Passive Imaging Research Articles

Moving target detection based on multi-satellite joint passive microwave imaging

Using satellite formations to form a space-based passive interferometric imaging system can achieve high spatial resolution, but the sparse detection baseline will cause aliasing in the inversion image, affecting the detection of single-pixel point targets. Considering the slowly varying characteristics of the observation area, a target detection method based on image sequence is proposed. The background is estimated by multi-frame images, and the background of the inversion image is eliminated; energy is gathered based on sidelobe characteristics, the noise in the target area is estimated, and candidate targets are selected; the motion trajectory of the target is obtained by combining the temporal motion characteristics, and the detection of moving point targets is realized. Taking the formation system composed of 10 geostationary orbit satellites as an example, 300 simulation experiments are carried out for the detection of 50 ship point targets. The results show that the proposed method can realize point target detection in a large field of view, with an average false alarm rate 14.5%and an average missed alarm rate 19.5%.

Bruise detection of apples based on passive thermal imaging technology

Bruise detection of apples based on passive thermal imaging technology

High-precision geometric positioning for optical remote sensing satellite in dynamic imaging

ABSTRACT Dynamic imaging of optical remote sensing satellites refers to the active acquisition of images while the satellite is maneuvering at a high angular velocity, which significantly enhances the efficiency and application value of remote sensing imagery. However, due to the influence of rapid maneuvering, the random error of star sensors significantly increases, resulting in a decrease in the geometric positioning accuracy of dynamic imaging remote sensing images. This paper proposes a dynamic fusion method for multisource attitude measurement data based on the noise adaptive estimation and bidirectional filter to achieve high-precision attitude determination and geometric positioning in dynamic imaging. Based on the measurement error model of star sensors, the weights of the star sensor and gyroscope are adaptively adjusted in multisource data fusion to reduce the impact of star sensor measurement errors on the gyroscope. Moreover, a bidirectional fusion filter that includes a low-velocity maneuvering stage is proposed to realize the optimal estimation of the satellite attitude parameter. The simulation data and onboard data of the Luojia3-01 (LJ3–01) satellite were tested to verify the effectiveness of the proposed method. The geometric positioning accuracy of the staring images of LJ3–01 improved from 10.048 m to 7.538 m. The registration accuracy of the sequential images improved from 3.568 pixels to 1.179 pixels. The proposed method can significantly improve the attitude determination accuracy and the geometric positioning accuracy of LJ3–01 satellite staring images. Moreover, for simulation data with various angular velocities, the attitude determination accuracies of the proposed method are better than 0.93”. The experimental results show that the proposed method can achieve high-precision attitude determination in dynamic imaging, reaching the accuracy in the traditional passive imaging.

Passive Source Reverse Time Migration Based on the Spectral Element Method

AbstractIncreasing deployment of dense arrays has facilitated detailed structure imaging for tectonic investigation, hazard assessment and resource exploration. Strong velocity heterogeneity and topographic changes have to be considered during passive source imaging. However, it is quite challenging for ray‐based methods, such as Kirchhoff migration or the widely used teleseismic receiver function, to handle these problems. In this study, we propose a 3‐D passive source reverse time migration strategy based on the spectral element method. It is realized by decomposing the time reversal full elastic wavefield into amplitude‐preserved vector P and S wavefields by solving the corresponding weak‐form solutions, followed by a dot‐product imaging condition to get images for the subsurface structures. It enables us to use regional 3‐D migration velocity models and take topographic variations into account, helping us to locate reflectors at more accurate positions than traditional 1‐D model‐based methods, like teleseismic receiver functions. Two synthetic tests are used to demonstrate the advantages of the proposed method to handle topographic variations and complex velocity heterogeneities. Furthermore, applications to the Laramie array data using both teleseismic P and S waves enable us to identify several south‐dipping structures beneath the Laramie basin in southeast Wyoming, which are interpreted as the Cheyenne Belt suture zone and agree with, and improve upon previous geological interpretations.

