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This PDF file contains the front matter associated with SPIE Proceedings Volume 13030, including the Title Page, Copyright information, Table of Contents, and Conference Committee information.
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Tunable optical materials can enable more functionality while maintaining flexibility in a single aperture, which is relevant to making visible and infrared image sensing more context aware. DARPA’s Accelerating discovery of Tunable Optical Materials (ATOM) program is exploring fundamental insights into the physics of tunable optical materials with the goal of developing new materials for optic and photonic applications. The specific characteristics of interest are a large change in refractive index (Δn) to delay light, low loss for high transmissivity (k), and fast switching speeds. Rare earth nickelates and phase change materials, integrated with machine learning to accelerate insights into new materials, show initial promise toward the ATOM program goals.
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In this presentation, we will report our recent efforts in achieving high performance in Antimonides type-II superlattice (T2SL) based infrared photodetectors using the barrier infrared detector (BIRD) architecture. The high operating temperature (HOT) BIRD focal plane arrays (FPAs) offer the same high performance, uniformity, operability, manufacturability, and affordability advantages as InSb. However, mid-wavelength infrared (MWIR) HOT-BIRD FPAs can operate at significantly higher temperatures (>150K) than InSb FPAs (typically 80K). Moreover, while InSb has a fixed cutoff wavelength (~5.4 µm), the HOT-BIRD offers a continuous adjustable cutoff wavelength, ranging from ~4 µm to >15 µm, and is therefore also suitable for long wavelength infrared (LWIR) as well. The LWIR detectors based on the BIRD architecture has also demonstrated significant operating temperature advantages over those based on traditional p-n junction designs. HyTI (Hyperspectral Thermal Imager) and c-FIRST (compact Fire Infrared Radiance Spectral Tracker) based on JPL's T2SL BIRD FPAs. Based on III-V compound semiconductors, the BIRD FPAs offer a breakthrough solution for the realization of low cost (high yield), high-performance FPAs with excellent uniformity and pixel-to-pixel operability.
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A NASA Advanced Component Technology (ACT) program targeted development of electron avalanche photodiodes (eAPDs) that spanned the 500 nm to 2500 nm spectral range. This ACT task leveraged an existing eAPD that are used by astronomers and other NASA programs. However, the existing eAPD cut-on wavelength starts at 800 nm, due to the CdTe buffer layer through which photons have to traverse prior to reaching the HgCdTe absorber layer. This ACT task extended the eAPD detectors cut-on wavelength down to the visible wavelength range, which required the removal of the GaAs substrate and the CdTe buffer layer. The most challenging portion of the project was the development of a passivation layer at the illuminating surface that transmits photons between 500 nm and 2500 nm, while minimizing surface recombination velocity at the surface to maintain low dark current. The baseline was to demonstrate an eAPD with 500 nm cuton wavelength, with a goal of extending the cut-on wavelength into UV. A critical task on the program was development of a passivation process to drive minority carriers away from the passivant/HgCdTe interface towards the gain region. Two potential passivants were investigated. Results of the experiments showed one variant gave the best results and has been chosen as the deposition method. Progress was made in the development of visible to SWIR APDs in that QE was measured to be flat across the 500 nm to 2500 nm band but was low ~ 15% for one of the arrays. Another APD array had QE as high as 28%. The contention is that etching for the two arrays was different resulting in different HgCdTe absorber thickness values. Low QE is probably because the thickness of the absorber may be approximately equal to or longer than the diffusion length. Consequently, the thinner absorber regions result in higher QE, whereas the thicker absorber region of the array result in lower QE. Gain as a function of bias was measured and gain M ranged from ~ 25 to 50 at 10 V bias exceeding the M = 10 at 10 V requirement. Improving QE in the future will be by etching further into the HgCdTe absorber. This will reduce the distance that the carriers have to diffuse to reach the junction and should increase the QE.
