HgCdTe materials have the advantages of fast response, high quantum efficiency, and continuously adjustable bandgap, and are widely used in the field of infrared detection. In this paper, the recent progress of the 11th Research Institute of CETC in the preparation of HgCdTe materials is reported. In the preparation of CdZnTe substrate materials, a breakthrough has been made in the crystal growth technology of ϕ135mm CdZnTe, and the average etch pit density (EPD) of CdZnTe substrate less than 1×104 cm-2, and has the mass production capacity of 80mm×80mm CdZnTe substrate. In terms of the preparation of HgCdTe films in liquid phase epitaxy, the average etch pit density (EPD) of tellurium-rich horizontal liquid epitaxial HgCdTe films is less than 4×104 cm-2, and it has the ability to prepare 80 mm × 80 mm HgCdTe, and the mercury-rich vertical liquid phase epitaxy realizes the batch preparation of high-quality double-layer heterojunction materials, and FWHM of heterojunction materials is controlled in the range of 20~40 arcsec, and the thickness homogeneity of HgCdTe films is better than △d=±0.6 m. In the molecular beam epitaxial HgCdTe film, the preparation of 6-inch Si-based HgCdTe material with a component standard deviation better than 0.0015 and a surface macroscopic defect density less than 100cm-2, and the CdZnTe-based HgCdTe has a preparation capacity of 50mm×50mm, with a standard deviation of 0.002 and a thickness standard deviation of 0.047 m. According to the verification results of the detectors, the engineering preparation of infrared focal plane detectors of 1 k×1 k, 2 k×2 k and other specifications based on the liquid phase epitaxial HgCdTe at the tellurium-rich level has been realized, the preparation of high-temperature working, long-wave and very long-wave detectors has been realized by using double-layer heterojunction materials, and the development of infrared focal plane detectors of 2.7 k × 2.7 k, 5.4 k × 5.4 k, 8 k × 8 k and other specifications has been realized by using HgCdTe films prepared by molecular beam epitaxy, which has great application potential in the aerospace field.

Large laser gyroscopes, based on the Sagnac effect, are considered to be suitable sensors for precise monitoring of the Earth's rotation for potential ground-based scientific research and major engineering applications, such as Universal Time 1 (UT1), solid Earth tide observations, rotational seismic wave detection, and the testing of predicted gravitational magnetic effects in general relativity. The sensitivity of laser gyroscopes increases with the size of their ring cavity and the long-term stability of its operation is influenced by environmental changes. The paper explores the impact of various environmental factors on the sensitivity and stability of large laser gyroscopes. It delves into the effects of temperature, tilt, air pressure, and wind, and the Sagnac frequency difference correction and disposal method of monitoring the changes of environmental factors on its output are analyzed and illustrated, so as to provide relevant guidance for the enhancement of the application performance of large laser gyroscope.

In this paper, the temperature field, stress field and corresponding thermal distortion of Yb∶YAG crystal slab laser module during high power operation at different cooling temperatures are simulated and analyzed. The results show that the temperature gradient thermal stresses and strains of the slats decrease significantly as the cooling temperature is reduced from 300 K to 77 K. The maximum principal stress is 4.14 MPa, which is only 15.6% of that at room temperature. When the cooling temperature is 77 K, the maximum principal stress is 4.14 MPa, which is only 15.6% of that at room temperature, and the maximum principal strain is 3.82×10-5, which is only 6% of that at room temperature. In order to analyze the beam quality of the output laser at different cooling temperatures of the Yb∶YAG crystal slab laser module to determine its optimal operating temperature, the 1030 nm probe light passing through the slat in one pass is simulated by the method of light tracing. It can be seen that when the cooling temperature is 77 K, the far-field spot energy is more concentrated, and the PV value of the detection light path difference is 0.7941 m, which is only 59.6% of that at 300 K. The simulation results show that the low-temperature operation is favourable to the generation of high-power and high-beam-quality laser output from the Yb∶YAG crystal slat laser module, which lays a foundation for the design of high-power and high-beam-quality Yb∶YAG crystal slat lasers.