Crustal imaging and characterization of active faults with a large-N nodal deployment - Application to the Chaînons Béarnais region (western Pyrenees foothills, France)

Understanding the driving forces and nature of intraplate seismicity remains a major unsolved problem in seismology. In the western Pyrénées, seismicity is concentrated in a narrow region that follows the boundary between the Axial Zone and the North Pyrenean Zone. Despite the presence of a permanent network in the region, the geometry of active faults, and their relationship with crustal structures, remain elusive, owing to significant earthquake location uncertainties. Here, we exploit data recorded by a large-N nodal array deployed in the Chaînons Béarnais region during four weeks of 2022 in order to image crustal structures and characterize active faults. We automatically detected and picked P and S waves with PhaseNet, resulting in a catalog of over 500 events, half of which are located beneath the temporary deployment. Tomographic images obtained from the inversion of P and S arrival times provide detailed insight into the geometry of folds and thrusts in the sedimentary cover, as well as the presence of a main fault in the basement which dips northward with an angle of 65° (Chaînons Béarnais normal fault). Seismicity relocation within the 3D model obtained by tomography shows that earthquakes are concentrated along this main active fault, extending from the top of the basement to a depth of approximately 16 km. These results demonstrate that passive imaging approaches can offer cost-effective alternatives to traditional controlled source imaging for seismotectonic studies and natural resource exploration in regions with active seismicity.

A novel framework for concealed weapons detection using passive terahertz imaging

ABSTRACT In this work, a novel framework for non-destructive, non-intrusive and completely automatic concealed weapon detection under human clothing for entry control and security check applications using passive terahertz (THz) images has been given. The technique models the problem of concealed weapon detection as that of binary segmentation, where the pixels corresponding to concealed weapons are foreground while the remaining are background. The core idea of the proposed framework is to first oversegment the THz image into superpixels and subsequently multiple handcrafted features are extracted from each superpixel. Finally, a machine learning-based classifier is used to perform binary classification thereby classifying each superpixel as foreground or background such that each pixel in a foreground superpixel is a foreground pixel and vice-versa for background. It is worth mentioning that this technique does not require a perfect segmentation to extract features from, rather an oversegmentation suffices. Furthermore, both global features like those based on image saliency and local features like those based on intensity are extracted considering the image properties. The detailed experiments and comparative analysis confirm that the proposed technique efficiently detects concealed weapons, exhibiting superior performance compared to state-of-the-art binary segmentation methods for the purpose.

Improving resolution in passive direct imaging with off-axis aberrations

Imaging systems with off-axis Seidel aberrations are shown to exhibit improved resolution of general object intensity distributions compared to the diffraction-limited system. The Fisher information for the estimation for unknown object intensity values in such systems is greater due to the increased sensitivity of their response to similar object scenes, via shift variance. This improvement in resolution is demonstrated for systems in which image-plane photons have Poisson or additive Gaussian statistics.

Towards Passive Imaging With Uncooled, Low-NEP SiGe HBT Terahertz Direct Detectors

Towards Passive Imaging With Uncooled, Low-NEP SiGe HBT Terahertz Direct Detectors

High‐resolution incoherent interference imaging without phase measurement

AbstractAiming for long‐distance, high‐resolution, passive imaging, we use fiber coupling to replace the spatial coupling of the segmented planar imaging detector for electro‐optical reconnaissance imaging system and propose a novel incoherent interference imaging method, which avoids the problem that the resolution of the imaging system is limited by the size of the silicon wafer. The method uses a phase retrieval algorithm and does not need to measure the phase in the system, effectively avoiding the intrinsic jitter problem of fiber optics. The feasibility of the method in achieving target image reconstruction was verified through simulation; furthermore, an indoor two‐dimensional discrete sampling imaging experiment for a simple four‐rod target was conducted, and an outdoor one‐dimensional feature identification experiment for a two‐rod target was also performed. The results showed that the resolution exceeds the diffraction limit and the reconstruction error of target size is less than 3.5%.

Telescope imaging beyond the Rayleigh limit in extremely low SNR

Abstract The Rayleigh limit and low Signal-to-Noise Ratio (SNR) scenarios pose significant limitations to optical imaging systems used in remote sensing, infrared thermal imaging, and space domain awareness. In this study, we introduce a Stochastic Sub-Rayleigh Imaging (SSRI) algorithm to localize point objects and estimate their positions, brightnesses, and number in low SNR conditions, even below the Rayleigh limit. Our algorithm adopts a maximum likelihood approach and exploits the Poisson distribution of incoming photons to overcome the Rayleigh limit in low SNR conditions. In our experimental validation, which closely mirrors practical scenarios, we focus on conditions with closely spaced sources within the sub-Rayleigh limit (0.49-1.00R) and weak signals (SNR less than 1.2). We use the Jaccard index and Jaccard efficiency as a figure of merit to quantify imaging performance in the sub-Rayleigh region. Our approach consistently outperforms established algorithms such as Richardson-Lucy and CLEAN by 4X in the low SNR, sub-Rayleigh regime. Our SSRI algorithm allows existing telescope-based optical/infrared imaging systems to overcome the extreme limit of sub-Rayleigh, low SNR source distributions, potentially impacting a wide range of fields, including passive thermal imaging, remote sensing, and space domain awareness.

