo and 2) the imaging of the MWP-SAR system is more sensitive to motion errors and therefore requires higher accuracy of motion compensation processing. To solve the above issues, a high-precision imaging method for MWP-SAR is proposed. First, based on the attribute scattering center (ASC) model, this article analyzes the target scattering characteristics with different frequencies and incident angles. Then, according to the influence of scattering phase on MWP-SAR imaging, an optimal subaperture division algorithm is proposed to guarantee the coherence of each subaperture data and better imaging results. Furthermore, to compensate for the effects of high-order motion errors, this article proposes a motion error estimation algorithm based on subimage registration, where the full-aperture high-order motion errors can be divided into multiple linear components, and the flight trajectory of platform can be accurately reconstructed. Finally, a full-aperture time-domain high-precision imaging method is presented, and the effectiveness of the proposed formation is verified by both simulation and actual airborne MWP-SAR data processing. [ABSTRACT FROM AUTHOR]

The 3-D ultrasound (US) imaging addresses the limitation in field-of-view (FOV) in conventional 2-D US imaging by providing 3-D viewing of the anatomy. The 3-D US imaging has been extensively adapted for diagnosis and image-guided surgical intervention. However, conventional approaches to implement 3-D US imaging require either expensive and sophisticated 2-D array transducers or external actuation mechanisms to move a 1-D array mechanically. Here, we propose a 3-D US imaging mechanism using an actuated acoustic reflector instead of the sensor elements for volume acquisition with significantly extended 3-D FOV, which can be implemented with simple hardware and compact size. To improve image quality on the elevation plane, we implemented the synthetic aperture focusing (SAF) method according to the diagonal geometry of the virtual element array in the proposed imaging mechanism for elevation beamforming. We first evaluated the proposed imaging mechanism and SAF with simulated point targets and cyst targets. The results of point targets suggested improved image quality on the elevation plane, and the results of cysts targets demonstrated a potential to improve 3-D visualization of human anatomy. We built a prototype imaging system with a 3-D FOV of 38 mm (lateral) by 38 mm (elevation) by 50 mm (axial) and collected data in imaging experiments with phantoms. Experimental data showed consistency with simulation results. The SAF method enhanced quantifying the cyst volume size in the breast mimicking phantom compared with no elevation beamforming. These results suggested that the proposed 3-D US imaging mechanism could potentially be applied in clinical scenarios. [ABSTRACT FROM AUTHOR]

For the near-field synthetic aperture interferometric radiometer (SAIR), the Fourier transform relationship between the visibility function and the near-field brightness temperature (BT) distribution is not valid. It is a challenging task for near-field SAIR imaging to realize very close-range accurate imaging with a large field of view (FOV). This article presents a new SAIR near-field imaging algorithm based on the angular spectrum theory to realize the passive millimeter-wave (PMMW) imaging, called synthetic-angular-spectrum imaging (SASI) algorithm. This SASI algorithm mainly addresses data samples of a 4-D visibility function acquired from planar arrays. First, we invert 4-D visibility samples into the angular spectrum domain via the Fourier transformation. The obtained angular spectrum data cannot be directly used to estimate the near-field BT distribution. Second, a dedicated phase factor compensation is adopted for handling this problem. The dimension-reducing accumulation is employed to generate the synthetic angular spectrum (SAS) of near-field BT distribution. Finally, we reconstruct the BT image by using the generated SAS data. Simulation and experiment results show that the presented SASI algorithm has the superiority on image reconstruction quality, especially for the off-axis regions, compared with the existing near-field SAIR imaging methods. [ABSTRACT FROM AUTHOR]

In this study, we propose a generalized algorithm for far-field radar cross section determination by using 3-D synthetic aperture imaging with arbitrary antenna-scanning surfaces. This method belongs to a class of techniques called image-based near-field-to-far-field transformation. The previous image-based approaches have been formulated based on a specific antenna-scanning trajectory or surface, such as a line, plane, circle, cylinder, and sphere; the majority of these approaches consider 2-D radar images to determine the azimuth radar cross section. We generalize the conventional image-based technique to accommodate an arbitrary antenna-scanning surface and consider a 3-D radar image for radar cross section prediction in both the azimuth and zenith directions. We validate the proposed algorithm by performing numerical simulations and anechoic chamber measurements. [ABSTRACT FROM AUTHOR]

This article proposes a new synthetic aperture radar (SAR), named as panoramic SAR, based on a combination of linear and rotational SARs, by which a large 360° panoramic view of the observed scene can be reconstructed. First, the system geometry and its imaging process based on the back-projection algorithm (BPA) are presented. The combined movement constitutes a 2-D synthetic aperture, and thus higher imaging resolutions can be obtained. The corresponding resolution analysis and the sampling criteria are discussed accordingly. Then, a novel dynamic piecewise compensation (DPC) algorithm, a recursive imaging process, is proposed to reduce the processing complexity significantly. The imaging implementation and the complexity are also studied respectively. Finally, a prototype of panoramic SAR is built based on an frequency-modulated continuous wave (FMCW) radar and a moving platform, and the simulation and experimental results are provided to validate the proposed panoramic SAR principle and the DPC algorithm. [ABSTRACT FROM AUTHOR]

A 360° video synthetic aperture radar (VideoSAR) appears as an interactive observation capability to understand the dynamic scenarios. VideoSAR system mounted on an unmanned aerial vehicle (UAV) delivers a highly flexible and cost-effective approach. In this letter, the UAV-borne repeat-pass circular stripmap (CSM) VideoSAR observation is formulated in the format of video area overflown to enhance the wide-area surveillance capability. A completely two-dimensional interpolation-free polar format algorithm is employed, especially in terms of repeat-pass CSM-VideoSAR configuration. We conduct the repeat-pass CSM-VideoSAR experiments on multirotor UAV-borne system in the interests of imaging demonstration and promoting the inspirations on the related open issues. [ABSTRACT FROM AUTHOR]

High-frequency endoscopic ultrasound (HFEUS) imaging is an important tool commonly used in clinical practice for imaging hollow organs. The virtual source synthetic aperture (VSSA) method is effective in improving the imaging quality of HFEUS. However, interference from the motor control unit severely affects the accuracy of the conventional delay and sum (DAS) method, thus compromising the effectiveness of VSSA. In this article, a new computational method based on phase correction was proposed to overcome these shortcomings, which is named phase-corrected-and-sum (PCAS). Meanwhile, the parameters of coherence factor weighting (CFW) can be obtained from the correlation coefficient of the superimposed signals to further increase the imaging quality. Three kinds of imaging experiments were designed to evaluate the proposed method. Compared with the conventional method, the results show that the PCAS-CFW method improves the lateral resolution by about 10% and the contrast-to-noise ratio (CNR) by about 44%. Therefore, this proposed method is capable of significantly improving HFEUS image quality, and this method can be easily integrated into current HFEUS imaging systems, showing great potential for clinical applications. [ABSTRACT FROM AUTHOR]