Vertical-Cavity Surface-Emitting Laser (VCSEL) is distinguished by its ability to emit light beams perpendicular to the cavity surface. This unique characteristic allows multiple VCSEL lasers to be densely integrated on a single chip without requiring a significant amount of space. Additionally, VCSEL lasers utilize the reflective mirrors of a resonant cavity to enhance and amplify the light, leading to efficient light emission. Typically, the luminous efficiency of VCSEL lasers can range between 40% and 60%. Compared to traditional lasers, VCSELs are more apt to achieve high efficiencies. Due to their excellent integrability and high efficiency, VCSELs have found broad applications in fields such as 3D perception, automatic driving, and optical communication. Hence, the quality inspection of VCSEL lasers is becoming increasingly vital. As VCSEL lasers venture into the high-power domain, their light beam modes have evolved from fundamental mode to high-order mode. The beam has transitioned from a Gaussian-like beam to a Laguerre-Gaussian hollow ring beam. While traditional methods such as 1/e2 and D86 are quite accurate for measuring the divergence angle of Gaussian-like beams in fundamental mode, they exhibit notable discrepancies when applied to the Laguerre-Gaussian hollow ring beams in high-order mode. Given the widespread use of VCSEL lasers in crucial areas like autonomous driving, the demand for precise beam measurements has also surged. Therefore, this article adopts the D4 algorithm to measure the divergence angle of the Laguerre-Gaussian hollow ring beam and compares it with conventional methods like 1/e2 and D86. The results indicate that the new method enhances the accuracy of divergence angle measurements by up to 2.30%.

In order to explore the dynamic characteristics of droplet impact on micro textured superhydrophobic surfaces under low Weber conditions, the triangular texture micro-nano-weave is prepared on the surface of Ti-6Al-4V specimens for aerospace applications using laser micro-weave technology with nanosecond lasers at different scanning speeds, and the dynamical behavior of water droplets impacting on flat and oblique surfaces is investigated with the help of a high-speed camera experimental platform. The experimental results show that the higher the height of the water droplet impact flat surface, the less air enters into the lamella, which increases the maximum spreading coefficient. Compared with the flat surface, more air enters into the lamella when sliding on the slanting surface of the same height and the maximum spreading coefficient is the smallest. Among them, at a scanning speed of 100 mm/s, the proportion of the surface bump reaches 64.611%, the surface nanoparticles are the largest, the micron particles are the most, and the static and dynamic contact characteristics of the surface are optimal. The synergistic effects of surface structure and surface energy jointly affect the state of water droplets bouncing off the surface. This experiment can provide a reference for the preparation of superhydrophobic and active anti-icing surfaces in the aerospace field.

In this paper, the structural principle of Herriott-type long optical range cell is adopted, and the optimal solution for the number of reflections of the Herriott cell under certain conditions is obtained through theoretical research and simulation analysis, and the design of a long optical range, low-cost and small-volume optical range cell is carried out by utilizing coated concave mirrors as mirrors, and by integrating the optical elements in the cell body. After experimental verification, the designed light-range cell with a physical length of 23 cm and volume of 243 mL of optical range cell can achieve 11 m effective optical range length, and built in the TDLAS methane detection system. The results show that the lower limit of detection is the lowest concentration of 47.6 ppb, which provides an effective way promote the application of the low-concentration, high-precision, and miniaturized TDLAS methane detection system.

Due to the limited number of tasks performed by a single drone and the overall low efficiency, the drone cluster movement has received increasing attention for its good stability, diverse task execution, easy operation, and ease of control. In the laser powered drone cluster, a new type of laser multi-beam energy-supply system based on the optical phased array technology is proposed in response to the problems that the on-board energy of the drone UAV limits the range and duration of the mission, and that the traditional energy-supply method can only fulfil one-to-one energy supply resulting in low energy-supply efficiency. The system includes an overall laser wireless energy transmission scheme, the overall workflow of the system, the unmanned aerial vehicle cluster formation control based on the navigation following method. The scheme can achieve the one-to-many self-regulating energy supply to meet the energy demand of the entire unmanned aerial vehicle cluster, improve the energy transmission distance and efficiency, and accurately reach the preset energy supply area through the algorithm control of the unmanned aerial vehicle cluster. It is informative for future areas and modalities of laser wireless energy transfer applications.