2D spatiotemporal passive cavitation imaging and evaluation during ultrasound thrombolysis based on diagnostic ultrasound platform

Acoustic cavitation plays a critical role in various biomedical applications. However, uncontrolled cavitation can lead to undesired damage to healthy tissues. Therefore, real-time monitoring and quantitative evaluation of cavitation dynamics is essential for understanding underlying mechanisms and optimizing ultrasound treatment efficiency and safety. The current research addressed the limitations of traditionally used cavitation detection methods by developing introduced an adaptive time-division multiplexing passive cavitation imaging (PCI) system integrated into a commercial diagnostic ultrasound platform. This new method combined real-time cavitation monitoring with B-mode imaging, allowing for simultaneous visualization of treatment progress and 2D quantitative evaluation of cavitation dosage within targeted area. An improved delay-and-sum (DAS) algorithm, optimized with a minimum variance (MV) beamformer, is utilized to minimize the side lobe effect and improve the axial resolution typically associated with PCI. In additional to visualize and quantitatively assess the cavitation activities generated under varied acoustic pressures and microbubble concentrations, this system was specifically applied to perform 2D cavitation evaluation for ultrasound thrombolysis mediated by different solutions, e.g., saline, nanodiamond (ND) and nitrogen-annealed nanodiamond (N-AND). This research aims to bridge the gap between laboratory-based research systems and real-time spatiotemporal cavitation evaluation demands in practical uses. Results indicate that this improved 2D cavitation monitoring and evaluation system could offer a useful tool for comprehensive evaluating cavitation-mediated effects (e.g., ultrasound thrombolysis), providing valuable insights into in-depth understanding of cavitation mechanisms and optimization of cavitation applications.

An improved scheme for passive cavitation imaging in high intensity focused ultrasound

Passive cavitation imaging (PCI) is an effective technique for monitoring high intensity focused ultrasound (HIFU) procedure due to the correlation between cavitation activities and the therapeutic effects. Nevertheless, current PCI techniques are unable to recognize noise signals from non-cavitation situations, and they fail to accurately visualize the highly dynamic cavitation activities due to the lack of a stable baseline reference. In this study, a deep learning-based cavitation detection network (CD-NET) was proposed to determine whether passively received channel signals originated from cavitation activities or were merely noises. Additionally, a cavitation intensity baseline was derived to better display the drastically time-varying cavitation activities. The CD-NET model was trained and validated with data collected from in-vitro and ex-vivo HIFU sonication experiments, and then tested by in-vivo rabbit experiments. Both CD-NET models, trained with data from the in-vitro agar phantoms and ex-vivo bovine liver tissues, successfully distinguished between cavitation and non-cavitation activities from the same study object, achieving accuracies as high as 99.7% and 99.5%, respectively. In addition, the models trained on in-vitro and ex-vivo datasets achieved accuracies of 88.1% and 91.4%, respectively, when detecting cavitation events from unseen in-vivo data. The results demonstrate that the improved PCI scheme, utilizing the CD-NET model and a data-derived cavitation baseline, is resistant to noise from non-cavitation situations and can depict the dynamic characteristics of cavitation more reliably. In conclusion, this study addressed two practical challenges in PCI techniques, allowing for better monitoring of cavitation-related HIFU sonication in clinical applications.

Van der Waals mid-wavelength infrared detector linear array for room temperature passive imaging.

Passive imaging for mid-wave infrared (MWIR) is resistant to atmospheric pollutants, guaranteeing image clarity and accuracy. Arrayed photodetectors can simultaneously perform radiation sensing to improve efficiency. Room temperature van der Waals (vdWs) photodetectors without lattice matching have evolved rapidly with optimized stacking methods, primarily for single-pixel devices. The urgent need to implement arrayed devices aligns with practical demands. Here, we present an 8 by 1 black phosphorus/molybdenum sulfide (BP/MoS2) vdWs photodetector linear array with a fill-factor of ~77%, fabricated using a temperature-assisted sloping transfer method. The flat interface and uniform thickness facilitate carrier transport and minimize pixel nonuniformities, showing an average peak detectivity (D*) of 2.34 × 109 cm·Hz1/2·W-1 in the mid-wave infrared region. Compared to a single pixel, push-broom scanning passive imaging is eight times more efficient and further enhanced through mean filtering and fast Fourier transform filtering for strip noise correction. Our study offers guidance on vdWs arrayed devices for engineering applications.

