Backscattered Signals Research Articles

Turbidity estimation from an acoustic backscatter signal in a tropical coral reef system.

This study investigated the estimation of Nephelometric Turbidity Units (NTU) from backscatter signals in a tropical coral reef system using a 1200-kHz towed Acoustic Doppler Current Profiler (ADCP). In order to perform the estimation, simultaneous acoustic backscatter and turbidity data were collected near the surface (above the pycnocline). Simultaneously, water samples at the same depths were analyzed to determine sediment composition. The results showed that a second-degree polynomial model provided the best correlation (r=0.69) between backscatter signals and turbidity measurements, highlighting the nonlinear relationship between acoustic signals and turbidity values obtained from optical devices. The reef's bathymetry significantly influenced the seawater turbidity, revealing the importance of physical configuration and hydrodynamic conditions in sediment distribution. From the sediment composition, it was determined that 89% of the total suspended solids are terrigenous sediments. This integrated methodological approach provides a detailed understanding of sediment dynamics, essential for the conservation and sustainable management of coral reefs around the word in a noninvasive way.

Dual-channel infrared OPO lidar optical system for remote sensing of greenhouse gases in the atmosphere: Design and characteristics

Current global warming and climate change under the greenhouse effect call for a thorough understanding of the spatial distribution of greenhouse gases in different atmospheric layers. Lidar systems are the most effective for remote greenhouse gas monitoring. We design a two-channel infrared OPO lidar optical system for remote DIAL/DOAS sensing of carbon dioxide and water vapor in the atmosphere. In this work, optimal geometric parameters of the transceiving channel of the lidar optical system are chosen, a need to focus laser radiation at a distance of 1 km from an observation point is demonstrated, and numerical simulations confirm the possibility of detecting lidar signals ranging from 10−7 to 10−10 W in the informative spectral range 4800–5100 cm−1 (1960–2083 nm). Laboratory experiments with the main components of the lidar system with experimentally confirmed parameters, which simulate atmospheric measurements of CO2 absorption at a calibrated sensing wavelength of 2005 nm (4987 cm−1) (pressure of 1 atm; CO2 concentration corresponding to the midlatitude summer background atmosphere) in the informative spectral range of the lidar system, enable selecting a pair of wavelengths with resonant absorption of the target gas near 2005 nm to study the background state of the atmosphere in the surface layer. Efficiency of the lidar optical system is confirmed by in situ test experiments, where backscattering signals from a topographic target with an albedo of ∼0.15 spaced 168 m apart from an observer are recorded at 60 mV when operating along a horizontal atmospheric path. The lidar system we design can be used in measuring complexes at carbon test sites. It can also be used for atmospheric monitoring in industrial centers, at background measuring stations, and in swamp areas.

Optimizing the Automated Analysis of Inorganic Gunshot Residue Particles by SEM-EDX: From Synthetic Particle Standards to More Time-Efficient Settings for Daily Casework

Gunshot residues deposited on all surfaces in the nearest vicinity of the shooting incident, when revealed, can contribute to the explanation of various aspects of such an incident for forensic purposes. Examinations of gunshot residue, mainly inorganic particles, at forensic laboratories are expected to be reliable and fast. This primarily depends on the performance of the used scanning electron microscope integrated with an energy dispersive X-ray spectrometer and the automatic program searching for particles of defined characteristics. Among the milestones on the pathway towards quality assurance in examinations of gunshot particles, the invention of the synthetic gunshot residue specimen ought to be named. Such a specimen with particles of known chemical content, size, and location is now used for proficiency testing, which is a condition for a forensic laboratory to obtain accreditation in this subject matter. In this publication, the need for optimization of the procedure for the examination of a synthetic specimen, in alignment with the necessary modifications for real gunshot particles, has been addressed. The presented process of validation resulted in two procedures. The first demonstrates the full capacity of the instrument for detecting all particles present in the synthetic specimen, including the 0.5 micrometer particle at the magnification of 250×. The other procedure is the modification of the first, however aiming at 1-micrometer particles or bigger (at the magnification of 120×) and allowing the necessary backscattered signal threshold changes depending on the actual composition of gunshot residue as well as the abundance of light element debris in the case of real gunshot particles.