Aiming at the characteristics of multi-dimension and high sensitivity obtained by new single-photon linear APD devices, an algorithm based on single-photon linear APD is proposed to extract the distance information of weak echo signal. Firstly, the echo signal is modeled using the Poisson distribution property of the weak signal, followed by counting the number of echo photons per nanosecond, performing a sliding-window summation using a distance window of equal width to the pulse width. The position of the maximum value is used as the moment of reception of the signal pulse, which in turn back-calculates the distance information. In addition, the target search strategy before tracking and the range gate matching algorithm after stable tracking are designed to effectively reduce the background light interference and computational resource consumption. And the calculation accuracy rates of 100%, 99.93%, and 96.58% are obtained when the number of echo photons is 200, 10 and 5, respectively. The pulse accumulation algorithm is designed for the single photon signal, and the computational correctness of a single photon signal echo is 99.5%. Besides, the information extraction with a signal-to-noise ratio of 0 dB or even negative dB is realized through algorithm iteration for stationary targets, and the calculation accuracy of 0.03 photon signal echo detection is 96.1%. The simulation results show that the proposed algorithm can comprehensively apply the intensity information of single-photon linear APD and single-photon sensitivity to realize the distance information extraction under the limit sensitivity domain.

Aiming at the problem that the image feature information utilized in the existing single-laser visual microdisplacement measurement methods is not rich, which leads to inaccurate measurement results, a dual-laser microdisplacement measurement method combining direct and oblique shooting, together with BP (Back Propagation) neural network is proposed to achieve high-precision measurement of displacement. In this paper, the principles of lens imaging and small-aperture imaging are adopted to theoretically analyze the dual-laser model, and ZEMAX is used to numerically simulate the ranging model to verify the theoretical feasibility and superiority of the proposed method. Secondly, according to the numerical simulation results, the experimental platform is designed and constructed for image acquisition experiments, a series of image features are extracted as the inputs to the BP network, and the displacement prediction with the displacement parameters are used as the outputs to construct the displacement prediction model. The experimental results show that the dual-laser displacement model proposed in this paper has higher measurement accuracy compared with the single-laser model, and the measurement accuracy reaches more than 99% after the introduction of BP neural network. This paper provides a new method and new ideas for the high-precision measurement of tiny displacement.

In this paper, an online energy monitoring system for laser rangefinders is designed to solve the problem of the difficulty of direct manual measurement of laser rangefinder emission energy under unattended conditions. In order to prevent the laser energy decline affects the performance of the laser rangefinder, it is necessary to monitor the working status of the laser rangefinder in real time. The structure of the energy probe and detection position was studied, and the hardware circuit was designed to measure the emission laser energy of rangefinder. The online energy monitoring system designed in this paper can realize the wide-range real-time energy monitoring of kHz repetition frequency laser rangefinder without affecting the performance, and achieve miniaturized and integrated requirements.

In this paper, the N-type annealing of medium-wave MCT materials is implemented by using mercury-rich open-tube heat treatment equipment, and the problem of how to control the mercury vapor reflux is studied and solved. Comparative experiments are carried out at the same annealing temperature and annealing time using the open-tube annealing process and the closed-tube annealing process, and it is found that with the increase of the annealing time, the Hall concentration of the chips treated by the two processes show a decreasing trend and the carrier mobility show an increasing trend. When the annealing temperature and annealing time are the same, the carrier mobility of the open tube annealing process is higher. The I-V test and the final test of the device assembly of the chip with open-tube annealing process show better performance.