Synthetic aperture radar (SAR) can provide high-resolution electromagnetic backscattering images of the illuminated area, playing a significant role in various applications. However, achieving focused SAR images is challenging under sparse sampling and phase error conditions. By exploiting the sparsity or compressibility priors, the state-of-the-art sparsity-driven SAR imaging methods can reconstruct images under the condition of sparse sampling. However, the handcrafted priors used in these methods limit the imaging performance, and the iterative solution schemes reduce the computational efficiency. Besides, the measurement inaccuracy introduced by the phase error also degrades the reconstruction performance of the sparsity-driven imaging methods. To address these issues, a deep network for SAR autofocus imaging is proposed, which alternately performs image reconstruction and phase error estimation. When performing image reconstruction, the sparsity-cognizant total least-square (S-TLS) model is introduced to handle the problem of measurement inaccuracy, contributing to robust reconstruction performance under the condition of phase error. During the implementation of the deep network, a feature transform operator is used to realize data-driven prior knowledge learning and overcome the limitations of handcrafted priors. Moreover, the deep network approach can significantly improve computational efficiency. Experiments on simulated and real data verify the effectiveness and efficiency of the proposed method. [ABSTRACT FROM AUTHOR]

Due to the significant acoustic impedance contrast at cortical boundaries, highly inside attenuation, and the unknown sound velocity distribution, accurate ultrasound cortical bone imaging remains a challenge, especially for the traditional pulse-echo modalities using unique sound velocity. Moreover, the large amounts of data recorded by multielement probe results in a relatively time-consuming reconstruction process. To overcome these limitations, this article proposed an index-rotated fast ultrasound imaging method based on predicted velocity model (IR-FUI-VP) for cortical cross section ultrasound tomography (UST) imaging, utilizing ray-tracing synthetic aperture (RTSA). In virtue of ring probe, the sound velocity model was predicted in advance using bent-ray inversion (BRI). With the predicted velocity model, index-rotated fast ultrasound imaging (IR-FUI) was further applied to image the cortical cross sections in the sectors corresponding to the dynamic apertures (DAs) and ring center. The final result was merged by all sector images. One cortical bone phantom and two ex vivo bovine femurs were utilized to demonstrate the performance of the proposed method. Compared to the conventional synthetic aperture (SA) imaging, the method can not only accurately image the outer cortical boundary but also precisely reconstruct the inner cortical surface. The mean relative errors of the predicted sound velocity in the region of interest (ROI) were all smaller than 7%, and the mean errors of cortical thickness are all less than 0.31 mm. The reconstructed images of bovine femurs were in good agreement with the reference images scanned by micro-computed tomography ($\mu $ CT) with respect to the morphology and thickness. The speed of IR-FUI is about 3.73 times faster than the traditional SA. It is proved that the proposed IR-FUI-VP-based UST is an effective way for fast and accurate cortical bone imaging. [ABSTRACT FROM AUTHOR]

Arc-synthetic aperture radar (ArcSAR) can observe the surrounding ground objects at 360°, with the advantages of a wide imaging range and constant azimuth angular resolution. In this article, based on the stepped frequency continuous wave (SFCW), fourth-order Taylor expansion, and the series-inversion method, the accurate phase expression of the 2-D spectrum is derived, and then, the 2-D frequency-domain imaging algorithm (2-D-FDA) for ArcSAR is realized. In the simulation part, the imaging results of 2-D-FDA are compared with the backprojection algorithm (BPA) and Liao’s method, which is the reference for 2-D-FDA. The simulation results show that the 2-D-FDA is more applicable to process the data obtained from the antenna with the beamwidth larger than 70°. The SFCW-ArcSAR system consists of a vector network analyzer (VNA), a rotating platform, two antennas, and a control computer. Then, the system is used for the outdoor experiment. The experimental results of the corner reflector show that the point target analysis of 2-D-FDA is consistent with those of the BPA and theory. Under the system parameters in this article, the measured azimuth angular resolution is 0.0177 radian, the peak sidelobe ratio (PSLR) in the range direction is −12.46 dB, and the range resolution is 0.48 m on the ground-range plane. The imaging results of the real scenario processed by BPA and 2-D-FDA are consistent, and the ArcSAR image agrees with the optical image of the experimental scene. The effectiveness and correctness of the 2-D-FDA are verified by simulation and experiment. [ABSTRACT FROM AUTHOR]

Transcranial ultrasound imaging (TUI) is a diagnostic modality with numerous applications, but unfortunately, it is hindered by phase aberration caused by the skull. In this article, we propose to reconstruct a transcranial B-mode image with a refraction-corrected synthetic aperture imaging (SAI) scheme. First, the compressional sound velocity of the aberrator (i.e., the skull) is estimated using the bidirectional headwave technique. The medium is described with four layers (i.e., lens, water, skull, and water), and a fast marching method calculates the travel times between individual array elements and image pixels. Finally, a delay-and-sum algorithm is used for image reconstruction with coherent compounding. The point spread function (PSF) in a wire phantom image and reconstructed with the conventional technique (using a constant sound speed throughout the medium), and the proposed method was quantified with numerical synthetic data and experiments with a bone-mimicking plate and a human skull, compared with the PSF achieved in a ground truth image of the medium without the aberrator (i.e., the bone plate or skull). A phased-array transducer (P4-1, ATL/Philips, 2.5 MHz, 96 elements, pitch $=$ 0.295 mm) was used for the experiments. The results with the synthetic signals, the bone-mimicking plate, and the skull indicated that the proposed method reconstructs the scatterers with an average lateral/axial localization error of 0.06/0.14 mm, 0.11/0.13 mm, and 1.0/0.32 mm, respectively. With the human skull, an average contrast ratio (CR) and full-width-half-maximum (FWHM) of 37.1 dB and 1.75 mm were obtained with the proposed approach, respectively. This corresponds to an improvement of CR and FWHM by 7.1 dB and 36% compared with the conventional method, respectively. These numbers were 12.7 dB and 41% with the bone-mimicking plate. [ABSTRACT FROM AUTHOR]

