Long-wave Infrared Bands Research Articles

Spectrally Tunable Ultrafast Long Wave Infrared Detection at Room Temperature.

Room-temperature longwave infrared (LWIR) detectors are preferred over cryogenically cooled solutions due to the cost effectiveness and ease of operation. The performance of present uncooled LWIR detectors such as microbolometers, is limited by reduced sensitivity, slow response time, and the lack of dynamic spectral tunability. Here, we present a graphene-based efficient room-temperature LWIR detector with high detectivity and fast response time utilizing its tunable optical and electronic characteristics. The inherent weak light absorption is enhanced by Dirac plasmons on the patterned graphene coupled to an optical cavity. The absorbed energy is converted into photovoltage by the Seebeck effect with an asymmetric carrier generation environment. Further, dynamic spectral tunability in the 8-12 μm LWIR band is achieved by electrostatic gating. The proposed detection platform paves the path to a fresh generation of uncooled graphene-based LWIR photodetectors for wide ranging applications such as molecular sensing, medical diagnostics, military, security and space.

Analysis of aero engine plume potential core infrared signature

Purpose Aero-engine exhaust plume length can be more than the aircraft length, making it easier to detect and track by infrared seeker. Aim of this study is to analyze the effect of free stream Mach number (M∞) on length of potential core of plume. Also, change in infrared (IR) signature of plume and aircraft surface with variation in elevation angle (θ) is examined. Design/methodology/approach Convergent divergent (CD) nozzle is located outside the rear fuselage of the aircraft. A two dimensional axisymmetric computational fluid dynamics (CFD) study was carried out to study effect of M∞ on potential core. The CFD data with aircraft and plume was then used for IR signature analysis. The sensor position is changed with respect to aircraft from directly bottom towards frontal section of aircraft. The IR signature is studied in mid wave IR (MWIR) and long wave IR (LWIR) band. Findings The potential plume core length and width increases as M∞ increases. At higher altitudes, the potential core length increases for a fixed M∞. The plume emits radiation in the MWIR band, whereas the aerodynamically heated aircraft surface emits IR in the LWIR band. The IR signature in the MWIR band continuously decreases as the sensor position changes from directly bottom towards frontal. In the LWIR band the IR signature initially decreases as the sensor moves from the directly bottom to the frontal, as the sensor begins to see the wing leading edges and nose cone, the IR signature in the LWIR band slightly increases. Originality/value The novelty of this study comes from the data reported on the effect of free stream Mach number on the potential plume core and variation of the overall IR signature of aircraft with change in elevation angle from directly below towards frontal section of aircraft.

Utilizing Alignment Loss to Advance Eye Center Detection and Face Recognition in the LWIR Band

Geometric normalization is an integral part of most of the face recognition (FR) systems. To geometrically normalize a face, it is essential to detect the eye centers, since one way to align the face images is to make the line joining the eye centers horizontal. This paper proposes a novel approach to detect eye centers in the challenging Long-Wave Infrared (LWIR) spectrum (8-14 μm). While using thermal band images for face recognition is a feasible approach in low-light and nighttime conditions, where visible face images cannot be used, there are not many thermal or dual band (visible and thermal) face datasets available to train and test new eye center detection models. This work takes advantage of the available deep learning based eye center detection algorithms in the visible band to detect the eye centers in thermal face images through image synthesis. While we empirically evaluate different image synthesis models, we determine that StarGAN2 yields the highest eye center detection accuracy, when compared to the other state-of-the-art models. We incorporate alignment loss that captures the normalized error between the detected and actual eye centers as an additional loss term during training (using the generated images during training, ground truth annotations, and an eye center detection model), so that the model learns to align the images to minimize this error. During test phase, visible images are generated from the thermal images using the trained model. Then, the available landmark detection algorithms in the visible band, namely, MT-CNN and HR-Net are used to detect the eye centers. Next, these eye centers are used to geometrically normalize the source thermal face images before performing same-spectral (thermal-to-thermal) face recognition. The proposed method improved the eye center detection accuracy by 60% over the baseline model, and by 14% over training only the StarGAN2 model without the alignment loss. The proposed approach also reports the highest improvement in the face recognition accuracy by 36% and 3% over the baseline and original StarGAN2 models, respectively, when using deep learning based face recognition models, namely, Facenet, ArcFace, and VGG-Face. We also perform experiments by augmenting the train and test datasets with images rotated in-plane to further demonstrate the efficiency of the proposed approach. When CycleGAN (another unpaired image translation network) is used to generate images before incorporating the alignment loss, it failed to preserve the alignment at the slightest, therefore the eye center detection accuracy was extremely low. With the alignment loss, the accuracy increased by 20%, 50%, and 80% when the normalized error (e) ≤ 0.05, 0.10 and 0.25 respectively.

