In this study, the research progress of long-wave infrared detectors based on InAs/GaSb type-II superlattices (T2SLs) is systematically reported. The advantages and disadvantages of various device structures based on GaSb and InAs substrates are compared and analyzed from the perspective of substrate, material growth, and device performance. The results show that the structure of the device with InAs as the substrate, InAs/InAs1-xSbx as the absorber material, and PB1IB2N type is a relatively optimized design. Combining the multilayer structure design of ZnS and Ge, a heavy doping buffer layer, and the inductively coupled plasma (ICP) dry etching process, the 50% cutoff wavelength of the device can achieve 12 ?m, the quantum efficiency (QE) can be increased to more than 65%, and the dark current density can be reduced to 1×10-5 A/cm2. Finally, the future development trend of InAs/GaSb T2SLs long-wave infrared detectors is summarized.

As a key shell component of semiconductor optoelectronic device packages, optical windows provide an indispensable optical signal transmission channel for optoelectronic devices, and the sealing quality of the structure has a significant impact on the long-term life of the device. Vacuum brazing technology is the process of obtaining a hermetic optical window by welding a metal shell and metalized optical window with solder under a vacuum environment and is one of the main technologies used to seal optical windows. It has the advantages of low sealing temperature, high air-tightness, good flatness, and long-term reliability, and it is widely used in the fields of optical device vacuum hermetic packaging and optical equipment manufacturing. In this study, the research status of vacuum brazing technology for optical windows is introduced from the perspectives of filler metal type, metallization structure design, brazing equipment, welding void ratio, gas tightness, and mechanical properties, and the development trends of future technologies in this field are discussed.

To meet the design requirements of a fast steering mirror (FSM) for an infrared search system, the electromechanical co-simulation technology of FSM based on the cross-reed transmission structure and voice coil actuator was studied. An electromechanical parametric model of the FSM was established, the transmission stiffness model of the flexible structure was constructed by the finite element analysis, the working model of the voice coil motor was constructed, and the key design parameters were compared and iterated to determine the optimal design parameters. MATLAB/Simulink was used as a co-simulation platform to establish the FSM dynamics simulation and electromagnetic drive simulation interfaces, combined with the classical control model to realize the co-simulation of the FSM and obtain the simulation results of the system dynamic response. Finally, the flyback compensation residual and phase lag under a 50-Hz imaging period were verified experimentally. The results show that the measured flyback compensation residual is 0.0365 mrad and the phase lag is 2.6 ms, which are higher than the simulation analysis results but meet the requirements of engineering applications. The open-loop frequency response curve of the system was compared, and the mid-low frequency amplitude response error did not exceed 10%. The simulation and experimental results show that this co-simulation technology has important theoretical significance for the design and optimization of FSMs.

Due to the night-vision display function of infrared images and their ability to observe targets over long distances, they are often used in sniper sights for firearms. However, when an infrared sight is first installed on a firearm, it is necessary to calibrate the zero position such that the cross-division center of the infrared sight coincides with the target center of the firearm during sniping. A target can only be accurately hit during sniping if the infrared sight has undergone zero calibration. Performing automatic and efficient zero calibration is a problem in that every infrared sight differs when it is first used. This article investigates the current mainstream zero calibration methods, analyzes and compares them, and proposes an efficient automatic calibration method and process based on single-key triggering, which simplifies the calibration process and improves its efficiency. In engineering applications, it solves the problem of difficult and slow calibration of infrared sights during initial use and greatly improves the user experience.

The optical axis of an infrared thermal imaging folding optical system is prone to shift owing to decentering of the tilt of optical components under complex environmental conditions, which affects the indication accuracy of the system for the target. Static sensitivity analysis of the optical axis for the optical system at the beginning of the design of the infrared thermal imaging system is useful for identifying the sensitive points of the optical system and provides constraints for the structural optimization design to meet the stability of the optical axis. The conversion relationship between the rotation process and spatial state quantities of the optical components was established by coordinate transformation based on the rotation matrix to simulate the spatial attitude of the optical component tilted in any direction and ensure that the Monte Carlo sampling in the optical axis sensitivity analysis corresponds to the constraint conditions of the structural design. On this basis, the flow of the static sensitivity analysis of the optical axis of the infrared folding optical system was established, and a program was compiled. A typical infrared thermal imaging folding optical system was analyzed using this program. According to the index requirements of the optical axis stability, the optical axis sensitivity and inverse sensitivity of the decenter and tilt of each optical component in the optical system were analyzed, and the initial tolerance limit was obtained. Then, Monte Carlo analysis sampling could be performed in any direction according to the initial tolerance limit data; thus, the decenter and tilt tolerance limit data that meet the optical axis stability index could be obtained, and the accuracy of the obtained data was verified by establishing a multi-coordinate system. Static sensitivity analysis provides a foundation for guiding the design of optical–mechanical thermal optimization.

