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The SHAllow RADar (SHARAD) is a subsurface sounding radar provided by the Italian Space Agency (ASI) as a facility instrument for NASA's Mars Reconnaissance Orbiter (MRO) mission, the second longest-lived mission to orbit Mars after Mars Odyssey. Developed by an Italian-US Team, SHARAD was designed to investigate to depth of up to one kilometer in the Martian subsurface and to map dielectric discontinuities associated with compositional and/or structural changes. The radar mapping began in November 2006 and, after 16 years of operations, SHARAD has mapped most of the planet's surface (∼55%), contributing a data volume for the entire MRO mission that exceeds that of all the past Mars missions combined. Designed to complement the lower-frequency, relatively narrower bandwidth capability of the MARSIS sounding radar, SHARAD emits an 85 μs , frequency-modulated (10 MHz) chirp at a central frequency of 20 MHz to increase the signal-to-noise ratio (SNR) and achieve a finer resolution compared to MARSIS. On the ground, echoes recorded by the radar are range compressed using conventional pulse compression techniques yielding a nominal range resolution of 15 m (vacuum, 5–8 m in typical Martian materials). Additionally, synthetic aperture processing is performed in along-track to increase the resolution up to 300–500 m. Throughout the entire mission duration, SHARAD provided a diverse and extensive range of imaging data. It was able to observe the internal structures of Planum Boreum and Planum Australe, two icy deposits that contain the North and South Polar Layered Deposits (NPLD-SPLD), thought to contain valuable information about the planet's past climate. The radar unveiled the massive deposits of buried CO 2 ice below the southern residual ice cap (SRIC), which confirmed the influence of the planet obliquity and insolation in the accumulation of dry ice. Furthermore, it revealed the intricate lava flows structures in the Tharsis Volcanic region, suggesting that the planet experienced deposition by multiple volcanic episodes. However, radar resolution often poses a limitation for subsurface investigations in many regions. Only recently, processing techniques have focused on enhancing SHARAD radargrams vertical resolution by implementing the Bandwidth Extrapolation (BWE) technique. This approach has demonstrated an improvement of the vertical resolution while preserving the time-of-arrival (TOA) and amplitude of the detected echoes. The resulting super-resolved data products exhibit better separation between radar returns, thus improving the overall understanding of the investigated terrains. The obtained results demonstrate the value of implementing the BWE techniques in the data processing pipeline whenever radar sounders are involved. • The Shallow Radar (SHARAD) is a subsurface sounding radar mounted on NASA's Mars Reconnaissance Orbiter (MRO) spacecraft. • In 16-year operations SHARAD provided extensive imaging data, contributing to imaging 55% of Martian subsurface. • The radar has provided valuable data on the complex internal structures of icy deposits, lava flows and buried channels, among other discoveries. • The Bandwidth Extrapolation Technique (BWE) improves the sounder vertical resolution, revealing subsurface features with higher detail. • We discuss the implication of the new data in constraining the composition and boosting the geophysical interpretation. [ABSTRACT FROM AUTHOR]

Ultrasonic imaging of cylindrical structures using linear array scanning is a promising nondestructive testing technique. The image resolution in the axial direction of a cylinder has significantly improved through 2D total focusing algorithms employing single-frame full matrix capture (FMC) data. Further enhancement in circumferential resolution is achievable with synthetic aperture focusing using multiple FMC frames. However, conventional methods suffer from time-consuming computational complexity when focusing in both directions. This paper introduces an efficient 3D wavenumber-domain reconstruction method for both axial total and circumferential focusing in cylindrical FMC scans. Key steps include cylindrical scan phase shift migration (CSPSM) for rapid image migration and subsequent deconvolution for high image resolutions. In CSPSM, the imaging model can be simplified for wavefield extrapolation through appropriate distance approximations and the principle of stationary phase. The extrapolation is applicable to multilayered structures, considering constant transmission coefficients. A 3D imaging rate of 5 Hz is attainable with 32 frames of FMC data in the circumferential direction, each acquired by a 32-element linear array. Experimental results demonstrate achieving an axial resolution of 1.684 mm and a circumferential resolution of 0. 3 7 ∘ . This method holds potential for real-time 3D imaging in the inspection of wrapped pipelines. • Perform both axial total and circumferential focusing for cylindrical FMC scans. • Investigate the wavenumber-domain method to improve the efficiency of 3D imaging. • Support multilayered pipeline inspection. [ABSTRACT FROM AUTHOR]