High spatial resolution φ-OFDR based on frequency-shift averaging and rotating vector summation

The coherent fading noise hinders the spatial resolution enhancements of phase optical frequency domain reflectometry (φ-OFDR). To mitigate the coherent fading noise, this study introduces frequency-shift averaging and rotating vector summation for strain measurements. The original Rayleigh backscattering signal was first divided into numerous sub-segments in frequency domain by using the frequency-shift averaging, and each sub-signal segment was transferred into vector signal with both intensity and phase information by using the rotating vector summation. Furthermore, a spatial position correction algorithm is incorporated to counteract the degradation of phase coherent, facilitating large-scale strain measurements. After optimizing the sub-frequency range and overlap ratio of the sub-signal in the frequency domain, we experimentally demonstrated that this method achieves strain measurement with a broad strain range of 2000 με, a high spatial resolution of 0.54 mm, and a high precision of 0.87%.

Frequency-locked Si3N4 microring for Doppler frequency shift detection

In this paper, we propose to use a homemade all-fiber Si3N4 microring as the frequency discriminator for Doppler frequency shift detection. The full width at half maximum of the microring is 361.83 MHz, which covers the dynamic range of ± 70 m/s for wind measurement applications. By introducing a time-division multiplexing method, we have achieved the frequency locking of the microring to the central frequency of the laser source, which effectively stabilizes the measurement accuracy against perturbations such as temperature fluctuations. By alternatively upshifting and downshifting the pulses, a dual-frequency lasing scheme has been designed to realize the double-edge technique for frequency shift detection. A commercial single-photon detector with 25% quantum efficiency and approximately 1300 Hz dark count rate is used to detect the backscattered signals, which circumvents the need for bulky and expensive superconducting single-photon detectors. The proposed system is validated through an outdoor wind speed detection experiment using a reference anemometer. The experiment results demonstrate the feasibility of using microring as the frequency discriminator and that the precise frequency locking control is able to improve the measurement accuracy to the state-of-the-art level under the influence of perturbations, which highlights the potential for highly integrated direct detection Doppler wind lidar design.

Random Raman Lasing in Diode-Pumped Multi-Mode Graded-Index Fiber with Femtosecond Laser-Inscribed Random Refractive Index Structures of Various Shapes

Diode-pumped multi-mode graded-index (GRIN) fiber Raman lasers provide prominent brightness enhancement both in linear and half-open cavities with random distributed feedback via natural Rayleigh backscattering. Femtosecond laser-inscribed random refractive index structures allow for the sufficient reduction in the Raman threshold by means of Rayleigh backscattering signal enhancement by +50 + 66 dB relative to the intrinsic fiber level. At the same time, they offer an opportunity to generate Stokes beams with a shape close to fundamental transverse mode (LP01), as well as to select higher-order modes such as LP11 with a near-1D longitudinal random structure shifted off the fiber axis. Further development of the inscription technology includes the fabrication of 3D ring-shaped random structures using a spatial light modulator (SLM) in a 100/140 μm GRIN multi-mode fiber. This allows for the generation of a multi-mode diode-pumped GRIN fiber random Raman laser at 976 nm with a ring-shaped output beam at a relatively low pumping threshold (~160 W), demonstrated for the first time to our knowledge.

Metallic material microstructure grain size measurements from backscattering signals in ultrasonic array data sets

Ultrasound backscattering signals from material microstructures can be used to evaluate the material microstructure grain size. This typically involves making pulse-echo immersion measurements at multiple locations using a focused ultrasonic transducer in order to obtain an accurate estimate of the root-mean-square amplitude of the back-scattered signal at a specified focal position. However, this restricts some practical applications of using such techniques in, for example, on-line measurements in high-value manufacturing and in-service inspections where multiple immersion measurements are not feasible to use. The main benefit of using ultrasonic phased arrays is that one array probe at one position can focus ultrasound beams at multiple points using different focal laws either physically or in data postprocessing. Potentially this means that accurate grain size measurements can be obtained from a single array measurement. In this paper, the classic backscattering method for conventional transducers is adapted to be used for full matrix capture datasets from an ultrasonic array. Three-dimensional ultrasonic models are developed in the proposed inverse process to measure material microstructure grain size. Experimental validations were performed on two metallic materials: copper (EN1652) and bright mild steel (BS970). A good agreement is shown between the experimentally measured grain sizes from array data and metallography measurements. Compared to the classic pulse-echo immersion back-scattering measurements, the proposed method enables accurate measurement of grain size in a direct contact configuration at fewer locations. This has potential to make on-line grain size measurements possible.