A Novel Two-Stage Destriping Algorithm Based on MWIR Energy Separation and Image Guidance (MES-IG)

Long-wave infrared (LWIR) bands in multispectral datasets are extremely useful in many applications. However, the LWIR bands usually suffer from undesirable stripe noise, which impedes their further application. Compared with emission-dominated LWIR, the mid-wave infrared (MWIR) bands containing both emitted and reflected radiation usually exhibit higher image quality. In this paper, we propose a novel two-stage MWIR energy separation and image guidance (MES-IG) algorithm to destripe the LWIR images with the assistance of the MWIR bands. In the first stage, we decompose the MWIR image into the emitted and reflected components by solving a constrained optimization problem. Specifically, we impose the low-rank penalty to enforce the similarities between MWIR and LWIR, and we use the total variation (TV) regularization to exploit the similarities between MWIR and visible and near-infrared (VNIR) images. In the second stage, the obtained emitted component of MWIR is considered as the guidance image to remove the stripes in the LWIR images by adopting the 1-D guided filter algorithm. Numerical experiments on Chinese Gaofen-5 satellite and MODIS data demonstrate the utility of the proposed method in providing improved LWIR image destriping performance over the state-of-the-art algorithms.

Near Perfect Absorber for Long-Wave Infrared Based on Localized Surface Plasmon Resonance

In recent years, broadband absorbers in the long-wave infrared (LWIR) spectrum have shown great scientific value and advantages in some areas, such as thermal imaging and radiation modulation. However, designing a broadband absorber with an ultra-high absorption rate has always been a challenge. In this paper, we design a near perfect absorber that is highly tunable, angle insensitive, and has polarization independence for LWIR. By using multi-mode localized surface plasmon resonance (LSPR) of a surface metal structure, the absorber achieves a very high absorption average of 99.7% in wavelengths from 9.7 μm to 12.0 μm. For incident light, the meta-structure absorber exhibits excellent polarization independence. When the incident angle increases from 0° up to 60°, the absorption rate maintains over 85%. By modulating the size of the structure, the meta-structure absorber can also achieve a high absorption rate of 95.6%, covering the entire LWIR band (8-14 μm in wavelength). This meta-structure absorber has application prospects in infrared detecting, infrared camouflage, radiation cooling, and other fields.

Aircraft visibility in view from below in the long-wave infrared band using infrared cross section.

Aircraft low observables' features are crucial in the long-wave infrared (LW-IR) band, due to imaging sensors used in IR search and track and in the latest generation of IR-guided missiles. Earthshine irradiance on the aircraft bottom surface is an important source; hence, it is derived using data for atmospheric transmission. Emission due to skin-friction heating (important at high εbot) and earthshine reflection (important at low εbot) are compared by a dimensionless ratio for different bottom surface emissivities (εbot). The infrared cross section of aircraft in direct view from below is obtained in the LW-IR band, which shows that aircraft is seen also due to negative contrast.