To meet the development trend of light, small, and compact airborne photoelectric pods and solve the heat dissipation problem of photoelectric pods, a combination of cooling and fan circulation convection heat dissipation was used. The contact heat components with the cabin using a metal structure were employed to establish a heat conduction channel. The internal air was circulated by a fan to strengthen the internal convection and establish a low-thermal-resistance convection heat-transfer channel. Modeling simulation was performed by ICEPAK thermal simulation software, and a high-temperature working test was also conducted. The results show that the maximum temperature rise of the key processors DSP, FPGA, SoC is respectively 29.1℃, 29.2℃, 33.8℃ under static conditions and 5.2℃, 3.5℃, 4.4℃ lower than the case without fans. And the maximum temperature rise is respectively 11.9℃, 9.1℃, 15.5℃ under flight conditions. At the same time, under the action of internal air circulation by the fan, the maximum ambient temperature in the cabin was reduced by approximately 5.5℃. The maximum temperature deviation between test and simulation at the same conditions is 3.1℃. The thermal management method can effectively reduce the temperature increase in the internal environment and devices inside the cabin, satisfy the requirements of pod use with a simple structure, and occupy a small space. Thus, it is suitable for light, small, and compact airborne photo-electric pods.

To accurately obtain the infrared radiation characteristics of an unmanned aerial vehicle (UAV), its infrared radiation luminance was measured with medium- and long-wave infrared thermal imagers of 3.7–4.8 .m and 7.7–10.3 .m, respectively, and the atmospheric transmittance and atmospheric radiation during measurement were calculated with the MODTRAN atmospheric radiation transmission software. The measurement results show that under these conditions, the radiation of the UAV fuselage skin is weak, the radiation brightness is close to the ground and background radiation brightness, and the radiation brightness is essentially the same in all directions. The radiation brightness of the fuselage skin in the long-wave band was approximately 280 times that of the corresponding part in the medium-wave band. The engine radiation brightness was much higher than that of the fuselage skin. For reasons such as fuselage shelter and structure of the body, the engine radiation brightness is directional, and the radiation is strongest in the backward direction.

To obtain more prominent target information and retain more textural details in infrared and visible light fusion images, an infrared and visible light image fusion algorithm based on the non-subsample shearlet transform (NSST) domain combined with a spiking cortical model (SCM) and improved fuzzy C-means clustering model (FCM) is proposed. First, the infrared target information in the source infrared image is extracted by the FCM. Subsequently, the NSST is used to decompose the target and background areas of the infrared and visible images to obtain their own high- and low-frequency sub-band images. Subsequently, different fusion strategies are adopted for different regions, and the SCM and improved time matrix are adopted for high-frequency background regions. The final fused image is obtained by using the NSST inverse transform. Simulation experiments show that, compared with other methods, the fusion image obtained by this algorithm has a prominent infrared target and intricate texture details in subjective vision, and its information entropy and edge retention factor are optimal for objective evaluation.

Here, a registration algorithm based on edge structure features is proposed to solve the difficulty of extracting feature points from infrared and visible images. First, the structural features of infrared images are enhanced using an optimized saliency algorithm. Second, we extract the stable edge structures of the infrared and visible images using a phase consistency algorithm. Further, the ORB feature points are extracted from the edge structures. Finally, the KNN algorithm and cosine similarity are combined to filter the matching feature points, and the random sample consensus (RANSAC) algorithm is used for purification. Experimental results show that the algorithm overcomes the influence of grayscale differences between infrared and visible images. In addition, it achieves a high registration accuracy and efficiency, which is conducive to the registration of infrared and visible images.

