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In this paper, an ultra-fast smart vision system-on-a-chip design is proposed to provide effective solutions for real time machine vision applications by taking advantages of recent advances in integrated sensing/processing designs, electronic neural networks, advanced microprocessors and sub-micron VLSI technology.
Space-based gamma-ray telescopes such as the Fermi Large Area Telescope have used single sided silicon strip detectors to measure the position of incident gamma-rays with high resolution. At lower energies, two dimensional position information within a single detector is required. This talk investigates the use of monolithic CMOS active pixel silicon sensors –AstroPix – as a novel technology for use in future gamma-ray telescopes. Based upon detectors designed for use in the ATLAS detector at the LHC, AstroPix has the potential to maintain the high energy and angular resolution required of a medium-energy gamma-ray telescope while reducing noise with the dual detection and readout capabilities of a CMOS chip. The status of AstroPix development and testing, as well as outlook for application in future telescopes such as the proposed medium-energy gamma-ray telescope AMEGO-X, will be presented.
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NASA Hubble Space Telescope (HST) and upcoming cosmology science missions carry instruments with multiple focal planes populated with many large sensor detector arrays. These sensors are passively cooled to low temperatures for low-level light (L3) and near-infrared (NIR) signal detection, and the sensor readout electronics circuitry must perform at extremely low noise levels to enable new required science measurements. Because we are at the technological edge of enhanced performance for sensors and readout electronics circuitry, as determined by thermal noise level at given temperature in analog domain, we must find new ways of further compensating for the noise in the signal digital domain. To facilitate this new approach, state-of-the-art sensors are augmented at their array hardware boundaries by non-illuminated reference pixels, which can be used to reduce noise attributed to sensors. There are a few proposed methodologies of processing in the digital domain the information carried by reference pixels, as employed by the Hubble Space Telescope and the James Webb Space Telescope Projects. These methods involve using spatial and temporal statistical parameters derived from boundary reference pixel information to enhance the active (non-reference) pixel signals. To make a step beyond this heritage methodology, we apply the NASA-developed technology known as the Hilbert- Huang Transform Data Processing System (HHT-DPS) for reference pixel information processing and its utilization in reconfigurable hardware on-board a spaceflight instrument or post-processing on the ground. The methodology examines signal processing for a 2-D domain, in which high-variance components of the thermal noise are carried by both active and reference pixels, similar to that in processing of low-voltage differential signals and subtraction of a single analog reference pixel from all active pixels on the sensor. Heritage methods using the aforementioned statistical parameters in the digital domain (such as statistical averaging of the reference pixels themselves) zeroes out the high-variance components, and the counterpart components in the active pixels remain uncorrected. This paper describes how the new methodology was demonstrated through analysis of fast-varying noise components using the Hilbert-Huang Transform Data Processing System tool (HHT-DPS) developed at NASA and the high-level programming language MATLAB (Trademark of MathWorks Inc.), as well as alternative methods for correcting for the high-variance noise component, using an HgCdTe sensor data. The NASA Hubble Space Telescope data post-processing, as well as future deep-space cosmology projects on-board instrument data processing from all the sensor channels, would benefit from this effort.
Switching and amplifying characteristics of a newly developed monolithic InGaAs Active Pixel Imager Array are presented. The sensor array is fabricated from InGaAs material epitaxially deposited on an InP substrate.
Modulation Transfer Function (MTF) is an important figure of merit in focal plane array sensors, especially for accurate target positions such as star trackers.
Synthetic Foveal imaging Technology (SyFT) is an emerging discipline of image capture and image-data processing that offers the prospect of greatly increased capabilities for real-time processing of large, high-resolution images (including mosaic images) for such purposes as automated recognition and tracking of moving objects of interest. SyFT offers a solution to the image-data processing problem arising from the proposed development of gigapixel mosaic focal-plane image-detector assemblies for very wide field-of-view imaging with high resolution for detecting and tracking sparse objects or events within narrow subfields of view. In order to identify and track the objects or events without the means of dynamic adaptation to be afforded by SyFT, it would be necessary to post-process data from an image-data space consisting of terabytes of data. Such post-processing would be time-consuming and, as a consequence, could result in missing significant events that could not be observed at all due to the time evolution of such events or could not be observed at required levels of fidelity without such real-time adaptations as adjusting focal-plane operating conditions or aiming of the focal plane in different directions to track such events. The basic concept of foveal imaging is straightforward: In imitation of a natural eye, a foveal-vision image sensor is designed to offer higher resolution in a small region of interest (ROI) within its field of view. Foveal vision reduces the amount of unwanted information that must be transferred from the image sensor to external image-data-processing circuitry. The aforementioned basic concept is not new in itself: indeed, image sensors based on these concepts have been described in several previous NASA Tech Briefs articles. Active-pixel integrated-circuit image sensors that can be programmed in real time to effect foveal artificial vision on demand are one such example. What is new in SyFT is a synergistic combination of recent advances in foveal imaging, computing, and related fields, along with a generalization of the basic foveal-vision concept to admit a synthetic fovea that is not restricted to one contiguous region of an image.