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Single photon sensitive detectors, such as avalanche photo diodes, require optical components to concentrate incident light onto the relatively small active area of each individual pixel. These concentrators have traditionally taken the form of micro-lens arrays (MLA). However, the existing manufacturing processes limit the achievable f-number for these micro-lenses, which in turn limits the maximum achievable acceptance angle of the front-end optical system. Microcompound parabolic concentrators (µCPC), similar to those used in solar arrays, provide an alternate design to microlens arrays that can enable greater light collection for detectors from faster optical system front ends. The µCPC design is fully reflective, wavelength agnostic, and the acceptance f-number is limited only by the detector active area and pixel pitch, making them ideal for fast, low SWaP optical systems. This paper provides an overview of design and fabrication techniques for the optical concentrators.
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The peculiar properties of quantum optical states represent a new resource for innovative imaging schemes, as sub shot noise imaging or quantum illumination. In particular, quantum entanglement and squeezing have significantly improved phase estimation and imaging in interferometric settings beyond the classical limits. In this proceeding, after a general introduction, I will describe part of the recent work on quantum imaging performed in INRIM concerning phase imaging and light field ghost imaging.
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With their recognized advantages such as system-level size, weight and power (SWaP) benefits, minimal monochromatic aberration, polarization discrimination capacity, and low-cost at scale, metasurfaces have emerged as a transformative optics technology. Optical distortion, an important metric in many optical design specifications, has however rarely been discussed in the context of metalens optics. Here we present we present a generic approach for on-demand distortion correction using wide field-of-view (FOV) compound metalenses.
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If a U.S. Air Force operated airfield is attacked, the current methodology for assessing its condition is a slow manual inspection process, exposing personnel to dangerous conditions. Advances in drone technology, remote sensing, deep learning, and computer vision have sparked interest in developing autonomous remote solutions. While digital image processing techniques have matured in recent decades, a lack of application-specific training data presents significant obstacles for developing reliable solutions to detect specific objects amongst rubble, debris, variations in pavement types, changing surface features, and other variable runway conditions. Consequently, near-surface hyperspectral imaging has been proposed as an alternative to RGB digital images, due to its discriminatory power in classifying materials. Spatio-spectral data acquired by hyperspectral imagers help address common challenges presented by data scarcity and scene complexity; however, raw data acquired by hyperspectral sensors must first undergo a reflectance correction process before it can be of use. This paper presents an expedient method, tailored to airfield damage assessment, for performing autonomous reflectance correction on near-surface hyperspectral data using in-scene pavement materials with a known spectral reflectance. Unlike most reflectance correction methods, this process eliminates the need for human intervention with the sensor (or its data) pre or post flight and does not require pre-staged reference targets or an additional downwelling irradiance sensor. Positive initial results from real-world flights over pavements are presented and compared to traditional methods of reflectance correction. Three separate flight tests report mean errors between 2% and 2.5% using the new method.
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Polarimetry is pivotal in analyzing light's polarization properties, with vast potential in areas like remote sensing, material analysis, biological imaging, medical diagnostics, and defense. Metasurfaces, finely engineered to control light's phase, amplitude, and polarization, present an innovative platform to augment polarized light examination. This study delves into the design, fabrication, and practical demonstration of these metasurfaces, showcasing their use in polarization demultiplexing and subsequent imaging reconstruction. Experimentally, we used metasurfaces to observe an underwater scene under varied polarized light sources. This allows the selective capture of distinct polarizations simultaneously, elevating the accuracy of polarimetric measurements. A more in-depth discussion on image reconstruction via Stokes parameters is provided.
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This article addresses the imperative of reducing the limit-of-detection (LoD) in sensing systems, focusing on micro- and nanoelectromechanical (MEM/NEM) resonant technologies. Typically, advancements on MEM/NEM offer high sensitivity and electromechanical performance, which is crucial for achieving quantum-limited LoD. However, when these devices are integrated in closed-loop oscillator, frequency fluctuations are introduced due to electrical noise, degrading the LoD. This work proposes a novel sensing system for Aluminum Scandium Nitride (AlScN) microacoustic resonant infrared (IR) detectors that addresses these challenges. Moreover, it enables self-sustained oscillation states without active components, while consuming minimal power (∼10 mW) and limiting RF power dissipation (≤ 1 µW), thus shaping a new paradigm in sensing technology.