Antarctic ice-shelf meltwater outflows in satellite radar imagery: ground-truthing and basal channel observations

Abstract Ice shelves regulate the flow of the Antarctic ice sheet toward the ocean and its contribution to sea-level rise. Accurately monitoring the basal and surface melting of ice shelves is therefore essential for predicting the ice sheet's response to climatic warming. In this study, we utilize Sentinel-1A synthetic aperture radar satellite imagery combined with shipboard measurements of water temperature and salinity to investigate the presence of surficial meltwater plumes along the Antarctic coastline. Our approach reveals a strong correlation between areas of pronounced low radar backscatter extending from ice shelves and significant decreases in water temperature and salinity, suggesting meltwater-enriched ocean waters. We propose that the low radar backscatter signature of meltwater outflows is caused by stable stratification of the upper water column, driven by density contrasts from buoyant, low-salinity meltwater and surface current shear that reduce Bragg scattering waves. The resulting smooth water surfaces were observed adjacent to the surface expression of deep basal channels, documented in a helicopter survey along part of the Bellingshausen Sea ice edge. We present high-temporal resolution satellite radar as a tool for identifying meltwater release from beneath ice shelves, capable of all-weather, day-and-night imaging.

Subpixel three-dimensional imaging using two-dimensional optical encoding with a downscaled avalanche photodiode array

Scannerless laser three-dimensional (3D) imaging relies on large-scale detector arrays to achieve high-resolution imaging and is one of the main technologies in light detection and ranging (LIDAR). However, the high production cost and complex manufacturing process is limiting the imaging resolution. In this paper, we demonstrate a subpixel 3D imaging method based on two-dimensional (2D) encoding and decoding. First, an LED array projects 2D spatio-temporal coded light beams onto the target space. Accordingly, an optical multiplexer separates and reconstructs the backscattered signals into a small-scale avalanche photodiode (APD) array. We designed a prototype with a 16×16 optical encoding and a 2×2 APD array. The scannerless imaging reconstructs 256 pixels per frame within the distance range of 39–68 cm.

Enhanced breast tumor localization with DRA antenna backscattering and GPR algorithm in microwave imaging

With the rapid rate of increasing breast cancer cases across the globe and restrictions of existing early stage detection techniques, microwave imaging based cancer and malignant cell diagnosing methodology is finding its way. Microwave imaging technology has higher accuracy of detection in the variation of tissue properties. In this article, a dielectric resonator based wide band antenna is designed and investigated for microwave imaging (MWI) of early breast cancer detection due to its improved accuracy. The designed antenna has compact size, broad frequency spectrum, high gain and broadside radiation characteristics. To attain the wider bandwidth from (6.5 GHz–12.5 GHz), two rectangular shaped dielectric slabs are used. Wide band microwave frequency band supports the high resolution images. A C-shaped defected ground structure is used to tune the impedance matching. Dielectric resonator based antenna has higher gain and reduces the squints in antenna impedance. Two-asymmetrical dielectric slabs contribute in the excitation of different resonating modes which in turn enhance the bandwidth. It also contributes to excite multiple resonance mode that in turn enhance the bandwidth. Antenna performance is first numerically and experimentally verified in free space. Then, simulation based performance is examined for the microwave imaging. Numerical phantom with equivalent tissue properties is designed with and without the tumor. Unhealthy cells have higher water percentage and larger dielectric constant as compared to healthy cells. It causes the different in the back scattered signal of antenna, which is analyzed to diagnose the tumor or cancer. Here, a maximum deviation of 16 dB is observed in the backscattered signal. Furthermore, surface of the breast tissue is scanned along the x-axis and y-axis at different angels. The collected signals are used to reconstruct the microwave image of the interior. Mean value data of backscattered signals is used to locate the existence of unhealthy cells and GPR algorithm is used to calculate the depth of a 4 mm tumor in breast tissue. Proposed structure has shown efficient performance for microwave imaging.