Ge/BaF2 thin-films for surface micromachined mid-wave and long-wave infrared reflectors

High performance distributed Bragg reflectors (DBRs) are key elements to achieving high finesse MEMS-based Fabry–Pérot interferometers (FPIs). Suitable mechanical parameters combined with high contrast between the refractive indices of the constituent optical materials are the main requirements. In this paper, Germanium (Ge) and barium fluoride (BaF2) optical thin-films have been investigated for mid-wave infrared (MWIR) and long-wave infrared (LWIR) filter applications. Thin-film deposition and fabrication processes were optimised to achieve mechanical and optical properties that provide flat suspended structures with uniform thickness and maximum reflectivity. Ge-BaF2-Ge 3-layer solid-material DBRs have been fabricated that matched the predicted simulation performance, although a degradation in performance was observed for wavelengths beyond 10 μm that is associated with optical absorption in the BaF2 material. Ge-Air-Ge 3-layer air-gap DBRs, in which air rather than BaF2 served as the low refractive index layer, were realized to exhibit layer flatness at the level of 10 to 20 nm across lateral DBR dimensions of several hundred micrometers. Measured DBR reflectance was found to be ≳90 % over the entire wavelength range of the MWIR band and for the LWIR band up to a wavelength of 11 μm. Simulations based on the measured DBR reflectance indicates that MEMS-based FPIs are able to achieve a peak transmission of ≳90 % over the entire MWIR band and up to 10 μm in the LWIR band, with a corresponding spectral passband of ≲50 nm in the MWIR and <80 nm in the LWIR.

Dual-band metamaterial absorber with a low-coherence composite cross structure in mid-wave and long-wave infrared bands.

The atmospheric window in the infrared (IR) band primarily consists of mid-wave (MWIR, 3-5 μm) and long-wave IR (LWIR, 8-12 μm) bands, also known as the working bands in most of the IR devices. The main factor affecting the device capability includes the absorption efficiency, hence, the absorption material. Herein, a dual-band absorber based on the composite cross structure (CCS) in both MWIR and LWIR bands was proposed, with absorption peaks of 4.28 μm and 8.23 μm. The obtained absorber is with high scalability in the MWIR and LWIR region respectively by tuning the structural parameters. A quadrupole polarization model is proposed for further understanding of the uneven distribution of electromagnetic field that was caused by the change of the center spacing of the embedded structure. Meanwhile, it was shown that the two absorption peaks exhibited good incident angle stability. In addition, as the incident angle of the TM mode increases, a waveguide is formed between the embedded structure and the surface structure, leading to another strong absorption in the LWIR band. The results showed that absorption increases as the incident angle increases. The proposed absorber can be a good candidate for applications in thermal emission, detection and solar energy harvesting.

Moving People Tracking and False Track Removing with Infrared Thermal Imaging by a Multirotor

Infrared (IR) thermal imaging can detect the warm temperature of the human body regardless of the light conditions, thus small drones equipped with the IR thermal camera can be utilized to recognize human activity for smart surveillance, road safety, and search and rescue missions. However, the unpredictable motion of the drone poses more challenges than a fixed camera. This paper addresses the detection and tracking of people through IR thermal video captured by a multirotor. For object detection, each frame is first registered with a reference frame to compensate for its coordinates. Then, the objects in each frame are segmented through k-means clustering and morphological operations. Falsely detected objects are removed considering the actual size and the shape of the object. The centroid of the segmented area is considered the measured position for target tracking. The track is initialized with two-point differencing initialization, and the target states are continuously estimated by the interacting multiple model (IMM) filter. The nearest neighbor association rule assigns the measurement to the track. Tracks that move slower than the minimum speed are terminated at the proposed criteria. In the experiments, three videos were captured with a long-wave IR band thermal imaging camera mounted on a multirotor. In the first and second videos, eight pedestrians on a pavement and three hikers on a mountain on winter nights were captured, respectively. In the third video, two walking people with complex backgrounds were captured on a windy summer day. The image characteristics vary between videos depending on the climate and surrounding objects, but the proposed scheme shows the robust performance in all cases; the average root mean squared errors in position and velocity are obtained as 0.08 m and 0.53 m/s, respectively for the first video, 0.06 m and 0.58 m/s, respectively for the second video, and 0.18 m and 1.84 m/s, respectively for the third video. The proposed method reduces false tracks from 10 to 1 in the third video.