Seafloor Rayleigh ellipticity, measured from unoriented data, and its significance for passive seismic imaging in the ocean

SUMMARY Observations of the seafloor Rayleigh ellipticity contribute to seismic imaging in the ocean. To extract such observables from the arbitrarily oriented ocean–bottom seismometer (OBS) data, we develop an orthogonal-regression-based approach to measure the waveform amplitude ratios of the unoriented horizontal and vertical components. The amplitude ratios are then used to calculate the Rayleigh ellipticity (and the sensor orientation angle). The robustness of our method is verified by applications to both the unoriented OBS data and the well oriented on-land seismic data. As we propose to calculate the Rayleigh ellipticity directly from the unoriented three-component data, the measurement process avoids the complexity arising from the surface wave non-great-circle effects and uncertainties of the OBS sensor orientation angles. Overall the Rayleigh ellipticity measurements from our method are systematically higher than those by conventional analysis and show less uncertainties. Our analyses suggest that the Rayleigh ellipticity curve (14–60 s), which could be retrieved from the raw broad-band OBS data, is effective to constrain the oceanic lithosphere structure, and the accurate measurement of Rayleigh ellipticity curve is important. The potential of seafloor Rayleigh ellipticity for seismic imaging in the ocean is evidenced by a case study of the Japan Basin, the Sea of Japan. Considering the insufficient station coverage in the ocean, the single-station measurement of seafloor Rayleigh ellipticity is of significance for OBS community.

A Case Study of 2D Bi2O2Se Nanoplate Near‐Infrared Photodetectors from the Perspective of Practical Applications

AbstractOver the past several decades infrared (IR) photodetectors have received wide attention due to their important applications. 2D materials, distinguished by their unique electronic structures, ultimate dimensional confinement, and robust light‐matter interactions, provide a promising candidate for fabricating future IR photodetectors. However, there is a lack of reports concerning the practical industrial applications of these 2D photodetectors, despite that some of these 2D photodetectors have demonstrated performance exceeding that of commercial photodetectors. In this work, a case study on 2D Bi2O2Se nanoplate near‐infrared photodetectors from the perspective of practical applications is presented. With the characterization method used for nano detectors, the 2D Bi2O2Se photodetector exhibits a responsivity of 212.5 A W−1, a specific detectivity of 4.99 × 1011 Jones and an external quantum efficiency of 26 887.68% at wavelength of 980 nm, while with the traditional characterization method the photodetector shows a responsivity of 0.13 A W−1 and a specific detectivity of 2.26 × 106 Jones and an external quantum efficiency of 17.87% at wavelength of 900 nm. The Bi2O2Se nanoplate photodetector also presents good passive imaging quality in the near‐infrared wavelength region. These results suggest the great potential of Bi2O2Se nanoplate photodetectors for practical applications.

Passive imaging through inhomogeneous scattering media

According to the atmospheric scattering model (ASM), the object signal’s attenuation diminishes exponentially as the imaging distance increases. This imposes limitations on ASM-based methods in situations where the scattering medium one wish to look through is inhomogeneous. Here, we extend ASM by taking into account the spatial variation of the medium density, and propose a two-step method for imaging through inhomogeneous scattering media. In the first step, the proposed method eliminates the direct current component of the scattered pattern by subscribing to the estimated global distribution (background). In the second step, it eliminates the randomized components of the scattered light by using threshold truncation, followed by the histogram equalization to further enhance the contrast. Outdoor experiments were carried out to demonstrate the proposed method.

Investigation of quantitative precursory indicators for rock failure using spatio-temporal characteristics of velocity