Lateral motion estimation has been a challenge in ultrasound elastography mainly due to the low resolution, low sampling frequency, and lack of phase information in the lateral direction. Synthetic transmit aperture (STA) can achieve high resolution due to two-way focusing and can beamform high-density image lines for improved lateral motion estimation with the disadvantages of low signal-to-noise ratio (SNR) and limited penetration depth. In this study, Hadamard-encoded STA (Hadamard-STA) is proposed for the improvement of lateral motion estimation in elastography, and it is compared with STA and conventional focused wave (CFW) imaging. Simulations, phantom, and in vivo experiments were conducted to make the comparison. The normalized root mean square error (NRMSE) and the contrast-to-noise ratio (CNR) were calculated as the evaluation criteria in the simulations. The results show that, at a noise level of −10 dB and an applied strain of −1% (compression), Hadamard-STA decreases the NRMSEs of lateral displacements by 46.92% and 35.35%, decreases the NRMSEs of lateral strains by 52.34% and 39.75%, and increases the CNRs by 9.70 and 9.75 dB compared with STA and CFW, respectively. In the phantom experiments performed on a heterogeneous tissue-mimicking phantom, the sum of squared differences (SSD) between the reference and the motion-compensated RF data, and the CNR were calculated as the evaluation criteria. At an applied strain of −1.80%, Hadamard-STA is found to decrease the SSDs by 20.91% and 30.99% and increase the CNRs by 14.15 and 24.66 dB compared with STA and CFW, respectively. In the experiments performed on a breast phantom, Hadamard-STA achieves better visualization of the breast inclusion with a clearer boundary between the inclusion and the background than STA and CFW. The in vivo experiments were performed on a patient with a breast tumor, and the tumor could also be better visualized with a more homogeneous background in the strain image obtained by Hadamard-STA than by STA and CFW. These results demonstrate that Hadamard-STA achieves a substantial improvement in lateral motion estimation and maybe a competitive method for quasi-static elastography. [ABSTRACT FROM AUTHOR]

Ultrafast ultrasound (US) revolutionized biomedical imaging with its capability of acquiring full-view frames at over 1 kHz, unlocking breakthrough modalities such as shear-wave elastography and functional US neuroimaging. Yet, it suffers from strong diffraction artifacts, mainly caused by grating lobes, sidelobes, or edge waves. Multiple acquisitions are typically required to obtain a sufficient image quality, at the cost of a reduced frame rate. To answer the increasing demand for high-quality imaging from single unfocused acquisitions, we propose a two-step convolutional neural network (CNN)-based image reconstruction method, compatible with real-time imaging. A low-quality estimate is obtained by means of a backprojection-based operation, akin to conventional delay-and-sum beamforming, from which a high-quality image is restored using a residual CNN with multiscale and multichannel filtering properties, trained specifically to remove the diffraction artifacts inherent to ultrafast US imaging. To account for both the high dynamic range and the oscillating properties of radio frequency US images, we introduce the mean signed logarithmic absolute error (MSLAE) as a training loss function. Experiments were conducted with a linear transducer array, in single plane-wave (PW) imaging. Trainings were performed on a simulated dataset, crafted to contain a wide diversity of structures and echogenicities. Extensive numerical evaluations demonstrate that the proposed approach can reconstruct images from single PWs with a quality similar to that of gold-standard synthetic aperture imaging, on a dynamic range in excess of 60 dB. In vitro and in vivo experiments show that trainings carried out on simulated data perform well in experimental settings. [ABSTRACT FROM AUTHOR]

Aiming at the problems of low resolution and poor noise suppression for maneuvering targets with traditional inverse synthetic aperture radar (ISAR) imaging algorithms, we propose a motion compensation-driven high-resolution imaging algorithm based on Fourier ptychographic microscopy (FPM) technology. FPM is a phase retrieval technology that uses the concept of synthetic aperture to obtain the high-resolution image of the target. The process of FPM imaging is composed of the enhancement of the known target information in the spatial domain and some fixed restricted alternating iteration in the frequency domain. This article analyzes the mathematical model of maneuvering target echo and then studies the rationality of applying the FPM phase retrieval algorithm to ISAR maneuvering target imaging. The proposed algorithm mainly includes two steps. First, a series of low-resolution ISAR images are generated by sampling echo data through an aperture function. Second, the FPM phase retrieval technology is applied to splice and reconstruct the spectrum of the low-resolution images to achieve the focused ISAR image. The effectiveness of the proposed algorithm is verified by using multiple groups of simulation data and real radar data. [ABSTRACT FROM AUTHOR]

In theory, coherent plane-wave compounding (CPWC) enables ultrafast ultrasound imaging while maintaining a high imaging quality that is comparable to conventional B-mode imaging based on focused beam transmissions. However, in practice, due to the imperfect synthetization of transmit focusing (e.g., heterogeneous speed of sound in tissue and limited range of steering angle), CPWC suffers from a variety of imaging artifacts resulting from side lobes, grating lobes, and axial lobes. This study focuses on addressing the issues of axial lobes for CPWC, which constitutes an important source of clutter that leads to the degradation of contrast ratio and contrast-to-noise ratio (CR and CNR) of CPWC. We first investigated the source of the axial lobes based on plane-wave propagation and the delay-and-sum (DAS) beamforming. We then proposed a new method that is based on pixel-oriented adaptive apodization (POAA) to eliminate the axial lobes throughout the entire field of view (FOV). POAA was first validated in a simulation study, followed by in vitro phantom experiments and an in vivo case study on a carotid artery from a healthy volunteer. In the simulation study, suppression of axial lobes by 120 dB was observed from wire targets, and an improvement of CNR by up to 60% was found in a cyst-mimicking digital phantom. In the phantom experiment, POAA showed an improvement in CNR by around 20% over conventional methods. The effectiveness of axial lobe suppression was finally demonstrated in vivo, where POAA showed a substantial suppression of clutters throughout the entire FOV. [ABSTRACT FROM AUTHOR]

Multinode remote sensing imaging loads have long been a fascinating focus of aerial earth observation applications, where the load denotes the device or equipment located on the aircraft for a specific task, such as aerial camera, scanning laser, and synthetic aperture radar. In order to guarantee high-quality imaging, distributed position and orientation system (POS) serves as high accuracy spatio-temporal reference information for remote sensing loads to realize motion compensation. As a result of the working environment, the flexible structure of the wing will suffer the external disturbance, then for distributed POS, the lever arm between the master system below the abdomen and slave system under the wing is time-varying, also the noise disturbance influences markedly on the motion parameters measurement accuracy. Then aiming at the transfer alignment accuracy improvement of distributed POS, a central difference $H_{\infty }$ filtering algorithm is proposed, which adopts the central difference Kalman filtering to realize nonlinear state estimation and $H_\infty $ filtering to suppress the disturbance influence on estimation, then the high accuracy motion parameters can be obtained. The flight test results show that the developed algorithm can effectively deal with the disturbance influence on transfer alignment estimation and enhance the parameter estimation accuracy, which can be used in aerial earth observation imaging. [ABSTRACT FROM AUTHOR]