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The first innovative Visible Infrared Imaging Radiometer Suite (VIIRS) sensor aboard the Suomi National Polar-orbiting Partnership (SNPP) satellite has been in operation for 10 years since its launch on 28 October 2011. The second VIIRS sensor aboard the first Join Polar Satellite System (JPSS-1) satellite has been in operation for 4 years since its launch on 18 November 2017, which became NOAA-20. Well-geolocated and radiometrically calibrated Level-1 sensor data records (SDRs) from VIIRS are crucial to numerical weather prediction (NWP) and Level-2+ environmental data record (EDR) algorithms and products. The high quality of Level-2+ EDRs is a requirement for the continuity of NASA Earth science data records (ESDRs) and climate data records (CDRs), one of the two objectives of the SNPP mission and one of the three elements in the JPSS mission objective. The other objective of the SNPP mission is risk reduction for the follow-on JPSS missions. This paper summarizes the on-orbit geolocation calibration and validation (Cal/Val) activities for both VIIRS sensors onboard SNPP and NOAA-20 in the past 10 years. These activities include nominal geolocation Cal/Val activities, risk reduction activities, and improvements for the on-orbit VIIRS sensor operations. After these activities, sub-pixel geolocation accuracy is achieved. Nadir equivalent geolocation uncertainty is generally within 75 m (1-σ), or 20% imagery band pixels, in either the along-scan or along-track direction for both SNPP and NOAA-20 VIIRS sensors. The worst 16-day measured geolocation errors (radial, 3-σ) are 280 m and 267 m, respectively, in the latest SNPP and NOAA-20 VIIRS data collections, which are better than the required accuracy of 375 m (radial, 3-σ). The risk reduction activities also improved VIIRS builds for JPSS-3 and JPSS-4 satellites, and provide lessons learned for other VIIRS-like sensor builds.
To cope with the challenging environment of the planned high luminosity upgrade of the Large Hadron Collider (HL-LHC), scheduled to start operation in 2029, CMS will replace its entire tracking system. The requirements for the tracker are largely determined by the long operation time of 10 years with an instantaneous peak luminosity of up to 7.5 × 10 34 cm –2 s –1 in the ultimate performance scenario. Depending on the radial distance from the interaction point, the silicon sensors will receive a particle fluence corresponding to a non-ionizing energy loss of up to $\Phi_{\text {eq}}$ = 3.5 × 10 16 cm –2 . Here this paper focuses on planar pixel sensor design and qualification up to a fluence of $\Phi_{\text {eq}}$ = 1.4 × 10 16 cm –2 . For the development of appropriate planar pixel sensors an R&D program was initiated, which includes $n^+ -p$ sensors on 150 mm (6”) wafers with an active thickness of 150 μm with pixel sizes of 100 × 25 μm 2 and 50 × 50 μm 2 manufactured by Hamamatsu. Single chip modules with ROC4Sens and RD53A readout chips were made. Irradiation with protons and neutrons, as well was an extensive test beam campaign at DESY were carried out. This paper presents the investigation of various assemblies mainly with ROC4Sens readout chips. It demonstrates that multiple designs fulfill the requirements in terms of breakdown voltage, leakage current and efficiency. The single point resolution for 50 × 50 μm 2 pixels is measured as 4.0 μm for non-irradiated samples, and 6.3 μm after irradiation to $\Phi_{\text {eq}}$ = 7.2 × 10 15 cm –2 .