3D shape sensor based on discrete-point Rayleigh reflectors inscribed by femtosecond pulses in multicore fibers

Fiber optic sensors which use reflectometry methods to process Rayleigh backscattering signal, are susceptible to any optical losses due to the inherently low level of Rayleigh backscattering in standard telecom optical fibers. In this work, we fabricate and study the shape sensor based on a multicore optical fiber with randomly spaced discrete-point reflectors inscribed in its cores by femtosecond laser pulses. By testing the sensor on different 3D shape samples, we demonstrate the robustness of the shape reconstruction accuracy to introduced optical losses of the signal up to 20 dB with the relative reconstruction error being less than 4 %. In contrast, such level of optical losses dramatically increases the reconstruction error when the unmodified fiber cores are used. A higher signal-to-noise ratio together with low birefringence of the inscribed point reflectors enable accurate shape sensing including the forms with low curvature.

TF-REF-RNN: Time-Frequency and Reference Signal Feature Fusion Recurrent Neural Network for Underwater Backscatter Signal Separation

Underwater wireless sensor networks play an important role in exploring the oceans as part of an integrated space–air–ground–ocean network. Because underwater energy is limited, the equipment’s efficiency is significantly impacted by the battery duration. Underwater backscatter technology does not require batteries and has significant potential in positioning, navigation, communication, and sensing due to its passive characteristics. However, underwater backscatter signals are susceptible to being swamped by the excitation signal. Additionally, the signals from different reflection signals share the same frequency and overlap, and contain fewer useful features, leading to significant challenges in detection. In order to solve the above problems, this paper proposes a recurrent neural network that introduces time-frequency and reference signal features for underwater backscatter signal separation (TF-REF-RNN). In the feature extraction part, we design an encoder that introduces time-frequency domain features to learn more about the frequency details. Additionally, to improve performance, we designed a separator that incorporates the reference signal’s pure global information features. The proposed TF-REF-RNN network model achieves metrics of 28.55 dB SI-SNRi and 19.51 dB SDRi in the dataset that includes shipsEar noise data and underwater simulated backscatter signals, outperforming similar classical methods.

Ultrasound Imaging in Knee Osteoarthritis: Current Role, Recent Advancements, and Future Perspectives.

While conventional radiography and MRI have a well-established role in the assessment of patients with knee osteoarthritis, ultrasound is considered a complementary and additional tool. Moreover, the actual usefulness of ultrasound is still a matter of debate in knee osteoarthritis assessment. Despite that, ultrasound offers several advantages and interesting aspects for both current clinical practice and future perspectives. Ultrasound is potentially a helpful tool in the detection of anomalies such as cartilage degradation, osteophytes, and synovitis in cases of knee osteoarthritis. Furthermore, local diagnostic and minimally invasive therapeutic operations pertaining to knee osteoarthritis can be safely guided by real-time ultrasound imaging. We are constantly observing a growing knowledge and awareness among radiologists and other physicians, concerning ultrasound imaging. Ultrasound studies can be extremely useful to track the response to various therapies. For this specific aim, tele-ultrasonography may constitute an easy tool aiding precise and repeated follow-up controls. Moreover, raw radio-frequency data from US backscattering signals contain more information than B-mode imaging. This paves the way for quantitative in-depth analyses of cartilage, bone, and other articular structures. Overall, ultrasound technologies and their rapid evolution have the potential to make a difference at both the research and clinical levels. This narrative review article describes the potential of such technologies and their possible future implications.