High-resolution wide-swath synthetic aperture radar (HRWS-SAR) imaging is highly desirable since it allows one to produce high-resolution SAR images of large areas during a short visit time. In this article, staggered coprime pulse repetition frequencies synthetic aperture radar (SCopSAR) is proposed. It divides the time during which a scatterer is illuminated by the antenna beam pattern into two halves where, in each half, pulses are transmitted at the rate of one of two sub-Nyquist pulse repetition frequencies (PRFs). Such PRFs are related to the Nyquist PRF using two coprime subsampling factors. This allows extending the maximum range swath width that can be imaged by a number of times that equals the smaller subsampling factor at the expense of a reduction in the azimuth resolution by half. It further allows for a reduction in the amount of data to be stored and communicated. SCopSAR is an imaging modality suitable for scenes that contain a small number of bright scatterers over a dark background which, for instance, is the case when imaging ships in a calm sea background. Compared with the techniques recently proposed in the literature, SCopSAR simplifies the radar requirements since it uses only one carrier frequency, one waveform, and one channel. Simulations and real ERS-2 satellite raw data are used to validate the theoretical findings presented in this article. [ABSTRACT FROM AUTHOR]

Arc synthetic aperture radar (ArcSAR) is a ground-based remote imaging technology with the ability to cover wide fields of view. However, because its azimuth is formed by scanning angle rotation, the focusing of ArcSAR images is different from classical SAR focusing. Since the existing imaging methods cannot give a good balance between computational efficiency and accuracy, the wavenumber domain algorithm (WMA) could become an interesting alternative. Due to the fact that in ArcSAR imaging, the slant range measurement depends on a sine term of the scanning angle, no dedicated WMA-based approach for ArcSAR imaging has been formulated yet. The main challenge in this context is that the solution of the stationary phase point cannot be resolved explicitly via Fourier transform (FT). This article proposes a new wavenumber domain imaging method, which exploits the sine law in the process of solving the stationary phase point during FT along the direction of the received echo using the triangular relationship formed by the target, the radar, and the rotation center of radar and then obtains the exact phase error expression in range and angular wavenumber domain without any approximation of the slant range or scanning angle. Using this formulation, we develop the corresponding phase error compensation method and complete image focusing. Through point target simulation and experiments on real ArcSAR data, the effectiveness of this method is verified in terms of imaging accuracy and computational efficiency. [ABSTRACT FROM AUTHOR]

This article presents an universal circular synthetic aperture radar (SAR) (UCSAR) by which the targets to be observed at any radial distance can be imaged, thus making SAR imaging possible in a more general scenario with a circular movement of the radar platform. The UCSAR point spread function (PSF) is firstly analyzed based on the time-domain correlation imaging approach, and thus a three-dimension (3-D) spatial variant PSF of the target can be formulated. The closed-form PSF expressions with single-frequency and frequency-modulated continuous wave (FMCW) transmitted signals are derived respectively to quantify the imaging resolutions, showing that the PSF is a product of a sinc function and a zeroth-order Bessel function when using a wideband FMCW signal. Secondly, a fast UCSAR imaging algorithm and its further simplified version are proposed to reduce the computational cost significantly based on the piecewise constant Doppler (PCD) principle. To quantify the imaging performance, we derive an error function of the slant range approximation for the proposed algorithm, serving as a practical guideline for the UCSAR parameter selection. Finally, the simulation and experimental results are provided to validate the PSF analysis, the fast imaging algorithm, and the implementation of the proposed UCSAR. [ABSTRACT FROM AUTHOR]

This article proposes an advanced THz multiple-input-multiple-output (MIMO) near-field sparse imaging scheme for target detection that uses single-pass synthetic aperture focusing and multipass interferometric synthetic aperture focusing techniques to improve imaging effectiveness and efficiency. It benefits from the MIMO of the linear sparse periodic array (SPA) and random undersampling sparse imaging to reduce sampling data and system cost. Both simulated and proof-of-concept experimental results have verified the scheme, revealing that the single-pass synthetic aperture imaging approach is sufficient to identify pure metallic targets with 3.87% of $\lambda /2$ sampling data. The multipass interferometric synthetic aperture imaging approach is capable of improving image quality on the image signal-to-noise ratio (SNR) and contrast, which is ideal for detecting more challenging targets. The random sparse imaging with help of the low-rank matrix completion (LRMC) technique has shown the promising potential of achieving equivalent image quality when further reducing 43.75% data in the experiment of five-pass imaging on a complex target; this corresponds to 82.51% data reduction compared to $\lambda /2$ sampling. [ABSTRACT FROM AUTHOR]

Objectives：Traditional echo simulator of synthetic aperture sonar (SAS) is based on the assumption that transmitter and receiver beam patterns are rectangle within mainlobe, which is determined by 3 dB beamwidth of beam pattern. This neglects the echo signal outside the mainlobe. Besides, the modulation of transmitter and receiver beam patterns is not considered. Methods：Depending on the instantaneous geometry relationship among transmitter, receiver and target, the echo simulation of SAS considering the modulation of transmitter and receiver beam patterns is carried out. Then, the influence of transmitter and receiver beam patterns on SAS imaging is discussed by the back projection algorithm. Results and Conslusions: Traditional array signal processing based on weighting is further conducted to show the influence of transmitter and receiver beam patterns on imaging results. The results are useful for the suppression of spectrum alias in the azimuth direction. Moreover, they are also helpful for the simulation verification and analysis of performance parameters of designed SAS systems. [ABSTRACT FROM AUTHOR]

In this article, a novel 2-D scanning synthetic aperture radar mode for high-resolution and wide-swath imaging is introduced. Instead of the interpulse progressive azimuth beam scanning used in Terrain Observation by Progressive Scans (TOPS) mode, the intrapulse continuous azimuth frequency scanning is employed in this mode. The same azimuth resolution as the multichannel TOPS mode can be obtained through this mode in the case of single channel transmitting and receiving. And the wide-swath imaging in range is still achieved through the cyclically elevation beam scanning from burst to burst. Moreover, the antenna aperture can be fully exploited for transmitting in this mode. Therefore, it will outperform the multichannel TOPS mode especially in the case of active array antenna. The signal model of this mode is derived. Based on the analysis of the characteristics of echo spectrum, the design criteria for this mode are developed, followed by a design example. Finally, an imaging algorithm for this mode is presented. Theoretical analysis and numerical simulations verify the effectiveness of the proposed design criteria and imaging algorithm. [ABSTRACT FROM AUTHOR]