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We propose to achieve sensitive, low-noise, and fast detection of incoherent thermal photons using a novel optomechanical spring sensing principle. In this unique active sensing approach, the coherent optomechanical oscillation (OMO) greatly amplifies the long-wavelength-infrared (LWIR)-induced eigenspectrum modification, leading to a noise-equivalent power (NEP) of < 0.03pW/Hz1/2. Meanwhile, our detection signal bandwidth is only determined by the frequency-demodulation circuit, which can reach > 100kHz. Both performance parameters are revolutionary and significantly above the current state of the art. Our success, based on mature photonic integrated circuit platforms, can easily scale up to multipixel arrays.
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This study describes a measurement-optimized parametric model of diffuse reflectance, based on the reduction of absorption spectra for Near Infrared (NIR) and Short-Wave Infrared (SWIR) absorbing dyes on substrates using critical feature isolation and projection. The critical features are identified through a structural analysis of the peaks, troughs, and points of inflection within the Kubelka-Munk absorption spectra, which is calculated from diffuse reflectance measurements. These critical features are then parameterized and projected into a reduced feature subspace using Lorentzian decompositions to effectively capture the fundamental characteristics of the absorbing dyes, while removing processing and measurement noise. A Kramers-Kronig analysis then characterizes the dielectric responses and provides an estimation of the reduced spectra reflectance. The model parameters for the analytical reduction are further refined using a nonlinear multivariable optimization function between the analytically predicted reflectance and the measured reflectance.
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The Sharjah Academy for Astronomy, Space Sciences, and Technology (SAASST) is developing an Earth observation mission called Sharjah-Sat-2, a 6-U CubeSat with a high-resolution hyperspectral camera and 5 meters Ground Sampling Distance (GSD). The mission's main goal is to deliver reliable information for applications in remote sensing and sustainable urban development projects. Frequently, a group of satellites working together, rather than one satellite, are needed for space missions. Thus, implementing a satellite constellation is essential to enhance the reliability and latency of the collected data. Several factors influence the selection of the number of satellites, so a constellation of tens, hundreds, or even thousands of satellites can be implemented depending on the type and requirements of the mission. Few satellites are needed for educational and scientific missions, while for commercial purposes, hundreds would not be enough. By varying the number of satellites in the constellation (4, 8, and 12 satellites), three different CubeSat constellation scenarios were simulated using Systems Tool Kit (STK) software designating Sharjah-Sat-2 as the reference satellite in the constellation. This paper focused on the STK simulation analysis, emphasizing how crucial constellation configurations play in optimizing Earth observation mission performance, including the pass frequency, area coverage, revisit time, and image latency. In summary, the results show that larger constellations offer greater coverage, more frequent visits to the targeted area, and greater imaging potential.
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This work describes a novel hyperspectral imaging system for the long-wave infrared domain. Being a spectral scanner, it is more versatile compared to single-point and push-broom techniques, which require relative movement between instrument and sample to acquire an image. The imager is equipped with a 1024×768-pixel uncooled microbolometer sensor, which is sensitive to wavelengths in the range from 8 to 14 µm. A scanning Fabry-Pérot interferometer is placed in front of the collecting optics. The distance between its two mirrors determines the distribution of wavelengths entering the system. By capturing images at different mirror separation distances, a hyperspectral data cube is formed. The spectral information provided in such a hyperspectral data cube can i.a. be used for material classification, as here demonstrated with an example of different gemstones.
