As precision guided weapons, missiles have been widely used in the battlefield, and corresponding countermeasures are also developing rapidly. Infrared decoy has become an important factor affecting the combat effectiveness of the guided missile with photoelectric seeker. In order to study the anti-decoy jamming ability of infrared self-homing missile, the physical effect environment of missile flight under the condition of infrared decoy jamming is constructed by using hardware-in-the-loop simulation system, and the anti-infrared decoy jamming ability of missile is analyzed in this paper. Through the hardware-in-the-loop simulation test, it can be seen that setting the distance between target and decoy properly can induce infrared guided missile to attack stationary target. For maneuvering target, if the decoy is placed at the right time, it can effectively induce infrared guided missile attack.

The large field-of-view optical passive astheratization system realized by using ordinary infrared optical materials has a technical problem that the number of lenses is large, and it is difficult to realize the lightweight and miniaturization when this system is applied to the current new high-resolution, large-area-array infrared detectors. To this end, a chalcogenide glass with a low temperature coefficient of refractive index is introduced, and an optical passive anthermalization imaging optical system with a working band of 8--12 m, a field-of-view of 40°×325°, an F-number of 10, and a 1280×1024 detector are designed. The design results show that in the operating temperature range of -55--70℃, the modulation transfer function (MTF) values at the detector characteristic frequency of 42 1p/mm are all greater than 035. The imaging performance of the system is good, which can meet the requirements of practical engineering applications.

The electrical and optical properties of narrow gap semiconductor mercury cadmium telluride materials directly affect the performance of infrared detectors. Doping is an effective means to improve the material properties, so it is very important to study the doping of mercury cadmium telluride materials. A step-scanning Fourier transform infrared modulated photoluminescence (FTIR-PL) spectrometer was used to measure the temperature change of In-doped mercury cadmium telluride in different annealing conditions. The signal-to-noise ratio (SNR) during the experiment was reduced and a better spectra was obtained. Based on the results, combining the Hall data, the change of energy level position caused by temperature change was analyzed as well as the change of luminescent peak intensity and position of mercury cadmium telluride materials after different annealing conditions.

Aiming at the contradiction between data processing capacity and real-time performance in current low-light-level video image acquisition and processing system, a real-time signal acquisition and preprocessing system based on FPGA is designed. The high-performance Xilinx A7 series chip is used as the main control chip. Two DDR2 SDRAM are used as the core memory device. And a CMOS sensing lens is customized as the video image acquisition device. When the hardware design of the system is completed, the engineering design and simulation analysis of the software system are carried out by Xilinx Vivado platform and Matlab. The whole process of video image acquisition, storage, processing and display in the low-light-level environment is realized. The experimental results show that the low-light-level video images acquired by the system have good real-time performance and smooth dynamic pictures.

The dewar cold head structure of the infrared detector is easily damaged by temperature impact, which directly leads to the failure of infrared detector components. This is one of the inevitable reliability problems in the development of infrared detector components. The low temperature reliability of the dewar cold head in the infrared detector was studied. Combined with the bonding failure principle and finite element simulation, the influence of adhesive thickness and overflow on the low temperature stress of dewar cold head, the relationship between the bonding area of cold head and cold finger and the detector temperature was discussed. The results show that the state of the adhesive layer is an important factor affecting the low temperature damage and temperature conduction of the dewar cold head. In the process of product development, the low temperature stress of the large array detector bonding structure can be reduced by controlling the adhesive layer, so as to improve the low temperature reliability of the cold head structure.

The cleaning process of InSb infrared detector before passivation was studied. On the basis of traditional cleaning method, a special cleaning solution was added to optimize the surface quality of InSb material before passivation. TOF-SIMS spectrometry test result showed that the Si impurity concentration on the surface of InSb material was reduced by about 85%, the concentration of main organic impurities was reduced by about 30%--60%, and the overall impurity content on the surface was significantly reduced after adding special cleaning solution. It is verified by tape-out that adding special cleaning solution for surface cleaning before passivation can improve the I-V performance and the long-term reliability of InSb photovoltaic chip significantly. This indicates that the surface quality of InSb material before passivation has an important influence on the performance and reliability of InSb infrared detectors. The optimization direction of cleaning before passivation provided in this paper has certain guiding significance.

In view of the phenomenon that the cooling head structure of an infrared detector is abnormal, the thermal resistance becomes large and the cooling head chip is not warm, the related research is carried out. In this paper, Ansys finite element software is used to carry out the simulation analysis of the cold head structure of the infrared detector. And the optimization design is carried out according to the analysis results. Through simulation analysis, it is found that under the condition of ensuring the low temperature stress and low temperature deformation of the detector chip, the stresses on the surface of the cold head and the structural parts of the cold head are significantly reduced. According to the optimized cold head structure, three new state infrared detector components are assembled. And 1000 times of aging experiments are conducted. The results show that the strength of cold head, non-uniformity of detector response, blind element rate and other key indicators do not change before and after the experiment. It is confirmed that the optimized cold head structure has higher reliability, which is beneficial to the long-term use of the detector, and the optimization scheme is reasonable.