Modeling infrared behavior of multilayer diffractive optical elements using Fourier optics.

In this paper, we propose to explore the infrared (IR) behavior of multilayer diffractive optical elements (MLDOEs). IR MLDOEs are designed for the development of space instruments dedicated to Earth observation. The phase effect of the MLDOE on a paraxial plane wave is studied using exact kinoform shapes for each layer. The modeling of the optical path difference uses thin element approximation. Until now, MLDOEs have been designed and simulated on ray-tracing software with binary diffractive layers. In this study, after passing through the MLDOE, the field is propagated using a method that utilizes the angular spectrum of plane waves. The Strehl ratio is used to determine the "best focus" plane, where it is shown that the focalization efficiency is above 95% for the working order in the mid- and long-wave IR bands. This result, along with the very low energy content of the other orders, proves the strong imaging potential of MLDOEs for dual-band applications. It is also demonstrated that the MLDOE has the same chromatic behavior as standard DOEs, making it a very useful component for IR achromatization.

Hypothetical Product Generation of Geostationary Ocean Color Imager Bands Over the Yellow Sea and Bohai Sea Using Deep Learning Technique

This study presents a deep learning model, using the conditional generative adversarial nets (CGAN) technique, that can produce daytime visible (VIS) band information, mimicking a narrow band sensor, by combining VIS and infrared (IR) broadband measurements by different sensors. The real-observed datasets of the Geostationary Ocean Color Imager (GOCI) and meteoritical imager (MI) sensors onboard the Communication, Ocean, and Meteorological Satellite were used for training and testing our CGAN model over the Yellow Sea and Bohai Sea. The trained and tested CGAN model was then applied to generate daytime GOCI VIS and near IR (NIR) bands (0.412 to 0.865 <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">μ</i> m) using daytime MI VIS (0.675 <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">μ</i> m), shortwave IR (3.75 <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">μ</i> m), and longwave IR bands (10.8 and 12.0 <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">μ</i> m) and the differences between them as input data. GOCI and MI data were collected from January 2017 to December 2018 using 705 images of 256 × 256 pixels for the training and 44 images for the model test. The results are statistically favorable (i.e., bias = −0.013 (in a reflectance unit from 0 to 1), root-mean-square error = 0.112, mean absolute error = 0.076, agreement index = 0.945, and correlation coefficient (CC) = 0.809 for daytime reflectance in the GOCI VIS 0.49- <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">μ</i> m band) between the real GOCI VIS band observation and the CGAN-generated simulation. Our CGAN-based model showed high CC and favorable results in the GOCI VIS and NIR bands. Consequently, our study demonstrates the possibility of applying a deep learning technique to improve the temporal resolution for ocean color studies using the GOCI sensor.

TiNb thin films as absorbers for LWIR microbolometers

Uncooled microbolometers use ultra-thin metal or dielectric layer to absorb the incoming longwave infrared (LWIR) radiation. This is due to the fact that thermometer layers in microbolometers are typically of very low LWIR absorption coefficients. In this paper, a novel ultra-thin film alloy of Titanium–Niobium (TiNb) is synthesized using sputter deposition, and further morphologically, compositionally and optically characterized. Simultaneous DC and RF sputtering from Ti and Nb targets is used to deposit a 10 nm thin film of TiNb. The surface morphology of the thin film is studied showing surface roughness of 0.23 nm. Compositional analysis was performed using X-ray photoelectron spectroscopy (XPS) and Electron dispersive X-ray spectroscopy (EDX). LWIR ellipsometry was used to measure the optical constants of the TiNb thin film. Finally, a Fabry-Perot cavity microbolometer configuration is numerically simulated and analyzed to assess the effectiveness of the developed TiNb thin film as an absorber for LWIR microbolometers. The TiNb thin film has shown higher absorptance % in the LWIR band at a wider range of cavity air gap thicknesses, when compared to typically used absorbers, NiCr and Ti. This work shows that TiNb thin films, never considered before as IR absorbers, can be effective IR absorbers for LWIR microbolometers.