A set of cloud retrieval algorithms developed for CERES and applied to MODIS data have been adapted to analyze other satellite imager data in near-real time. The cloud products, including single-layer cloud amount, top and base height, optical depth, phase, effective particle size, and liquid and ice water paths, are being retrieved from GOES- 10/11/12, MTSAT-1R, FY-2C, and Meteosat imager data as well as from MODIS. A comprehensive system to normalize the calibrations to MODIS has been implemented to maximize consistency in the products across platforms. Estimates of surface and top-of-atmosphere broadband radiative fluxes are also provided. Multilayered cloud properties are retrieved from GOES-12, Meteosat, and MODIS data. Native pixel resolution analyses are performed over selected domains, while reduced sampling is used for full-disk retrievals. Tools have been developed for matching the pixel-level results with instrumented surface sites and active sensor satellites. The calibrations, methods, examples of the products, and comparisons with the ICESat GLAS lidar are discussed. These products are currently being used for aircraft icing diagnoses, numerical weather modeling assimilation, and atmospheric radiation research and have potential for use in many other applications.
The High Luminosity upgrade of the CERN LHC collider (HL-LHC) demands a new high-radiation–tolerant solid-state pixel sensor capable of surviving fluencies up to a few 10$^{16} n_{eq}/\mathrm{cm}^2$ at ~ 3 cm from the interaction point. To this extent the INFN ATLAS-CMS joint research activity, in collaboration with Fondazione Bruno Kessler (FBK), is aiming at the development of thin n -in- p –type pixel sensors for the HL-LHC. The R&D covers both planar and single-sided 3D columnar pixel devices made with the Si-Si Direct Wafer Bonding technique, which allows for the production of sensors with 100 μm and 130 μm active thickness for planar sensors, and 130 μm for 3D sensors, the thinnest ones ever produced so far. The first prototypes of hybrid modules, bump-bonded to the present CMS readout chip, have been tested on beam. The first results on their performance before and after irradiation are presented
The High Luminosity upgrade of the CERN-LHC (HL-LHC) demands for a new high-radiation tolerant solid-state pixel sensor capable of surviving fluencies up to a few 10 16 particles/cm 2 at ~3 cm from the interaction point. To this extent the INFN ATLAS-CMS joint research activity, in collaboration with Fondazione Bruno Kessler-FBK, is aiming at the development of thin n-in-p type pixel sensors for the HL-LHC. The R&D covers both planar and single-sided 3D columnar pixel devices made with the Si-Si Direct Wafer Bonding technique, which allows for the production of sensors with 100 μm and 130 μm active thickness for planar sensors, and 130 μm for 3D sensors, the thinnest ones ever produced so far. The first prototypes of hybrid modules bump-bonded to the present CMS and ATLAS readout chips have been tested in beam tests. Furthermore, the preliminary results on their performance before and after irradiation are presented.
This paper reports on the INFN (Istituto Nazionale di Fisica Nucleare, Italy) research activity in collaboration with FBK foundry, which is aiming at the development of new pixel detectors for the LHC Phase-2 upgrades. The R&D covers both planar pixel devices and 3D detectors built using columnar technology. All sensors are low thickness n-in-p type, as this is the general direction envisaged for the High Luminosity LHC pixel detector upgrades. Hybrid modules with 100 $\upmu $ m and 130 $\upmu $ m active thickness, connected to the PSI46dig readout chip, have been tested on beam test experiments. Selected preliminary results from test beams are described for both planar and 3D devices. The results on the 3D pixel sensors before irradiation are very satisfactory and support the conclusion that columnar devices are very good candidates for the inner layers of the upgrade pixel detectors.
Facing direction detection plays a critical role in human-computer interaction and has a wide application in surveillance systems, driving awareness recognition, smart home appliances, computer games, and so on. Current detection methods are mainly focused on extracting specific patterns from user's optical images, which raises concerns on privacy invasion and these detection techniques do not usually work in a dark environment. To address these concerns, here this paper proposes an activity recognition system guided by an unobtrusive sensor (ARGUS). By using a low pixel infrared thermopile array sensor, ARGUS is capable of identifying five facing directions (left 45°/90°, right 45°/90°, and front) through the support vector machine classifier. Also two feature extraction methods are compared. One is manually-defined and the other is based on a pre-trained convolutional neural network (CNN) model. The facing direction detection accuracy resulting from manually-defined features reaches 85.3%, 90.6%, and 85.2% at detection distance of 0.6, 1.2, and 1.8 m, respectively. The level of accuracy resulted from using pre-trained CNN features demonstrates a much more reliable performance (89.1%, 95.3%, and 95.1% at distance of 0.6, 1.2, and 1.8 m, respectively). In addition, ARGUS has been successfully applied for occupancy tracking with a root mean square error of 0.19 m.