Stress redistribution and crack development are prominent features in rock failure. However, these processes are complex and challenging to analyze, making early warning of instability in rock engineering difficult. To characterize the rock failure process and obtain reliable precursory indicators, the imaging method that combines active and passive sources was employed to construct the velocity field during the rock failure process in this study. The micro-crack propagation law and its potential connection with the stress environment were investigated by mapping the velocity field, the acoustic emission (AE) density field, and the energy field. Moreover, the Mutation Trend Coefficient (MTC) and Deformation Coefficient (DC) were proposed as precursory indicators of instability based on the spatio-temporal correlation and directional differences of velocity evolution. Results show that the nucleation of AE sources and the release of energy accumulation are key to the formation of the velocity gradient, and progressive rock failure is accompanied by the intensification of velocity anisotropy. Additionally, low-velocity regions usually preferentially extend in the direction parallel to the principal stress, while expansion in the direction vertical to the principal stress is dominant in the plastic stage, indicating that the stress environment controls the spatial heterogeneity of the velocity field. The evolution trend of precursor indicators shows that the increase of MTC from a low value and the continuous decrease of DC can be regarded as the initiation of rock secondary cracks. The proposed indicators and method not only provide beneficial complements to the understanding of the evolution mechanism of rock damage but also have potential in the early warning and identification of the early stage of crack propagation, offering references for the safety prevention and control of rock engineering disasters.

Bayesian cloud-top phase determination for Meteosat Second Generation

Abstract. A comprehensive understanding of the cloud thermodynamic phase is crucial for assessing the cloud radiative effect and is a prerequisite for remote sensing retrievals of microphysical cloud properties. While previous algorithms mainly detected ice and liquid phases, there is now a growing awareness for the need to further distinguish between warm liquid, supercooled and mixed-phase clouds. To address this need, we introduce a novel method named ProPS (PRObabilistic cloud top Phase retrieval for SEVIRI), which enables cloud detection and the determination of cloud-top phase using SEVIRI (Spinning Enhanced Visible and Infrared Imager), the geostationary passive imager aboard Meteosat Second Generation. ProPS discriminates between clear sky, optically thin ice (TI) cloud, optically thick ice (IC) cloud, mixed-phase (MP) cloud, supercooled liquid (SC) cloud and warm liquid (LQ) cloud. Our method uses a Bayesian approach based on the cloud mask and cloud phase from the lidar–radar cloud product DARDAR (liDAR/raDAR). The validation of ProPS using 6 months of independent DARDAR data shows promising results: the daytime algorithm successfully detects 93 % of clouds and 86 % of clear-sky pixels. In addition, for phase determination, ProPS accurately classifies 91 % of IC, 78 % of TI, 52 % of MP, 58 % of SC and 86 % of LQ clouds, providing a significant improvement in accurate cloud-top phase discrimination compared to traditional retrieval methods.

Dynamics of thermal plumes for large spaces: A comparative study of in-situ smoke test and a CFD model

This study focuses on natural convection heat transfer in building heating and ventilation. Amid advancements in natural ventilation and a changing energy landscape, innovative heating methods are crucial. Thermal radiators play a key role in enhancing heat convection and understanding thermal plumes to optimize heating efficiency.This study investigates the use of coloured smoke sources to visualize thermal plume flow fields in real-scale (in-situ), naturally ventilated large spaces, distinguishing itself from most studies that prioritize enhancing thermal efficiency radiator. It offers a way for both qualitative and quantitative validation of a CFD model using passive scalars and experimental images to illustrate thermal plume propagation. This novel approach provides an effective way to visualize and understand thermal plumes in spaces where other experimental techniques are challenging to implement.Experimental results showed high consistency between measured and CFD values for velocity, temperature, and heat exchange, with differences below 10 %. The study unveiled a low impact of initial smoke source velocities on plume visualization. Using coloured smoke images to validate the CFD model yielded errors from 2.3 % to 14.5 %, proving the method’s reliability for both qualitative and quantitative analysis of plume propagation, offering valuable insights into air propagation in naturally ventilated spaces.

High repetition-rate dual-channel X-ray spectrometer for high-intensity laser-plasma experiments.

We describe the development and demonstration of a high-repetition-rate-capable dual-channel (DC) x-ray spectrometer designed for high-intensity laser-plasma experiments (≥1×1021 W/cm2). The spectrometer, which operates at high repetition rates, is limited only by the refresh rate of targets and the camera's frame rate. It features two channels, each equipped with a flat highly oriented pyrolytic graphite (HOPG) crystal and a unique detector plane, allowing it to resolve two distinct x-ray bands: approximately 7-10 and 10-13keV. Each detector plate carrier holds two slots for active (scintillators) or passive (imaging plates) x-ray detectors. We present the design and testing of the HR-DC-HOPG using both the COMET laser (10J, 0.5ps shot/4min) at LLNL's Jupiter Laser Facility and the SCARLET laser (10J, 30fs shot/min) at Ohio State University. The results demonstrate the spectrometer's performance across various laser energies, target materials, pulse shapes, and detector types.