Undoped GaSb material exhibits P-type characteristic, which limits its application of GaSb materials in the fields such as InAs/GaSb superlattice infrared detectors. The theoretical basis for estimating superlattice carrier concentration and growing superlattice substrate, buffer layer and electrode contact layer can be provided by exploring the electrical properties of N-type GaSb films. Te doping can achieve the preparation of N-type GaSb films by suppressing GaSb intrinsic defects. Molecular Beam Epitaxy technology is used to get the doped GaSb films which are grown on GaSb substrate and GaAs substrate at different GaTe source temperatures. GaTe source temperatures are set at 420 ℃, 450 ℃ and 480 ℃, respectively, and the electrical characteristic of GaSb films are investigated by Hall test. In the Hall test at 77K, it is found that all GaSb films grow on the GaAs substrate showing N-type semiconductors, with carrier concentration increasing with source temperature. Compared with the undoped GaSb, carrier concentration and the mobility at 420 ℃ and 450 ℃ due to impurity scattering caused by the increase in carrier concentration, and increases with temperature, but at 480 ℃, the mobility decreases considerably due to the decrease in defect density. A 7000 Be-doped GaSb buffer layer is grown on a GaSb substrate, followed by a 5000 Te-doped GaSb film. The results show that due to the presence of P-type buffer layer, the film appears as a P-type semiconductor when the source temperature is 420 ℃, the presence of hole carriers increases the overall carrier concentration of the film, but the compensation of holes and electrons significantly reduces the mobility. When the source temperature is 450 ℃ and 480 ℃, the film is still N-type semiconductor, and the carrier concentration which is 2~3 times that of GaSb film grown on GaAs substrate increases with temperature. The mobility is highest at 450 ℃ and decreases at 480 ℃. Setting the GaTe source temperature at 450℃ with higher carrier concentration and higher mobility of GaSb thin films involved in the preparation of superlattice materials can make the best effect of the whole material.

Infrared detectors are the core components of space infrared early warning satellites. With the continuous improvement of infrared detector performance, the use of larger and more spectral infrared detector focal plane array is the development trend of infrared detectors for early warning in the future. The infrared detector with longer line scale is prepared by multi-chip and multi-spectrum integration splicing to meet the large market, high resolution and multi-spectral detection capability of infrared early warning satellites. In this paper, the development status and technical route of multi-chip and multi-spectrum splicing infrared detector components at home and abroad are compared, and the application prospects of miniaturized splicing detectors in other fields are prospected. Finally, the main problems existing in the development of large-size splicing infrared detectors are pointed out.

To improve the accuracy of circuit chip fault diagnosis, the efficiency of hyperparameter setting and the efficiency of feature extraction, an improved arithmetic optimization algorithm (IAOA) based on temporal pattern attention mechanism (TPA) is proposed to optimize the bi-directional long and short-term memory network (BiLSTM) for circuit fault diagnosis. Firstly, IAOA is employed to search for the optimal hyperparameter combinations of BiLSTM to improve the diagnostic accuracy of the model. Then TPA is used to extract important features and assign weights to enhance the model feature extraction capability. Finally, the infrared temperature data collected by the infrared camera is inputted into the optimal diagnostic model to achieve circuit board chip fault diagnosis. The experiments are verified by using 0~30 V adjustable regulated power supply circuit board. The results show that the model for circuit chip fault diagnosis is as high as 98.27%, which can achieve high accuracy fault diagnosis for circuit board chips.

Photovoltaic fault detection is of great significance to the intelligent operation and maintenance of photovoltaic power plants. To address the problem of small targets and difficult detection of hot spots in infrared images of photovoltaic modules, an ran infrared hot spot fault detection model for PV modules based on improved Faster R-CNN is studied. Swin Transformer is employed as the feature extraction module in the Faster R-CNN model to capture the global information from the images and establish dependencies between the features, thereby enhancing the modeling capability of the model. Furthermore, the BiFPN is utilized for feature fusion, improving the issue of thermal spot faults that are easily ignored by the model due to the small target and inconspicuous features. Additionally, to suppress interference from background and noise in photovoltaic infrared images, a lightweight attention module called CBAM is incorporated to enable the model to focus more on important channels and key regions, so as to improve the accuracy of thermal spot fault detection. Experimental evaluations are conducted on a self-built dataset of photovoltaic component images, resulting in an impressive detection accuracy of 91.5%, which validates the effectiveness of the proposed model for detecting thermal spot faults in photovoltaic components.