High Spectral Infrared Atmospheric Sounder (HIRAS): System Overview and On-Orbit Performance Assessment

The High Spectral Infrared Atmospheric Sounder (HIRAS) is the first Chinese Fourier Transform Michelson interferometer onboard the FengYun 3D (FY-3D) polar-orbiting meteorological satellite launched on November 15, 2017. The FY-3D HIRAS provides infrared (IR) radiance spectra measurements in three spectral bands: the long-wave IR (LWIR) band from 650 to 1135 cm−1, middle-wave IR (MWIR) band from 1210 to 1750 cm−1, and short-wave IR (SWIR) band from 2155 to 2550 cm−1. The ground system processes the interferogram measurements into calibrated radiance spectra. In each cross-track scan, there are 29 observations, each with a field-of-regard (FOR) comprising an array of $2\times 2$ field of views. In a six-month intensive campaign period, the HIRAS system was tuned, characterized, and validated. For the operational Level 1 product, the radiance noise levels meet the specifications. The spectral frequency accuracy was improved by maximizing the spectral correlation between the measured and simulated spectra by tuning the instrument-line-shape parameters. The absolute spectral frequency biases are less than 3 part per million (ppm) for all the three bands, and spectral bias standard deviations are less than 3 ppm in the LWIR and MWIR bands, and are about 3–5 ppm in the SWIR band. The radiometric calibration uncertainties were assessed by the comparisons of the radiance spectra between HIRAS and other IR hyperspectral sensors on different satellites. The radiance differences of the cross-sensor comparisons are in general less than 0.3, 0.7, and 1.0 K in the LWIR, MWIR, and SWIR bands, respectively. The HIRAS spectra were also compared with the spectra simulated with a fast radiative transfer model. Some remaining issues for the FY-3D HIRAS are also discussed.

Sea Fog Detection Based on Normalized Difference Snow Index Using Advanced Himawari Imager Observations

Many previous studies have attempted to distinguish fog from clouds using low-orbit and geostationary satellite observations from visible (VIS) to longwave infrared (LWIR) bands. However, clouds and fog have often been misidentified because of their similar spectral features. Recently, advanced meteorological geostationary satellites with improved spectral, spatial, and temporal resolutions, including Himawari-8/9, GOES-16/17, and GeoKompsat-2A, have become operational. Accordingly, this study presents an improved algorithm for detecting daytime sea fog using one VIS and one near-infrared (NIR) band of the Advanced Himawari Imager (AHI) of the Himawari-8 satellite. We propose a regression-based relationship for sea fog detection using a combination of the Normalized Difference Snow Index (NDSI) and reflectance at the green band of the AHI. Several case studies, including various foggy and cloudy weather conditions in the Yellow Sea for three years (2017–2019), have been performed. The results of our algorithm showed a successful detection of sea fog without any cloud mask information. The pixel-level comparison results with the sea fog detection based on the shortwave infrared (SWIR) band (3.9 μm) and the brightness temperature difference between SWIR and LWIR bands of the AHI showed high statistical scores for probability of detection (POD), post agreement (PAG), critical success index (CSI), and Heidke skill score (HSS). Consequently, the proposed algorithms for daytime sea fog detection can be effective in daytime, particularly twilight, conditions, for many satellites equipped with VIS and NIR bands.