Distributed Acoustic Sensing Signal Model Under Static Fiber Conditions

This paper presents a statistical model for distributed acoustic sensor interrogation units that utilizes laser pulses transmitted into fiber optics. Interactions within the fiber lead to localized acoustic energy, resulting in backscatter, which is a reflection of the light. Explicit equations were used to calculate the amplitudes and phases of backscattered signals. The proposed model accurately predicts the amplitude signal spectrum and autocorrelation, aligning well with experimental observations. This study also explores the phase signal characteristics relevant to optical time-domain reflectometry (OTDR) system sensing applications, demonstrating consistency with the experimental results. The experiments were conducted using Python coding, enabling the analysis of the individual components of the Distributed Acoustic Sensing (DAS) system. The assumptions of the model include the static condition of the fiber, implying the absence of external forces or vibrations. Consequently, no external acoustic disturbances were considered. The backscattered signal comprises a random noise component resulting from intrinsic fiber imperfections, and a coherent component arising from the interplay between the laser pulse and the fiber. Keywords: distributed acoustic sensing, fiber optics, optical time-domain reflectometry, Rayleigh scattering.

Mapping Ratoon Rice Fields Based on SAR Time Series and Phenology Data in Cloudy Regions

Ratoon rice (RR) has emerged as an active adaptation to climate uncertainty, stabilizing total paddy rice yield and effectively reducing agriculture-related ecological environmental issues. However, identifying key remote sensing parameters for RR under cloudy and foggy conditions is challenging, and existing RR monitoring methods in these regions face significant uncertainties. Here, given the sensitivity of synthetic aperture radar (SAR) backscattering signals to the crop phenological period, this paper introduces a threshold model utilizing Sentinel-1A SAR data and phenological information for mapping RR. The Yongchuan District of Chongqing, which is often cloudy and foggy, was selected as a specific study region where VH-polarized backscatter coefficients of Sentinel-1 images were obtained at 10 m spatial resolution in 2020. Based on the proposed threshold model, the RR extraction overall accuracy was up to 90.24%, F1 score was 0.92, and Kappa coefficient was 0.80. Further analysis showed that the extracted RR boundaries exhibited high consistency with true Sentinel-2 remote sensing images and the RR extracted area was in good agreement with the actual planted area situation. This threshold model demonstrated good applicability in the studied cloudy and foggy region, and successfully distinguished RR from other paddy rice types. The methodological framework established in this study provides a basis for extensive application in China and other significant RR-producing regions globally.

High-Resolution Ultrasound Platform for Infant Meningitis Detection: An In Vitro Demonstration.

Infant meningitis remains a severe burden on global health, particularly for young infants. Traditional ultrasound imaging techniques are limited in spatial resolution to visualize white blood cells (WBCs) in the cerebrospinal fluid (CSF), which is considered a well-established marker for meningitis detection. This work presents a novel platform that uses high-resolution ultrasound to detect the backscatter signals from microscopic CSF WBCs through the anterior fontanelle of neonates and young infants. The whole system was built around a custom probe that allows for a 20 MHz focused transducer to be mechanically controlled to map the area of interest in the CSF. Data processing can be performed internally in the device without the need to extract the images for further analysis. The in vitro feasibility of the proposed solution was evaluated in imaging 7 μm particle suspensions at different concentrations relevant to meningitis diagnosis ranging from 7- to 646-particles (pp)/μL. The experimental tests were conducted from a simple setup using a sample container to a more realistic setup based on an anatomical phantom of the neonatal head. The results show high-quality images, where 7 μm particles can be resolved for the different concentrations.

A unified approach for breast cancer discrimination using metasurface-based microwave technology

Multifocal (MF) and multicentric (MC) breast cancers are more likely to be aggressive than unifocal (UF) breast tumors, and they are linked to high recurrence probability, lymph node metastases, and low survival rates. Metastasis is the process through which cancer cells spread to different body areas. Although the longevity of patients with metastatic breast cancer is high, it is restricted by the growth of brain metastases. Medical imaging techniques have inherent limits. Hence, a precise and sensitive substitution is required. Because microwave imaging is portable, non-ionizing, and affordable, it has become a viable method for the detection of breast cancer. As far as we know, this is the first research aiming at discriminating MF and MC breast cancers from UF ones. This proposal presents a 2×2\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$2\ imes 2$$\\end{document} planar metasurface-based array antenna in the Industrial Scientific Medical frequency band at 2.4 GHz. The proposed array configuration significantly enhanced the gain to 4 dBi rather than a single element at 50 Ω. The geometric arrangement of the four antenna elements is optimized to discriminate the critical stage of breast cancers (UF, MF, or MC). As the proposed structure does not surround the breast, it contributes to a higher degree of comfort than the conventional antenna configurations. The magnitude and phase of S-parameters of the backscattered signals are analyzed in this research.