Functional textile materials with low infrared emissivity and heat insulation are widely used in industrial and military fields. In this paper, the functional materials with low infrared emissivity and good heat insulation performance are prepared from the two aspects of low surface emissivity and controlling the surface temperature of objects. The effects of particle size and dosage of aluminum powder on infrared emissivity of coating are studied by using PA as film forming bonding material. Different hollow microbeads are used as thermal insulation filler, and the thermal insulation effect of coated fabric is studied. Finally, the low emissivity coating and heat insulation coating are combined to produce a material with low emissivity and heat insulation properties. The results show that the emissivity of 400 mesh sheet aluminum powder is lower than that of 600 mesh sheet aluminum powder. The infrared emissivity of the coating surface prepared by 20% 400 mesh sheet aluminum powder coating adhesive is as low as 0237. Since hollow microbeads are good thermal insulation fillers, 15% glass microbeads are used as thermal insulation layer, and 20% 400 mesh flake aluminum powder is used as infrared low emissivity coating. The emissivity of the prepared fiber-based composite coating material is 0507, and the temperature difference between the hot body sample and the background is 375℃. The material has good thermal insulation performance and low infrared emissivity.

In order to improve the output power of 1342 nm distributed feedback (DFB) semiconductor laser, three kinds of cavity surface film combinations are designed in this paper. Electron beam evaporation coating technology is used to coat the cavity surface of the laser, and the output power of the laser under three kinds of film combinations is tested. The results show that the highest output power of 1342 nm DFB semiconductor laser is obtained by using the combination of cavity surface film system (antireflective film: Sub/Al2O3/Ta2O5/Air, high reflection film: Sub/(Al2O3/Si)3Al2O3/Air). The reflectance of the anterior cavity surface is 02%, and that of the posterior cavity surface is 986%. At 260 mA DC, the average output power reaches more than 85 mW (an increase of 856%), and the slope efficiency increases by 829%. The output power of the laser can be greatly improved by coating the cavity surface of the laser with this combination of film systems.

Aiming at the problem of low accuracy of traditional infrared image target classification methods, a method of SVM based on PSO combined with multi-feature fusion is proposed. HOG and LBP are used to describe the contour features and local textures of targets in infrared images. The method shows the characteristics of infrared image from different aspects, so there is a certain complementarity in the expression of image features. After feature extraction, the convex hull algorithm is used to calculate the sample data, and some representative sample data are obtained, so as to improve the efficiency of classification calculation. In the training of classification model, PSO is used to optimize SVM to find the optimal penalty factor and kernel parameters of SVM, so as to improve the accuracy of classification model. The experimental results show that the accuracy of the multi-feature fusion classification model is nearly 10% higher than that of the single-feature classification model, and the classification accuracy of the final SVM model optimized by PSO is as high as 99%.

The key of forest fire prevention is to predict the fire risk effectively through the real-time fire monitoring system. By analyzing the application of UAVs in forest fire prevention, a medium wave infrared camera system for forest fire real-time monitoring based on UAVs is proposed in this paper. The focal length is 75 mm, the wavelength band is 37--48 m, F number is 20. The system can match a 1280×1024 cooled MWIR focal plane detector with pixel size of 12 m×12 m. In the optical design, three infrared optical materials (silicon, zinc selenide and germanium) are combined, and three even aspheric surfaces are introduced. The passive athermal optical design is realized as well. The design results show that the modulation transfer function (MTF) of each field of view is greater than or close to 04 at the spatial frequency of 417 lp /mm in the temperature range of -60~100℃, which has good imaging quality. Since the medium wave infrared system has high imaging quality and resolution, large field of view, adaptability in wide temperature range, compact structure and can be installed easily，it has a wide application prospect in the field of forest fire prevention.

In order to find out a fast, simple and accurate method to explore the types of mold growing on the surface of weapons and equipment after mold test, the mold test according to the standard test method is conducted in this paper. Fourier infrared spectrometer is used to test the samples corroded by different strains. Spectral data are obtained, and the identification region of spectral data is determined by principal component analysis. The minimum distance matching, spectral angle matching, spectral information divergence, spectral covariance, principal component analysis, PLS-DA and random forest are used to establish the recognition model. The results show that mold species can be identified well by the random forest algorithm, and the accuracy is expected to be more than 98%. Based on the appropriate classification algorithm, FTIR technology can realize the effective identification of bacterial species.

In 2019, the CO2M mission has been selected by the ESA as Sentinel 7 in Copernicus programme, which will be measuring CO2 concentration in terms of column-averaged mole fraction (denoted as XCO2). The payload comprises a suite of instruments addressing the various aspects of the challenging observation requirements. A push-broom imaging spectrometer will perform co-located measurements of top-of-atmosphere radiances in the near infrared (NIR) and short-wave infrared (SWIR) at high to moderate spectral resolution. A multi-angle polarimeter is co-located measurements of aerosols performed. Finally, measurements of a three-band cloud imager, co-registered with the CO2 observations, will provide the required cloud-flagging capacity at sub-sample level. This paper will review the results of the Phase A/B1 instrument studies, including technology pre-development activities, preliminary design of the CO2M mission′s instruments, etc.