Narrowband, infrared absorbing metasurface using polystyrene thin films

We present the results of an experimental investigation of polystyrene’s suitability as a dielectric material for designing narrowband, infrared metasurface-based absorbers. Our study included characterization of processing parameters of polystyrene films, such as surface roughness and film thickness, which are critical for device fabrication, and the dielectric properties, which we measured, using spectroscopic ellipsometry. Our results confirm that thin film polystyrene is a relatively low-loss dielectric material at long-wave infrared (LWIR) frequencies. Subsequently, this material was used as the dielectric substrate of a thin, narrowband, metasurface-based absorber at LWIR frequencies. The fabricated narrowband absorber demonstrates excellent performance in the LWIR band with absorptivity as high as 96% and a full-width-at-half-maximum bandwidth of 0.502μm or 4.87%.

Early Calibration and Performance Assessments of NOAA-20 VIIRS Thermal Emissive Bands

The Visible Infrared Imaging Radiometer Suite (VIIRS) sensor aboard the NOAA-20 (previously JPSS-1) spacecraft has successfully operated since its launch in November, 2017. Similar to the first VIIRS instrument on the Suomi-National Polar-orbiting Partnership (SNPP) spacecraft, the data are collected in 22 spectral bands that are calibrated by a set of onboard calibrators. This paper provides an overview of the NOAA-20 VIIRS on-orbit operation and calibration, with a particular focus on the thermal emissive bands (TEBs). The results presented in this paper include the on-orbit changes in the TEB spectral band responses, detector noise characterization, and key calibration parameters, such as the nonlinear coefficients derived from the blackbody warm-up cool-down cycles. Other issues, such as the early mission long-wave infrared (LWIR) response degradation due to icing on the dewar window, and their impact on sensor calibration are also discussed. Since launch, the VIIRS instrument temperature has been stable to within ±0.8 K and the cold focal plane temperatures are well controlled with variations less than 40 mK. With the exception of the early degradation observed in the LWIR bands, the TEB gains have been stable to within 0.04% (except I5 at 0.07%). Based on the current performance, VIIRS is expected to meet its calibration requirements throughout its design lifetime.

Broadband lightweight flat lenses for long-wave infrared imaging

We experimentally demonstrate imaging in the long-wave infrared (LWIR) spectral band (8 μm to 12 μm) using a single polymer flat lens based upon multilevel diffractive optics. The device thickness is only 10 μm, and chromatic aberrations are corrected over the entire LWIR band with one surface. Due to the drastic reduction in device thickness, we are able to utilize polymers with absorption in the LWIR, allowing for inexpensive manufacturing via imprint lithography. The weight of our lens is less than 100 times those of comparable refractive lenses. We fabricated and characterized 2 different flat lenses. Even with about 25% absorption losses, experiments show that our flat polymer lenses obtain good imaging with field of view of 35° and angular resolution less than 0.013°. The flat lenses were characterized with 2 different commercial LWIR image sensors. Finally, we show that, by using lossless, higher-refractive-index materials like silicon, focusing efficiencies in excess of 70% can be achieved over the entire LWIR band. Our results firmly establish the potential for lightweight, ultrathin, broadband lenses for high-quality imaging in the LWIR band.

A New Method for Characterizing NOAA-20/S-NPP VIIRS Thermal Emissive Bands Response Versus Scan Using On-Orbit Pitch Maneuver Data