The Synthetic Aperture Focusing Technique (SAFT) is employed in laser ultrasonic non-destructive testing to image defects. However, during the laser ultrasonic imaging process, the influence of multi-mode waves often introduces various artifacts in the imaging results. We investigated a multi-iteration frequency-domain SAFT (MIF-SAFT) algorithm to tackle this challenge. Initially, a single low-precision F-SAFT imaging result is performed to identify potential defect locations. Subsequently, a back-projection method is applied to determine defect positions and separates acoustic waves of different modes in the B-scan. After that, a multi-mode F-SAFT imaging is performed for evaluation, and the above process is repeated until the imaging outcome stabilizes. The result shows that artifacts are removed when the image remains unchanged after multiple iterations, and the imaging quality is effectively improved by MIF-SAFT. Furthermore, including directivity patterns of laser ultrasound also enhances defect imaging capabilities within MIF-SAFT. Additionally, we examined the MIF-SAFT's capacity to detect multiple defects, which can image them simultaneously. • Multi-iteration in F-SAFT for artifact removal. • Different ultrasonic signals are separated by using the algorithm. • Directivity patterns are performed to enhance the imaging result. • Applied for multiple defects imaging simultaneously. [ABSTRACT FROM AUTHOR]

The inverse synthetic aperture Ladar (ISAL) is an important system for observation of space objects. Here, a 2-D ISAL imaging and tracking algorithm is proposed for low observable maneuvering extended objects tracking (M−EOT) such as small space UAVs. When imaging maneuvering objects with ISAL, dispersion and Doppler frequency time-variation exist in the range and cross-range echo signal, respectively. Additionally, the ISAL system can achieve high-resolution images for long-range moving objects, while its performance is affected by atmospheric turbulence. Atmospheric turbulence is a very complicated random state formed by the instability of regular laminar flow at a high maneuvering velocity, which is caused by the random motion of the atmosphere and lead to the random fluctuation of the atmospheric refractive index. Therefore, in real-time M−EOT scenario, the measurements distribution over the whole object is not symmetrical but distributed and skewed in some portions while a target maneuvers due to the unbalanced of reflection that caused by the atmospheric turbulence. In practice, the micro Doppler effect caused by micro moving components such as drone rotors will seriously affect the focused ISAL imaging of the M−EOT's rigid body. To solve these problems in real-time low observable M−EOTs imaging and tracking from 2-D ISAL system, a novel robustness measurement model and recursion multi-Bernoulli track-before-detect filter based on a multiple model skewed non-symmetrically normal distribution is represented with more than one ellipse and lower complexity. In this paper, the Radon-Laplace method is presented to reduce this micro-Doppler effect in ISAL imaging. Additionally, we will eliminate the effect of atmospheric turbulence in ISAL Imaging by using the network-based variance–covariance estimation (NVCE) weighting method. In particular, we describe the M−EOT's state through the random matrices model (RMM). In RMM, the extent is applied by one ellipse, which often lose information about size, heading, and shape, when the scatter centers are distributed symmetrically around the M−EOT's centroid. In this paper, a new observation model used to modify a sub-RMM by considering the characteristics of 2-D ISAL data is proposed. Simulation results demonstrates the proposed robustness algorithm with the influence of the atmospheric turbulence and micro-Doppler. [ABSTRACT FROM AUTHOR]

In recent years, there has been a growing interest in the development of ground-based Synthetic Aperture Radars (GBSAR) for the purpose of monitoring structural displacements. GBSAR offers high-resolution monitoring over a wide area and can capture data every few minutes. However, compact high-frequency multiple input multiple output (MIMO) radars have emerged as an alternative for monitoring sub-second displacements, such as structural vibrations. MIMO radar has sub-second acquisition interval. However, it has limited cross-range resolution compared to GBSAR, and interference between antennas and presence of multiple scatterers in the scene can cause strong sidelobes in the processed data. On the other hand, GBSAR utilizes a long synthetic aperture to achieve high cross-range resolution. However, due to its longer data acquisition time compared to MIMO radar, conventional methods are insufficient for detecting scatterers' sub-second displacements that occur during the data acquisition process. This study proposes a method to effectively monitor sub-second or sub-minute displacements using GBSAR signals. The proposed method enhances the conventional radar interferometric processes by employing spectral estimation, allowing for multi-dimensional detection of targets' azimuth angle, linear displacement, and vibrational characteristics. Consequently, this method improves both the processing of MIMO radar data and enables high-resolution fast displacement monitoring from GBSAR signals. The paper presents the theoretical details and mathematical formulations of the proposed method for both MIMO radar and GBSAR imaging modes. To evaluate the effectiveness of the proposed method, numerical simulations and real experiments are conducted. The experimental results validate the capability of the proposed method in both GBSAR and MIMO configuration modes for high-resolution monitoring of fast linear displacements and vibrations. The results exhibit promising signal-to-noise ratio (SNR) and peak-to-sidelobe ratio (PSLR) values. [ABSTRACT FROM AUTHOR]