In order to improve the radar and infrared stealth effect of the shielding surface, a periodic structure shielding surface with convex and concave is designed by using contour stealth technology. Firstly, four models with different shapes are established to carry out electromagnetic simulation calculation and compared with experimental measurement results, which show that the correlation coefficients between the simulation and experimental data are above 0.9, and the simulation results are accurate and usable. Secondly, the electromagnetic scattering mechanism of each model is analyzed to provide a theoretical basis for the shape design of the shielding surface. Then, the shielding surface with fluctuating characteristics is designed and after simulation calculation, it is found that the reflection coefficient of the shielding surface is less than -10 dB when the convex and concave degree radius r reaches 24 mm, and the reflection coefficient is less than -17 dB when r reaches 28 mm. Finally, the raised part of the shielding surface is filled with thermal insulation material, and it is simulated to be covered on the equipment with an operating temperature of 80 ℃. It is found that the temperature of the shielding surface with thermal insulation material is reduced by 3.5 ℃, which has a certain infrared camouflage effect.

Cement is an important basic building material that has a significant impact on social production. The rapid detection of cement raw material composition is of great significance for the development of the construction industry. The content detection of Al2O3 and Fe2O3 in cement raw meal based on near-infrared spectral analysis method is performed. Firstly, the sample set is divided by the combined X-Y distance division method. And the training set is processed by different spectral pretreatment methods. Finally, PLS and SVM are utilized to establish prediction models for NIR data respectively. The predicted results are analyzed and compared and the results show that the NIR analysis method using S-G smoothing pretreatment and PLS modeling has a better detection results. The decision coefficient R2 of the Al2O3 detection model is 0.895, and the RMSEP is 0.072; the decision coefficient R2 of the Fe2O3 detection model is 0.732, and the RMSEP is 0.023. The research results provide an effective analytical method for detecting the composition of cement raw materials, promoting the further development of the cement industry.

Uncooled infrared detectors have been applied in several fields with the development of infrared imaging technology, and how their thermal effect under laser irradiation has become one of the current research directions. In this paper, the structure and working principle of VOx imaging detector are analyzed at firstly. Then, experiments of laser irradiation VOx uncooled IR imaging equipment under saturation and point damage by 10.6 m pulse laser is carried out. Under laser irradiation saturation conditions, saturation occurs in the center image element of the spot, and at the end of the laser irradiation, the response of this image element increases by about 20 grey levels compared to the pre-irradiation period. The pixels around jamming spot center are abnormal corresponding, and return to normal after non-uniformity correction; under laser irradiation point damage conditions, a circular interference effect occurred, and the pixels in the center of the jamming spot show damage, which could not be recovered even with non-uniformity correction. And the corresponding laser power densities are given. Based on the experimental results, the diffraction effect is simulated, and it is pointed out that the diffraction, the thermal effect of the detector and the heat "overflow" are the reasons leading to the detector pixel anomaly larger than the irradiated spot. This paper is an important reference for the development of uncooled VOx detectors and the study of interference effects.

A domestically produced high-precision optical dual station spatial positioning measurement system based on close range photogrammetry technology is carried out. The paper mainly proposes a design scheme for the system, including the overall structure, camera, light source, two-dimensional turntable, moving target, processing software, and other aspects of the system design. At the same time, experimental testing is performed on the basis of design and development. Through accuracy analysis with the current high-precision measurement instrument excitation tracker, the experimental data shows that its maximum deviation is 0.2 mm, meeting the installation tolerance requirement of the main circuit equipment≤0.3 mm, verifying that the system can effectively meet the needs of high-precision measurement equipment in China, and has a certain degree of feasibility in the localisation of substitution.

In the context of increasing battlefield transparency and "find and destroy" reconnaissance strikes, camouflage has become an effective means of improving the survival of military targets and covering military operations. This paper provides a systematic analysis of reconnaissance and surveillance and various types of camouflage countermeasures covering the air-sky-earth-sea range against the background of the Russian-Ukrainian conflict. And the development direction of camouflage countermeasures is proposed from the aspects of adaptive multi-spectral camouflage technology development, lightweight and long-span camouflage equipment development, multi-dimensional camouflage strategy application and effect evaluation.