In the actual scene of interferometric inverse synthetic aperture radar (InISAR) imaging, the noncooperative targets may make a nonuniform 3-D rotational motion (3-D-RM), which contributes not only to the time-variant Doppler modulation but also to the spatial-variant wave path difference (SVWPD). This, in turn, seriously degrades the 3-D geometry reconstruction accuracy of the targets. Furthermore, it is an enormous challenge to realize InISAR imaging from sparse frequency band and sparse aperture (SFB-SA) signals. This article seeks to address the problems of fine image registration and 2-D joint sparse reconstruction (2-D-JSR) for InISAR imaging with SFB-SA signals. With regard to the maneuvering targets with 3-D-RM, a novel SVWPD signal model is established. Moreover, a new algorithm, named joint wave path difference compensation (JWPDC) algorithm, is developed to perform fine image registration. It can not only combine multiple channels to achieve image registration but also jointly compensate for the non-SVWPD (NSVWPD) and SVWPD. A joint multichannel 2-D-JSR (JMC-2-D-JSR) ISAR imaging algorithm is also proposed according to the SFB-SA signal model to produce high-resolution ISAR images. Underpinned by the Bayesian compressive sensing (BCS) theory, the JMC-2-D-JSR ISAR imaging can be realized by solving a sparsity-driven optimization problem via a modified quasi-Newton solver. Through iterative processing of JMC-2-D-JSR and JWPDC, the high-quality 3-D InISAR images of maneuvering targets with 3-D-RM can be obtained. Extensive experimental results based on both simulated and real data corroborate the effectiveness of the proposed algorithm that outperforms other available InISAR imaging frameworks in 2-D imaging, 3-D imaging, and motion compensation. [ABSTRACT FROM AUTHOR]

Synthetic aperture (SA) beamforming is a principal technology of modern medical ultrasound imaging. In that the use of focused transmission provides superior signal-to-noise ratio (SNR) and is promising for cardiovascular diagnosis at the maximum imaging depth of about 160 mm. But there is a pitfall in increasing the frame rate to more than 80 frames per second (frames/s) without image degradation by the haze artifact produced when the transmit foci (SA virtual sources) placed within the imaging field. We hypothesize that the source of this artifact is a grating lobe caused by coarse (decimated) multiple transmission and manifesting in the low brightness region in the accelerated-frame-rate images. We propose an intertransmission coherence factor (ITCF) method suppressing haze artifacts caused by coarse-pitch multiple transmission. The method is expected to suppress the image blurring because the SA grating lobe signal is less coherent than the main lobe signals. We evaluated an ITCF algorithm for suppressing the grating artifact when the transmission pitch is up to four times larger than the normal pitch (equivalent to 160 frames/s). In in-vitro and in-vivo experiments, we demonstrated the strong relation of haze artifact with the grating lobe due to the coarse-pitch transmission. Then, we confirmed that the ITCF method suppresses the haze artifact of a human heart by 15 dB while preserving the spatial resolution. The ITCF method combined with focused transmission SA beamforming is a valid method for getting cardiovascular ultrasound B-mode images without making a compromise in the trade-off relationship between the frame rate and the SNR. [ABSTRACT FROM AUTHOR]

Radar imaging using the synthetic aperture radar (SAR) principle is a common method to obtain information about e.g., the surface of a target. However, most image formation algorithms for such systems assume (quasi-)static measurements. This may lead to errors in the processed images if the sensor is moving during the measurement process. This is especially the case for frequency-modulated continuous-wave (FMCW)-based sensors since the signal duration is longer than in a pulsed system and the achievable bandwidth is much larger and introduces additional challenges. Motion compensation in the context of radar imaging is usually related to the correction of deviations from an ideal trajectory. In contrast, this article presents a method to take the sensor movement during a single FMCW ramp into account and therefore addresses the effects caused by a continuous path during the transmit/receive process. Hence, faster movement can be achieved during the scanning of the synthetic aperture without being bound by stop-and-go approximations. In addition, it will be shown that the algorithm is suitable to reduce systematic errors due to aliasing caused by spatial sampling below the Nyquist rate. For this purpose, this article presents simulations and measurement results, obtained by an ultrawideband $D$ -band FMCW radar operating between 122 and 170 GHz. [ABSTRACT FROM AUTHOR]

Two-way dynamic focusing in synthetic transmit aperture (STA) beamforming can benefit high-quality ultrasound imaging with higher lateral spatial resolution and contrast resolution. However, STA requires the complete dataset for beamforming in a relatively low frame rate and transmit power. This paper proposes a deep-learning architecture to achieve high frame rate STA imaging with two-way dynamic focusing. The network consists of an encoder and a joint decoder. The encoder trains a set of binary weights as the apodizations of the high-frame-rate plane wave transmissions. In this respect, we term our network ApodNet. The decoder can recover the complete dataset from the acquired channel data to achieve dynamic transmit focusing. We evaluate the proposed method by simulations at different levels of noise and in-vivo experiments on the human biceps brachii and common carotid artery. The experimental results demonstrate that ApodNet provides a promising strategy for high frame rate STA imaging, obtaining comparable lateral resolution and contrast resolution with four-times higher frame rate than conventional STA imaging in the in-vivo experiments. Particularly, ApodNet improves contrast resolution of the hypoechoic targets with much shorter computational time when compared with other high-frame-rate methods in both simulations and in-vivo experiments. [ABSTRACT FROM AUTHOR]

Forward-looking multichannel synthetic aperture radar (FLMC-SAR) is an important tool for modern remote sensing applications, which has the capability to reconstruct the high-resolution image of the front area. However, due to the azimuth-variant characteristics of the motion errors over a long aperture, FLMC-SAR data processing is usually a challenging task, especially when involving the motion compensation (MOCO) coupled with Doppler ambiguity resolving. To accomplish an accurate MOCO for FLMC-SAR, a novel parametric azimuth-variant MOCO approach is proposed in this article. Aiming at the coupling problem of MOCO and Doppler ambiguity resolving over the full aperture, we can decouple them through the subaperture division. As a full synthetic aperture is decomposed into several subapertures, the high-order motion errors of the full aperture can be decomposed into the first-order motion errors of the subaperture. On this basis, the mismatch of the space–time spectrum caused by the motion errors can be solved by spectral estimation, yielding Doppler ambiguity resolving for each subaperture. Meanwhile, the azimuth-variant characteristic of motion errors in FLMC-SAR system is characterized by a parametric angle-dependent quadratic phase error (QPE) model. The motion parameters are estimated by a joint multichannel angle estimation-based signal quadratic decomposition method. Immediately, the MOCO for ambiguous targets with different motion errors can be processed separately to improve the imaging performance. Experimental results based on both simulated and real data demonstrate that the proposed method is suitable for FLMC-SAR system. [ABSTRACT FROM AUTHOR]