To address the problems of false and missed alarms caused by smoke interference in pulsed laser proximity detection, according to Mie scattering theory and the Monte Carlo method, this study established a pulsed laser proximity detection model, simulated a 905-nm pulsed laser to obtain echoes of large and small targets under the conditions of no interference and smoke interference, and analyzed the waveform characteristics of the echoes. The results show that there is a negative correlation between the distance from the transmitting and receiving system to the target and the echo amplitude without interference. The rising rate of the echo front of large and small targets increases. Under the condition of smoke interference, the pulse widths of the smoke and target echoes have a certain broadening compared with the transmitted laser waveform. However, the broadening degree of the former is greater than that of the latter, and the smoke echo waveform is asymmetric with a steep front edge and gentle back edge. The results provide a theoretical basis for anti-smoke interference in laser proximity detection.

The variation law of the performance with working time in the super Gen-II image intensifier was studied, and the characteristics of the performance variation were grasped. Through performance testing and curve fitting, it was found that the brightness gain and signal-to-noise ratio gradually decrease with working time, and the resolution remains almost unchanged with the change of working time. In addition, the brightness gain changes exponentially with working time. That is, when the working time is within 10,000 h of the super Gen-II image intensifier, the brightness gain changes rapidly with the working time; however, as the working time increases, the brightness gain decreases and finally stabilizes. The signal-to-noise ratio changes as a polynomial function with working time and finally stabilizes. The signal-to-noise ratio changes as a polynomial function with working time and gradually decreases with working time. Through anatomical analysis of the image intensifier after working for a long time, its brightness gain and signal-to-noise ratio changes were found to be mainly related to the sensitivity of the photocathode, luminous efficiency of the phosphor screen, and gain stability of the MCP. Compared with the sensitivity and luminous efficiency of the fluorescent screen, the MCP gain stability changed significantly.

Low-velocity impact damage of woven composites is mainly caused by internal delamination damage, which cannot be effectively detected by visual inspection; this seriously reduces the structural load-bearing capacity and threatens the safe use of the compiled composite components. In this study, ultrasonic infrared thermography was used to perform nondestructive testing of the low-velocity impact damage of woven composites, and five specimens were produced using impact energies of 10, 20, 30, 40, and 50 J. The temperature increase and space temperature curves of the ultrasonic excitation process were analyzed. By comparing different impact energy specimens, it was found that the damage under low-speed impact was mainly internal, and the larger the impact energy, the larger the damage area. Moreover, the damage was ductile. The damage area was identified quantitatively using a curve classification algorithm. It was found that the damage area of woven composites and the impact energy were linearly correlated.

This study introduces a thermal defect detection technique for power equipment based on a spectral transformation model. First, the spectral residual transform model is constructed according to the redundancy of the natural background and significance of the thermal defect target in infrared images of power equipment. Then, the infrared image of the power equipment is transformed by spectral residuals to remove redundant image information of the natural background target, and a result map with significant information is generated. The experimental results show that compared with other traditional thermal defect detection methods, the proposed method has significant advantages in terms of recognition accuracy and efficiency and meets the application requirements of thermal fault detection of power equipment.

Caries is one of the most prevalent oral diseases worldwide. Terahertz spectral imaging technology has the advantages of strong broadband spectral analysis ability, high spatial resolution, and low ionizing radiation and is expected to be a new technical means for caries diagnosis. In this study, tooth slices containing dentin caries were used as the research object, and reflective terahertz spectral scanning was performed. The spectral data of the samples were reconstructed using two-dimensional imaging with the frequency-domain amplitude as the parameter, and several terahertz spectral images of caries were obtained at different frequencies. To solve the problems of small dynamic range, low contrast, and ambiguous edges, the detailed position of the terahertz image was obtained using a single parameter. Using the fusion method of wavelet gradient domain reconstruction, the larger gradient amplitudes of several images are concentrated in one image, and a new image with clearer and more complete detailed features is obtained. The experimental results show that the information entropy, average gradient, and contrast of the fused images are improved compared with those of the pre-fused images, and the discrimination effect between different tissues is more significant.