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Synthetic Aperture Radar (SAR) Automatic Target Recognition (ATR) is a key technique used in military applications like remote-sensing image recognition. Vision Transformers (ViTs) are the state-of-the-art in various computer vision applications, outperforming Convolutional Neural Networks (CNNs). However, using ViTs for SAR ATR applications is challenging due to (1) standard ViTs require extensive training data to generalize well due to their low locality. The standard SAR datasets have a limited number of labeled training data, reducing the learning capability of ViTs (2) ViTs have a high parameter count and are computation intensive which makes their deployment on resource-constrained SAR platforms difficult. In this work, we develop a lightweight ViT model that can be trained directly on small datasets without pre-training. To this end, we incorporate the Shifted Patch Tokenization (SPT) and Locality Self-Attention (LSA) modules into the ViT model. We directly train this model on SAR datasets to evaluate its effectiveness for SAR ATR applications. The proposed model, VTR (ViT for SAR ATR), is evaluated on three widely used SAR datasets: MSTAR, SynthWakeSAR, and GBSAR. Experimental results show that the proposed VTR model achieves a classification accuracy of 95.96%, 93.47%, and 99.46% on MSTAR, SynthWakeSAR, and GBSAR datasets, respectively. VTR achieves accuracy comparable to the state-of-the-art models on MSTAR and GBSAR datasets with 1.1× and 36× smaller model sizes, respectively. On SynthWakeSAR dataset, VTR achieves a higher accuracy with a model size that is 17× smaller. Further, a novel FPGA accelerator is proposed for VTR, to enable real-time SAR ATR applications. Compared with the implementation of VTR on state-of-the-art CPU and GPU platforms, our FPGA implementation achieves latency reduction by a factor of 70× and 30×, respectively. For inference on small batch sizes, our FPGA implementation achieves a 2× higher throughput compared with GPU.
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We perform first-principles calculations based on density functional theory (DFT) to study the electronic properties of HgCdTe alloys for infrared detection applications. The Heyd, Scuseria, and Ernzerhof (HSE) and the modified Becke-Johnson (mBJ) functionals are employed to predict the bandgap of the ternary alloy over the full composition range. Due to the disordered nature of ternary alloys, we compute the bandgap values by enumerating all distinct atomic arrangements of supercells up to 16 atoms. By using the alloy composition to tune the HSE and mBJ functionals, we show that both functionals successfully produce bandgap values in good agreement with the experimental data. Subsequently, we apply the developed model to study the electronic structure properties of the alloy and its binary compounds under biaxial strain. Our results show that biaxial strain leads to a reduction in the bandgap in CdTe. In contrast, HgTe transitions from a semimetal at its equilibrium geometry to an indirect gap semiconductor under the same strain conditions. For the ternary alloys, we examine alloy compositions for applications in the long and mid-wavelength infrared detection regimes. Strain was applied to 32-atoms representative supercells for Cd compositions of 21 % and 31 %, which were obtained using the Special Quasirandom Structure (SQS) method. For both compositions, all strain configurations lead to a reduction in the bandgap. However, bandgap narrowing exhibits a stronger dependence on the strain magnitude in the case of tensile strain compared to compressive strain.
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Subwavelength moth eye structures are the nanostructures arranged uniformly whose feature size is less than the incident optical wavelength. These structures are promising to reduce the reflection of any material by creating a refractive index gradient profile at the interface surface. Mid-wave infrared (MWIR) is an important wavelength to investigate the moth eye structures for various applications like photovoltaic, solar cells and display technologies. In this paper, we fabricated two different moth eye structures Nano pillars and Nano holes using the simple and robust lithography technique. Using silicon dioxide as a hard mask, structures are transferred onto gallium arsenide substrate using different etching conditions. We compared the transmission of nanoholes and nanopillars structures and find out that nanoholes structures shows better transmittance in MWIR. We also obtained theoretical transmission data using rigorous coupled wave analysis (RCWA) which agrees with our experimental data. Moreover, Nano holes structures has an advantage over nanopillars structure as the former are resistant against contamination which therefore will not lead to decrease in transmission performance. The characterization results of the structures are obtained from SEM which shows the morphologies of the structures. Our approach is reproducible and can be easily applied to any optical devices which require antireflective property.