Identifying grain size in ASTM A36 steel using ultrasonic backscattered signals and machine learning

Ultrasonic nondestructive techniques can be useful tools in the microstructural classification of metallic alloys. Among the most common techniques for characterizing materials, backscattered signal analysis stands out because it does not require a back surface echo. This study classifies five ASTM A36 steel samples with varying grain sizes using ultrasonic waves. For each sample, ultrasound signals were obtained using two ultrasonic array probes with center frequencies of 5 and 10 MHz. An extensive feature engineering process was conducted using the tfresh package in Python, which extracts a wide range of features from time series data, transforming raw ultrasound signals into a structured format. Seven machine learning models were evaluated based on accuracy, precision, recall, and F1 score, with performances ranging from 70 to 100%. The XGBoost model exhibited the best performance with 10 MHz probe signals, achieving 100% accuracy. An additional validation test was conducted to evaluate the models’ generalization capability, considering inter-specimen variabilities. Despite a slight reduction in prediction metrics, the XGBoost model maintained good performance, with accuracy between 89% and 100% across all frequencies. Such findings demonstrate that backscattered grain noise can effectively identify grain sizes provided that an adequate machine learning model is used.

Single-cell and extracellular nano-vesicles biosensing through phase spectral analysis of optical fiber tweezers back-scattering signals

Diagnosis of health disorders relies heavily on detecting biological data and accurately observing pathological changes. A significant challenge lies in detecting targeted biological signals and developing reliable sensing technology for clinically relevant results. The combination of data analytics with the sensing abilities of Optical Fiber Tweezers (OFT) provides a high-capability, multifunctional biosensing approach for biophotonic tools. In this work, we introduced phase as a new domain to obtain light patterns in OFT back-scattering signals. By applying a multivariate data analysis procedure, we extract phase spectral information for discriminating micro and nano (bio)particles. A newly proposed method—Hilbert Phase Slope—presented high suitability for differentiation problems, providing features able to discriminate with statistical significance two optically trapped human tumoral cells (MKN45 gastric cell line) and two classes of non-trapped cancer-derived extracellular nanovesicles – an important outcome in view of the current challenges of label-free bio-detection for multifunctional single-molecule analytic tools.

Fading suppression and noise reduction of a DAS system integrated multi-core fiber.

Multi-core fiber (MCF) has attracted increasing attention for application in distributed fiber sensing owing to its unique properties of independent light transmission in multiple spatial channels. Here, we report a distributed acoustic sensing (DAS) system integrated MCF to suppress coherent fading, which overcomes an inevitable challenge in DAS systems. Because the parallel spatial cores in MCF allow the use of space-division multiplexed (SDM) technology, we propose that fading can be effectively suppressed by merging different signals with the spatial rotated-vector-average (SRVA) method. We theoretically analyze the principle of SRVA in fading suppression, and identify that it can effectively reduce phase noise with preventing phase unwrapping failures. In our experiment, a DAS system with 2.58-km length MCF have been investigated, the fading rate of Rayleigh backscattered signals is effectively reduced by three orders of magnitude and the amplitude fluctuation range is decreased by 21.9 dB. Compared with the conventional spectrum extraction and remix method (SERM), SRVA reduces the noise level by 9.5 dB, which also shows excellent low-frequency signal recovery ability. Benefiting from its fading suppression, the false alarm of localization is mitigated and the phase recovery can be distortionless. The proposed and verified method is helpful for the application of SDM-based MCF in long-distance distributed fiber sensors and accelerates the progress of integrated sensing and communication.