Lamb-wave-based structural health monitoring (SHM) has attracted extensive attention in recent years. This article aims to realize the functions of data communication, defect detection, and energy transmission through piezoelectric transducers. In this work, the ${S}_{{0}}$ mode at 500 kHz and the ${A}_{{0}}$ mode at 150 kHz are selected as the carrier waves and the optimized excitation frequencies are determined through analytical investigation and frequency sweeping experiments. The ${S}_{{0}}$ mode is used for data communication and defect inspection due to the high excitation frequency and low dispersion properties. A single piezoelectric sensing element acts as the transmitter and a nine-element piezoelectric transducer array (PTA) is the receiver. Their roles exchange in terms of energy transmission based on the ${A}_{{0}}$ mode. Simultaneous data communication and energy transmission are achieved based on the frequency division multiplexing (FDM) strategy. After performing a matched filter on the received signals, the digital data information can be recovered under the interference of the energy transmission signal. The synthetic aperture imaging technology (SAFT) is adopted for accurately locating defects on aluminum plates. In terms of energy transmission, a constructive interference performance is achieved by the transducer array with a transmitted power of 3.81 mW. This system has great potential for health monitoring of the enclosed structure by eliminating the cumbersome wires for powering and communication. [ABSTRACT FROM AUTHOR]

A novel super-resolution volumetric photoacoustic microscopy, based on the theory of structured-illumination, is proposed in this paper. The structured-illumination will be introduced in order to surpass the diffraction limit in a photoacoustic microscopy (PAM) structure. Through optical excitation of the targeted object with a sinusoidal spatial fringe pattern, the object’s frequency spectrum is forced to shift in the spatial frequency domain. The shifting in the desired direction leads to the passage of the high-frequency contents of the object through the passband of the acoustic diffraction frequency response. Finally, combining the low-frequency image with the high-frequency parts in four regular orientations in the spatial frequency domain is equivalent to imaging the targeted object with an imaging system of two-fold bandwidth and thus half lateral resolution. In order to obtain the image of out-of-focus regions and improve the lateral resolution outside the focal region of a PAM imaging system, Fourier-domain reconstruction algorithm based on the synthetic aperture focusing technique (SAFT) using the virtual detector concept is utilized for reduction in the required computational load and time. The performance of the proposed imaging system is validated with in vivo and ex vivo targets. The experimental results obtained from several tungsten filaments in the depth range of 1.2 mm, show an improvement of −6 dB lateral resolution from 55–287 μm to 25–29 μm and also an improvement of signal-to-noise ratio (SNR) from 16–22 dB to 27–33 dB in the proposed system. [ABSTRACT FROM AUTHOR]

There is a significant acoustic impedance contrast between the cortical bone and the surrounding soft tissue, resulting in difficulty for ultrasound penetration into bone tissue with high frequency. It is challenging for the conventional pulse-echo modalities to give accurate cortical bone images using uniform sound velocity model. To overcome these limitations, an ultrasound imaging method called full-matrix Fourier-domain synthetic aperture based on velocity inversion (FM-FDSA-VI) was developed to provide accurate cortical bone images. The dual linear arrays were located on the upper and lower sides of the imaging region. After full-matrix acquisition with two identical linear array probes facing each other, travel-time inversion was used to estimate the velocity distribution in advance. Then, full-matrix Fourier-domain synthetic aperture (FM-FDSA) imaging based on the estimated velocity model was applied twice to image the cortical bone, utilizing the data acquired from top and bottom linear array, respectively. Finally, to further improve the image quality, the two images were merged to give the ultimate result. The performance of the method was verified by two simulated models and two bone phantoms (i.e., regular and irregular hollow bone phantom). The mean relative errors of estimated sound velocity in the region-of-interest (ROI) are all below 12%, and the mean errors of cortical section thickness are all less than 0.3 mm. Compared to the conventional synthetic aperture (SA) imaging, the FM-FDSA-VI method is able to accurately image cortical bone with respect to the structure. Moreover, the result of irregular bone phantom was close to the image scanned by microcomputed tomography ($\mu $ CT) in terms of macro geometry and thickness. It is demonstrated that the proposed FM-FDSA-VI method is an efficient way for cortical bone ultrasonic imaging. [ABSTRACT FROM AUTHOR]

The emerging field of combining compressed sensing (CS) and three-dimensional synthetic aperture radar (3D SAR) imaging has shown significant potential to reduce sampling rate and improve image quality. However, the conventional CS-driven algorithms are always limited by huge computational costs and non-trivial tuning of parameters. In this article, to address this problem, we propose a two-path iterative framework dubbed TPSSI-Net for 3D SAR sparse imaging. By mapping the AMP into a layer-fixed deep neural network, each layer of TPSSI-Net consists of four modules in cascade corresponding to four steps of the AMP optimization. Differently, the Onsager terms in TPSSI-Net are modified to be differentiable and scaled by learnable coefficients. Rather than manually choosing a sparsifying basis, a two-path convolutional neural network (CNN) is developed and embedded in TPSSI-Net for nonlinear sparse representation in the complex-valued domain. All parameters are layer-varied and optimized by end-to-end training based on a channel-wise loss function, bounding both symmetry constraint and measurement fidelity. Finally, extensive SAR imaging experiments, including simulations and real-measured tests, demonstrate the effectiveness and high efficiency of the proposed TPSSI-Net. [ABSTRACT FROM AUTHOR]

Inverse synthetic aperture radar (ISAR) imaging for the target with micro-motion parts is influenced by the micro-Doppler (m-D) effects. In this case, the radar echo is generally decomposed into the components from the main body and micro-motion parts of target, respectively, to remove the m-D effects and derive a focused ISAR image of the main body. For the sparse aperture data, however, the radar echo is intentionally or occasionally under-sampled, which defocuses the ISAR image by introducing considerable interference, and deteriorates the performance of signal decomposition for the removal of m-D effects. To address this issue, this paper proposes a novel m-D effects removed sparse aperture ISAR (SA-ISAR) imaging algorithm. Note that during a short interval of ISAR imaging, the range profiles of the main body of target from different pulses are similar, resulting in a low-rank matrix of range profile sequence of main body. For the range profiles of the micro-motion parts, they either spread in different range cells or glint in a single range cell, which results in a sparse matrix of range profile sequence. From this perspective, the low-rank and sparse properties are utilized to decompose the range profiles of the main body and micro-motion parts, respectively. Moreover, the sparsity of ISAR image is also utilized as a constraint to eliminate the interference caused by sparse aperture. Hence, SA-ISAR imaging with the removal of m-D effects is modeled as a triply constrained underdetermined optimization problem. The alternating direction method of multipliers (ADMM) and linearized ADMM (L-ADMM) are further utilized to solve the problem with high efficiency. Experimental results based on both simulated and measured data validate the effectiveness of the proposed algorithm. [ABSTRACT FROM AUTHOR]