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One of the methods for detecting an object behind obscurants primarily relies on the well-known principle that the autocorrelation of the object’s reflectance is effectively equivalent to autocorrelation of the reflected intensity captured after the obscurants in conventional incoherent illuminations. Here, we present a novel approach to acquiring information about an object embedded in obscurants by illuminating it with different modes of a Bessel-Gaussian beam in the far field also known as a perfect optical vortex beam (POV). Each POV with different topological charges scattered from a turbid medium induces the quasi-independent speckle fields. Through numerical analysis, we determine the optimal configurations of POVs for the number of shots and the size of speckles required for effectively imaging a hidden object. By employing the prevalent imaging method based on the ensemble-averaged intensity for each illumination, we effectively reconstruct the object's details. Unlike conventional spatially incoherent sources, our approach is expected to not only efficiently identify distant objects but also offer versatile applications through adjustment of the speckle aspect ratio.
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A recently, triple-band shortwave infrared-mid-wave infrared-long-wave infrared (SWIR-MWIR-LWIR) photodetector based on III-V material showed promising performance with successful separation of operation regimes. When the applied bias voltage changes, the device demonstrates consecutively the three different colors detection, corresponding to the different bandgaps of SWIR, MWIR and LWIR absorber regions. Nevertheless, the bias dependency for MWIR and especially for LWIR signals is still much of concern. The triple-band device reveals strong bias dependency for quantum efficiency (QE) for MWIR and LWIR response as well as high dark current value, which made the structure unsuitable for FPA imaging application. In this matter, to control the high bias dependency and dark current value observed in previous design, a new approach was chosen in design to enhance the performance of the triple-band device.
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Colloidal quantum dots (CQDs) are a desirable platform for the development of next-generation infrared (IR) detectors thanks to their scalable synthesis, tunable optoelectronic properties, CMOS compatibility, and monolithic integration. However, CQD-based IR detectors typically have lower quantum efficiencies than epitaxial semiconductors and still require cryogenic cooling to achieve background-limited infrared photodetection. Developing CQD-based IR detectors that achieve state-of-the-art performance could bridge the gap between low-cost and high operating temperature detectors for IR sensing, especially for MWIR capabilities. Such a technology could significantly enable the advancement of compact, lightweight, and low-cost infrared systems for higher volume applications such as unmanned drone surveillance, driver-assisted vehicle navigation in low-visibility environments, and soldiermountable visual systems for advanced situational awareness. A systematic approach to materials development and detector design that relates material synthesis to detector optoelectronic properties will accelerate the development of CQD-based IR detector technologies. Such a system has not been explicitly established for CQD materials and their IR detectors. In this report, a process using a combination of empirical and numerical approaches has been described to guide and accelerate the development of CQD-based IR detectors. HgTe CQDs, one of the more mature IR CQD materials, was studied as a model system to provide useful feedback for establishing design rules and relationships between synthesis, material properties, and detector performance. Improvements to the performance of mid-wave infrared HgTe CQD photodetectors as an outcome of this study are demonstrated.
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Over the past few years, the number of CubeSats has been steadily growing, allowing them to be used successfully for many innovative and complex missions requiring much larger satellites. As a result, the space sector has seen a breakthrough in efficiency while reducing costs for designing, testing, and integrating these devices. In collaboration with Istanbul Technical University (ITU) and Sabanci University (SU), the Sharjah Academy for Astronomy, Space Sciences, and Technology (SAASST) has developed Sharjah-Sat-1, the first CubeSat mission of the University of Sharjah. This 3U+ CubeSat was launched on January 3, 2023, with two payloads on board. In addition, Sharjah-Sat-1 is dedicated to building the capacities of SAASST and exposing the students of the University of Sharjah to the world of space technology through a space engineering program. This paper will provide an overview of the dual camera system and a description of the tests conducted to ensure mission success. Following this, we will discuss in more detail how the images and data obtained from the camera were used to study the terrain in that region.
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