To address the problem that the point cloud on the bottom surface of the measured object cannot be acquired efficiently in 3D laser inspection, a supplementary perspective 3D point cloud scanning method based on the principle of right-angle prism refraction is proposed in this paper. The method adopts a right-angle prism to refract the bottom view image to the side, compensating for the lack of a bottom detection viewpoint for 3D detection and complements the bottom detection viewpoint. The sealing ring is taken as the defect detection object, and a structured light 3D camera is employed to collect the 3D point cloud. Compared with the direct scanning methods, this approach allows for real-time and rapid identification of surface defects with intact sealing rings in a single operation. It particularly simplifies the detection of bottom defects, eliminating the need for specialized gripping devices or complex mechanical structures such as robotic arms, and only the addition of a right-angle prism is required. Experimental results demonstrate that the point cloud scanning method with the supplementary perspective using a right-angle prism can meet the imaging requirements and effectively detect common defects such as fracture and collapse in sealing rings, achieving a detection accuracy of 100% and fulfilling the requirements of sealing rubber ring defect detection.

By detecting the laser backscattering characteristics of the ship's wake which are different from the environment, the ship's course, speed, tonnage and other key information can be counter-performed, which has a high military value. In this paper, a set of ship wake imaging detection system is constructed on top of the laser active illumination detection mode combining an industrial camera and a high-frequency laser, which achieves the effective detection of ship wake bubbles with a large field of view and a large dynamic range. Monte Carlo method is used to construct the simulation platform of ship wake imaging detection, and the feasibility of this method is verified. In addition, a prototype of ship wake image detection system based on laser active illumination is built, and a large number of experiments are carried out under the conditions of indoor laboratory pool to verify the system performance, and the influence of different system parameters on the detection performance is analyzed. At the same time, the evaluation of detection performance under visible light interference is carried out, which verifies that the system has strong anti-visible light interference ability, and provides theoretical support for the practice of laser active illumination imaging detection mode in ship wake detection.

Hyperspectral unmixing is the process of extracting endmembers and abundance features through image decomposition. However, intra-spectral variability caused by factors such as illumination and atmosphere, or in-ter-spectral variability caused by non-linear factors such as environmental changes and equipment, can lead to a decrease in feature extraction accuracy. To comprehensively consider the issue of spectral changes during the unmixing process, an enhanced spectral unmixing optimization model is proposed in this paper by introducing a low-rank orthogonal prior for spectral variability. Firstly, a variability data fitting term is introduced on top of the linear unmixing model to account for both intra-class and inter-class spectral variations. And a scaling factor is used to address intra-class variability in the spectrum, while a spectral variability perturbation matrix is added to address inter-class variability. Secondly, the model utilises orthogonal prior constraints to achieve the low spatial coherence between the original spectral dictionary and the variability term, and suppresses tiny tiny components and noise by employing kernel norm logarithmic relaxation to strengthen the low-rank property of the abundance matrix. Finally, the alternating optimization method and vector-matrix operator are used to reduce the complexity of the solution algorithm. The results of simulation tests on both simulated and real datasets show that the proposed algorithm achieves better performance than the comparison algorithm, which verifies the effectiveness of the optimization model.

At present, projection compensation algorithms have achieved good research results, but most of the projected image color compensation research ignores the optical part of the color transfer function modeling process, resulting in poor modeling accuracy of the color transfer function. At the same time, most of the deep learning network optimization designs are less for the phenomenon of deepening the network resulting in the loss of extracted feature information in the process of projected image colour compensation. To address the above problems, a luminosity compensation method for projected images based on attentional feature enhancement is proposed in this paper. The method extracts feature information from the projected surfaces with colored textures by increasing the depth of the network, and employs deep learning to fit a complex composite radiative transfer function to solve the problems of traditional photometric compensation methods, which improves the quality and colors of the projected images, and further eliminates the reliance on high-quality projection screens. The luminosity compensation results of the proposed method in this paper are better than other comparative algorithms in three evaluation indexes, Peak Signal-to-Noise Ratio (PSNR), Root Mean Square Error (RMSE) and Structural Similarity Index Measure (SSIM). Compared with the CompenNet series of methods, the proposed method in this paper improves up to 5.717% in PSNR evaluation metrics, reduces up to 14.968% in RMSE evaluation metrics, and improves up to 2.893% in SSIM evaluation metrics.