The High-Luminosity LHC (HL-LHC) upgrade of the CMS pixel detector will require the development of novel pixel sensors which can withstand the increase in instantaneous luminosity to L = 5 × 10 34 cm –2 s –1 and collect ~ 3000fb –1 of data. The innermost layer of the pixel detector will be exposed to doses of about 10 16 n eq / cm 2 . Hence, new pixel sensors with improved radiation hardness need to be investigated. A variety of silicon materials (Float-zone, Magnetic Czochralski and Epitaxially grown silicon), with thicknesses from 50 μm to 320 μm in p-type and n-type substrates have been fabricated using single-sided processing. The effect of reducing the sensor active thickness to improve radiation hardness by using various techniques (deep diffusion, wafer thinning, or growing epitaxial silicon on a handle wafer) has been studied. Furthermore, the results for electrical characterization, charge collection efficiency, and position resolution of various n-on-p pixel sensors with different substrates and different pixel geometries (different bias dot gaps and pixel implant sizes) will be presented.
Multimodal biometric verification is increasingly applied across operational contexts ranging from close-range security cameras and building-mounted surveillance to long-range ground sensors and unmanned aerial system (UAS) imagery. Variations in acquisition conditions—such as image resolution, viewing geometry, and motion artifacts—pose significant challenges for cross-domain algorithmic generalization. This study evaluates two independent multimodal biometric verification systems developed under the Intelligence Advanced Research Projects Activity (IARPA) Biometric Recognition and Identification at Altitude and Range (BRIAR) program, comparing performance on close-range and aerial datasets. Close-range video served as a baseline to quantify the decline in verification performance on aerial footage. The dataset included six UAS platforms, spanning small quadcopters at 10m altitude to medium-sized fixed-wing aircraft at 360m. Mixed-effects logistic regression identified image resolution (head and body pixel counts), head height, sensor characteristics, and algorithm selection as primary determinants of verification success, whereas demographic attributes and mission gait were not significant predictors. Activity type and collection site influenced performance in close-range data but had negligible impact on UAS imagery. These results clarify modality-specific strengths and limitations and highlight opportunities to enhance cross-domain biometric verification.
Purpose: The purpose of this work is to simulate a multi-focus plenoptic camera used as the measuring device in a real-time three-dimensional scintillation dosimeter. Simulating and optimizing this realistic optical system will bridge the technological gap between concept validation and a clinically viable tool that can provide highly efficient, accurate and precise measurements for dynamic radiotherapy techniques. Methods: The experimental prototype, previously developed for proof of concept purposes, uses an off-the-shelf multi-focus plenoptic camera. With an array of interleaved microlenses of different focal lengths, this camera records spatial and angular information of light emitted by a plastic scintillator volume. The three distinct microlens focal lengths were determined experimentally for use as baseline parameters by measuring image-to-object magnification for different distances in object space. A simulated plenoptic system was implemented using the non-sequential ray tracing software Zemax: this tool allows complete simulation of multiple optical paths by modeling interactions at interfaces such as scatter, diffraction, reflection and refraction. The active sensor was modeled based on the camera manufacturer specifications by a 2048×2048, 5 µm-pixel pitch sensor. Planar light sources, simulating the plastic scintillator volume, were employed for ray tracing simulations. Results: The microlens focal lengths were determined to be 384, 327 and 290 µm. A realistic multi-focus plenoptic system, with independently defined and optimizable specifications, was fully simulated. A f/2.9 and 54 mm-focal length Double Gauss objective was modeled as the system’s main lens. A three-focal length hexagonal microlens array of 250-µm thickness was designed, acting as an image-relay system between the main lens and sensor. Conclusion: Simulation of a fully modeled multi-focus plenoptic camera enables the decoupled optimization of the main lens and microlens specifications. This work leads the way to improving the 3D dosimeter’s achievable resolution, efficiency and build for providing a quality assurance tool fully meeting clinical needs. M.R. is financially supported by a Master’s Canada Graduate Scholarship from the NSERC. This research is also supported by the NSERC Industrial Research Chair in Optical Design.