An adaptive scanning algorithm is proposed for reducing scanning time associated with generating synthetic aperture radar (SAR) images, for nondestructive evaluation (NDE) applications, while preserving optimal cross-range resolution and image quality. The proposed method is based on the fact that optimum SAR cross-range resolution is target depth, synthetic aperture dimension, and scanning step size dependent. Hence, in the proposed method, the target properties, such as position and depth, are first estimated using an initial coarse scan of the scene of interest. Then, a localized dense scan is performed for obtaining optimal spatial resolution and image quality. During this procedure, the synthetic aperture dimension of the localized dense scan is adaptively increased (optimized) by reducing pixel-by-pixel image root-mean-square (rms) intensity difference between the images produced before and after each increment increase in the synthetic aperture dimension of the localized dense scan. At the same time, scanning step size is determined in a manner, which is related to the target depth in order to reduce scanning time and to insure obtaining (close to) optimal spatial sampling. Results of several illustrative measurements are provided by which the efficacy of the proposed method is demonstrated. The proposed algorithm, which mainly applies for imaging a localized flaw or a strong-scattering target in a relatively homogenous environment, is common in NDE applications and can be implemented using an automated and adaptive process. [ABSTRACT FROM AUTHOR]

Inverse synthetic aperture sonar (ISAS) is the major instrument to observe moving underwater vehicles with high-resolution acoustic images. In this article, we consider the cyclic prefix (CP)-based orthogonal frequency-division multiplexing (OFDM) ISAS imaging for a noncooperative underwater vehicle. Compared to the ISAS using the conventional linear frequency-modulated (LFM) waveform, the OFDM signal is more sensitive to Doppler shifts/errors. The fluctuation of acoustic velocity in the propagating medium brings random phase errors and leads to heavily blurred images. Existing ISAS imaging methods are based on the translational motion of the target, and these methods suffer from defocusing in severe ocean conditions. In this article, we propose the motion compensation algorithm for the OFDM ISAS imaging to minimize the effect of velocity variations caused by ocean turbulence. The sparsity of the ISAS image is utilized as a global metric for the phase error estimation and image generation by constructing an $\ell _{1} $ -norm optimization. It is demonstrated that inter-range-cell interference (IRCI)-free ISAS images can be obtained no matter whether there are phase errors and/or strong noise. Simulation results indicate the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

Detecting covered cracks in metals is critical in many applications. In this article, a single dual-polarized circular aperture antenna and synthetic aperture imaging are devised to detect arbitrarily oriented cracks covered under thick dielectric layer. The devised monostatic quad-polarized system facilitates measurements of the reflection (copolarized) and transmission (cross-polarized) parameters which form the basis for reliable detection. Through analysis and measurements involving dielectric covers with thicknesses ranging from 4.25 to 12.7 mm, it will be demonstrated that the background clutter and the effect of the cover are largely suppressed in the images formed using the cross-polarized parameter. On the other hand, it will be highlighted that the crack could be actually masked by the clutter in the image formed using the reflection measurements commonly used for crack detection. [ABSTRACT FROM AUTHOR]

The influence of the antenna gain pattern on synthetic aperture radar (SAR) image sidelobe level is analyzed in this article. The traditionally used antenna with wide beamwidth results in relatively constant and large sidelobe level in SAR image. The presence of these sidelobes can mask adjacent weak indications, which often necessitate windowing or implementation of other signal processing techniques in order to help reduce the effect of image sidelobes associated with strong target indications. Alternatively, using an antenna with a relatively narrow beamwidth provides for an inherent weighting function applied to the target spectrum, which is calculated within the SAR algorithm, along the cross-range direction, and this weighting function is directly related to the scanning antenna gain pattern properties. Consequently, an antenna with a relatively narrow beamwidth produces a lower SAR image sidelobe level along the cross-range direction. Corroborating results from numerical simulations and measurements are provided to illustrate the impact of antenna gain pattern on SAR image sidelobe level. [ABSTRACT FROM AUTHOR]

In this study, we propose a synthetic aperture imaging technique for near-field scatterers mutually coupled with an antenna array, such as supporting structures, fixtures of the antenna, and a radome enclosing the antenna. Mutual coupling is a phenomenon, in which the scattered and reradiated waves from the array elements and the near-field scatterers are received by the array elements, and it is known to cause undesired effects in array signal processing, such as direction-of-arrival estimation. Therefore, we need to design the antenna array with the goal of reducing the unwanted scattered and reradiated waves as much as possible, and we require a method to evaluate the scattering intensity for validation of the antenna design. For this purpose, we utilize the bistatic synthetic aperture radar measurement, whereby we mount the receiving antenna array under test on a turntable for azimuth rotation and irradiate this antenna with a fixed transmitting antenna. The measured signals are synthesized to image an area that contains both the array elements and scatters of interest. Because the spatial separations between the array elements and the scatterers are small, the direct waves from the transmitting antenna to the receiving elements result in serious artifacts in the reconstructed image. To suppress this effect, we apply a direct wave filter as a preprocessing method for image reconstruction. We demonstrate the proposed imaging scheme via data sets of numerical electromagnetic simulations and anechoic chamber measurements. [ABSTRACT FROM AUTHOR]

Objective: The current standard of care for peripheral chronic total occlusions involves the manual routing of a guidewire under fluoroscopy. Despite significant improvements in recent decades, navigation remains clinically challenging with high rates of procedural failure and iatrogenic injury. To address this challenge, we present a proof-of-concept robotic guidewire system with forward-viewing ultrasound imaging to allow visualization and maneuverability through complex vasculature. Methods: A 0.035” guidewire-specific ultrasound transducer with matching layer and acoustic backing was designed, fabricated, and characterized. The effect of guidewire motion on signal decorrelation was assessed with simulations and experimentally, driving the development of a synthetic aperture beamforming approach to form images as the transducer is steered on the robotic guidewire. System performance was evaluated by imaging wire targets in water. Finally, proof-of-concept was demonstrated by imaging an ex vivo artery. Results: The designed custom transducer was fabricated with a center frequency of 15.7 MHz, 45.4% fractional bandwidth, and 31 dB SNR. In imaging 20 μm wire targets at a depth of 6 mm, the lateral −6 dB target width was 0.25 ± 0.03 mm. The 3D artery reconstruction allowed visualization of vessel wall structure and lumen. Conclusion: Initial proof-of-concept for an ultrasound transducer-tipped steerable guidewire including 3D image formation without an additional sensor to determine guidewire position was demonstrated for a sub-mm system with an integrated ultrasound transducer and a robotically-steered guidewire. Significance: The developed forward-viewing, robotically-steered guidewire may enable navigation through occluded vascular regions that cannot be crossed with current methods. [ABSTRACT FROM AUTHOR]