The on-orbit calibration of Visible Infrared Imaging Radiometer Suite (VIIRS) Thermal Emissive Bands (TEB), onboard the National Oceanic and Atmospheric Administration-20 (NOAA-20) and the Suomi National Polar-orbiting Partnership (S-NPP) satellites, have been stable during nominal operations. However, larger than expected scan angle/scene temperature dependent biases, relative to the co-located Cross-track Infrared Sounder (CrIS) observations, were observed in the NOAA-20 longwave infrared (LWIR) bands. The Response Versus Scan (RVS) effect—the variation of instrument reflectance of source radiance with scan angle, is a significant contributor to VIIRS calibration. TEB RVS is characterized using prelaunch test data and verified on-orbit using pitch maneuver data. This study presents a new method that characterizes VIIRS on-orbit TEB RVS at both Earth View (EV) and Space View (SV) scan angles simultaneously. This method was compared with an existing on-orbit RVS method (the Wu et al. method), which derives RVS at EV scan angles using pitch maneuver data and extrapolates SV RVS from EV. The new method derived on-orbit RVS differ from prelaunch values up to 1.0% at the beginning of scan in the NOAA-20 LWIR bands, and ~0.5% in S-NPP M15. VIIRS–CrIS inter-comparison results indicates that the new method derived on-orbit RVS can effectively minimize LWIR scan angle/scene temperature dependent biases, with scan averaged biases reduced from 0.40K to 0.15K for NOAA-20 LWIR bands, and from 0.24K to 0.08K for S-NPP M15. The Wu et al. method can also reduce the scan angle dependent biases, but at the expense of increasing the scene temperature dependent biases.

An Angle-Sensing Infrared Detector Using a Two-Element Biomimetic Antenna Array

We present a technique for designing the angle-sensing infrared detectors with subwavelength dimensions. The proposed detector is composed of a two-element long-wave infrared (LWIR) biomimetic antenna array. The detector consists of two closely spaced and strongly coupled IR antennas whose natural mutual coupling is augmented by using an external coupling network. Each antenna is connected to a microbolometer to detect the incoming IR radiation. By controlling the mutual coupling between the antennas and designing an optimum coupling network, the ratio of the power absorbed in the two bolometers is made to a one-to-one function of the incidence angle. This allows for determining the angle of incidence of the incoming IR light by measuring the changes of the dc currents passing through the bolometers when the antennas are biased with a dc voltage source. A prototype of the proposed angle-sensing detector is designed to operate at $10.6~\mu \text{m}$ in the LWIR band. The prototype is fabricated and characterized. Measurement results show that the device has a one-to-one response function for transverse electric waves within a field of view of ±60°. The response of the device for incident waves having the transverse magnetic or random polarizations was also simulated and measured. In all cases, the measurement results are found to be in good agreement with the theoretical predictions.

High-sensitivity short-wave infrared technology for thermal imaging

Thermal imaging technology is widely used in various fields, such as security, defense, medicine and spaceborne applications in the Geo-synchronous Earth Orbit. Most thermal imaging systems operate in the long-wave infrared (LWIR) range or the medium-wave infrared (MWIR) range. However, the longer the wavelength is, the more difficult the imaging system is to provide high resolution due to diffraction limit. Compared to MWIR and LWIR imagers, a short-wave infrared (SWIR) imager achieves higher resolution owing to its higher diffraction limit. However, radiation from an object at 300 k in the SWIR band is weaker than that in the MWIR and LWIR bands. Therefore, the sensitivity is low. With the rapid development of detector technology, the sensitivity of SWIR detector is improved by low dark current and noise. It exhibits good performance in thermal imaging applications. In order to validate SWIR thermal imaging key performance, this study analyzes the thermal imaging capability of an SWIR imager compared to MWIR and LWIR. The noise equivalent temperature differences (NETDs) of SWIR, MWIR, and LWIR imagers for thermal imaging applications are calculated. A compact SWIR imager prototype covering a spectral range of 2.0–2.7 μm is designed and implemented. The facial thermal imaging experiment proves that the high-sensitivity SWIR imager can obtain high-quality thermal images with an NETD of 24 mK at a temperature of 310 K. In addition, in the continuous integration and multiple read-out (IMRO) imaging mode, the dynamic range of the system is extended by 20 dB. The theoretical analysis and experiment show that the SWIR imager can provide high sensitivity with long integration time. In addition, SWIR thermal imaging can provide higher resolution than MWIR and LWIR imagers. Therefore, SWIR imager has considerable potential for high-sensitivity thermal imaging applications in Geo-synchronous Earth Orbit.