In order to improve the image quality of a coded-aperture-based gamma-ray imaging apparatus, a method for removing Compton scattered and other multipixel events is presented that removes inaccurate position estimations from the data stream. In coded-aperture gamma-ray imaging detectors, scattering events that are shared between different partitions in the active medium can result in the inaccurate determination of the initial gamma-ray interaction position, the result of which is distortion in the angular reconstruction mapping. For coded-aperture system in which the rapid localization and identification of the emitting source is important, the distortion due to scattered radiation can increase the integration time of the system. We show, in both software and hardware implementations using a cerium-doped gadolinium aluminum gallium garnet pixelated scintillator array, that filtering the data to remove multipixel events can improve the image quality despite the efficiency loss associated with not utilizing all of the interactions within the detector. [ABSTRACT FROM AUTHOR]

Ultrasound elastography (USE) is an emerging noninvasive imaging technique in which pathological alterations can be visualized by revealing the mechanical properties of the tissue. Estimating tissue displacement in all directions is required to accurately estimate the mechanical properties. Despite capabilities of elastography techniques in estimating displacement in both axial and lateral directions, estimation of axial displacement is more accurate than lateral direction due to higher sampling frequency, higher resolution, and having a carrier signal propagating in the axial direction. Among different ultrasound imaging techniques, synthetic aperture (SA) has better lateral resolution than others, but it is not commonly used for USE due to its limitation in imaging depth of field. Virtual source synthetic aperture (VSSA) imaging is a technique to implement SA beamforming on the focused transmitted data to overcome the limitation of SA in depth of field while maintaining the same lateral resolution as SA. Besides lateral resolution, VSSA has the capability of increasing sampling frequency in the lateral direction without interpolation. In this article, we utilize VSSA to perform beamforming to enable higher resolution and sampling frequency in the lateral direction. The beamformed data are then processed using our recently published elastography technique, OVERWIND. Simulation and experimental results show substantial improvement in the estimation of lateral displacements. [ABSTRACT FROM AUTHOR]

A 3-D synthetic transmit aperture ultrasound imaging system with a fully addressed array usually leads to high hardware complexity and cost since each element in the array is individually controlled. To reduce the hardware complexity, we had presented the large-pitch synthetic transmit aperture (LPSTA) ultrasound imaging for 2-D imaging using a 1-D phased array to reduce the number of measurement channels M (the product of number of transmissions, IT, and the number of receiving channels in each transmission, IR). In this article, we extend this method to a 2-D matrix array for 3-D imaging. We present both numerical simulations and experimental measurements. We combined L × L adjacent elements into transmission subapertures (SAP) and K × K adjacent elements into receive SAPs in synthetic transmit aperture (STA) imaging. In the image reconstruction, we conducted the first attempt to apply and integrate Gaussian-approximated spatial response function (G-SRF) with delay and sum (DAS) to improve the image contrast, especially for the near-field targets. The imaging performance obtained from G-SRF was also evaluated numerically and compared with the previously presented frequency-domain SRF (Freq-domain SRF). The 3-D large-pitch synthetic transmit aperture (3-D-LPSTA) with G-SRF can provide a computationally efficient solution compared with the standard 3-D-STA method. With approximately 1900-fold reduction in the number of measurement channels, 3-D-LPSTA can provide image contrast comparable with the standard 3-D-STA with a full array and significantly better than using a periodically sparse array with similar complexity. In addition to reducing the system complexity, the 3-D-LPSTA achieves 700-fold reduction in computational complexity and 523-fold reduction in data storage. Finally, we evaluated and implemented the G-SRF using phantom data, which were consistent with the simulation results showing that the G-SRF can improve the image contrast. The results demonstrate that the proposed 3-D-LPSTA shows the great potential for designing an inexpensive ultrasound system to ensure the real-time 3-D clinical ultrasound imaging using large arrays. The limits of the proposed method were also discussed. [ABSTRACT FROM AUTHOR]

This article studies the near-range 3-D image reconstruction based on millimeter-wave multiple-input-multiple-output circular synthetic aperture radar (MIMO-CSAR). We first derive the exact forward wave model of MIMO-CSAR and then propose a range migration algorithm for near-range high-precision 3-D image reconstruction. Our formulation is strictly based on wave theory. The propagation attenuation, which is an inherent factor in wave equation and is significant for near-range wide-angle sensing case, is considered and compensated efficiently with a Fourier-domain matched filtering. Besides, the phase decoupling is achieved with a 2-D Stolt mapping. The computational complexity of the algorithm is at the same level as the state-of-the-art method. Compared with the state of the art, by considering the amplitude variation, the imaging quality can be improved for near-range measurement with large beamwidth. The results from both synthetic and practical measurement data demonstrate that a wider dynamic range (less sidelobes appeared at the same dynamic level) and a better recovery for widespread targets compared with the state-of-the-art imaging method. [ABSTRACT FROM AUTHOR]

The delay-and-sum (DAS) beamformer is the most commonly used method in medical ultrasound imaging. Compared with the DAS beamformer, the minimum variance (MV) beamformer has an excellent ability to improve lateral resolution by minimizing the output of interference and noise power. However, it is hard to overcome the tradeoff between satisfactory lateral resolution and speckle preservation performance due to the fixed subarray length of covariance matrix estimation. In this study, a new approach for MV beamforming with adaptive spatial smoothing is developed to address this problem. In the new approach, the generalized coherence factor (GCF) is used as a local coherence detection tool to adaptively determine the subarray length for spatial smoothing, which is called adaptive spatial-smoothed MV (AMV). Furthermore, another adaptive regional weighting strategy based on the local signal-to-noise ratio (SNR) and GCF is devised for AMV to enhance the image contrast, which is called GCF regional weighted AMV (GAMV). To evaluate the performance of the proposed methods, we compare them with the standard MV by conducting the simulation, in vitro experiment, and the in vivo rat mammary tumor study. The results show that the proposed methods outperform MV in speckle preservation without an appreciable loss in lateral resolution. Moreover, GAMV offers excellent performance in image contrast. In particular, AMV can achieve maximal improvements of speckle signal-to-noise ratio (SNR) by 96.19% (simulation) and 62.82% (in vitro) compared with MV. GAMV achieves improvements of contrast-to-noise ratio by 27.16% (simulation) and 47.47% (in vitro) compared with GCF. Meanwhile, the losses in lateral resolution of AMV are 0.01 mm (simulation) and 0.17 mm (in vitro) compared with MV. Overall, this indicates that the proposed methods can effectively address the inherent limitation of the standard MV in order to improve the image quality. [ABSTRACT FROM AUTHOR]