Because of their excellent optical and electrical properties and the special band structure, topological insulators have great prospects in the development of high-performance broadband photodetectors. However, owing to the late discovery of topological insulators, research based on them, in the field of photodetectors, is still in its early stages. Therefore, there are several problems that need to be resolved, such as the preparation of topological insulator materials of a higher quality. This review summarizes the development of topological insulator materials and further delineates the research progress of photodetectors, based on topological insulator materials from the perspective of material preparations and material systems; furthermore, it details the prospects for the development of topological insulator materials in the field of photodetectors.

With the demand of from space technology for a large field of view and higher resolution, the scale of line infrared detectors is increasing. Single point coupling mode fails to meet the temperature uniformity requirement of long linear infrared detector chips. This study compares and analyzes various types of flexible thermal links, based on the design and the testing outcomes from many domestic and international research institutes. The characteristics and applicability of the various flexible thermal link designs, in terms of thermal and mechanical properties, are summarized.

We proposed an infrared dual-band common aperture optical system, without thermalization, based on harmonic diffraction in this study. The optical system has two working bands of 3-5 .m and 8-12 .m, a focal length of 45 mm, a value of F/# of 2, and a resolution ratio of the frigorific double-color detector of 320×256 with a 30 .m pixel size. The harmonic diffractive optical element improves the large dispersion problem of the diffractive optical element over a wide wavelength band and solves the severe dispersion problem of the diffractive optical element over a wide wavelength band and low diffraction efficiency. The optical system uses harmonic diffractive optical elements to widen the chromatic aberration of the band and temperature range, so that the mid and long-wave infrared diffracted at different diffraction orders, to achieve resonant confocal imaging, and the dual-band infrared optical system are corrected using fewer optical components. This optical system also reflects the incomparable advantages of traditional optical systems with respect to improving image quality, reducing volumetric weight, and wide-band a thermalization. With the further investigation of the research and development (R&D) and manufacturing technology of dual-band detector harmonic diffractive lenses, this dual-band optical system could be widely used in military systems such as target tracking, identification, and precision strikes.

Using only three lenses, an infrared system matching 640×512 uncooled vanadium oxide long-wave focal plane detector was designed. The system has a focal length of 100 mm, an F-number of 1.1, a total length of 107 mm, and a working band range of 8-12 .m. A binary diffraction surface was introduced to realize the non-thermal temperature compensation function. The simulation design using Zemax shows that the modulation transfer function (MTF)value at the Nyquist frequency (30 lp/mm) of the system reached 0.49 in the temperature range of -40℃-+60℃, which is close to the diffraction limit. The system has the characteristics of a long focal length, large relative aperture, good image quality in the full field of view, suitable temperature adaptation, high binary diffraction efficiency, easy processing, and compact structure.

This study focuses on parameter identification for miniature stabilized platforms based on infrared imaging and offers a linearization technique to reduce the nonlinear effect on modeling identification. During the identification process, a pseudorandom binary sequence is used as the modulated input signal to drive the system, and the corresponding system output is a velocity signal. In addition, the augmented least square method is applied to identify the discrete modeling parameter. Finally, the precision of the modeling is tested in two ways: parameterization and non-parameterization. The results show that parameter modeling can adequately describe the dynamic character, similar to the real system.

To reduce structural parameters needed in the process of the state space modeling of a fast steering mirror (FSM), a modeling method based on system identification is proposed. Only two structural parameters, namely, coil resistance and inductance, are needed when using this modeling method. Based on the state model, a set of combined control systems consisting of a reduced-order observer, state feedback, an internal model, and a stabilization compensator were designed; the internal model and stabilization compensator were designed by using state feedback. Furthermore, current and angular velocity can be obtained using a reduced-order observer. The combined system can progressively track of input signals and suppress disturbances; the simulation model was built using SIMULINK. The simulation results show that, compared with the incomplete differential proportional integral derivative (PID) control system, the setting time decreases by 53.6% and the overshoot increases by 131.2% without considering the disturbance in the composite system. The dynamic and steady-state performance of the incomplete differential PID control system decreases significantly after adding the disturbance signal, while the composite system is maintained. The simulation results verify the correctness of the theoretical analysis.

Most of the published literature relating to parallel optical path fusion focuses on analysis and research of image fusion algorithms; little literature discusses the optical system for image fusion. This paper designs and analyzes a fusion optical system of visible light /low-light and a long wave infrared image fusion and parallel light path layout according to the characteristics of a hand-held fusion observation lens. Firstly, the advantages and disadvantages of a shared optical path optical layout pattern and parallel optical path optical layout pattern were introduced. The optical layout pattern of the parallel optical path was selected according to the characteristics of the handheld fusion observation lens. Secondly, according to the requirements of the hand-held fused observation lens, the “heat dissipation difference” and fixed-focus optical design of the visible light /low-light optical objective lens were determined and the internal focusing optical design was performed for the long-wave infrared objective lens. Thirdly, the image registration accuracy was analyzed from the three aspects of the optical layout, magnification, and distortion of the parallel light path, according to the design of the fused optical system. Finally, the fusion image of the actual scene of the handheld fusion observation lens was analyzed and judged; it was found that the fusion image quality is suitable and the fusion performance of the handheld fusion observation lens can meet the requirements.

For the fusion of infrared and visible images, it is easy to produce problems such as missing detail information and suppressing less noise. In this paper, an improved fusion algorithm is proposed by applying the characteristics of a rolling guidance filter, which preserves edge and local brightness. First, the input images are decomposed into base and detail layers by mean filtering. Second, the saliency maps of the input images are obtained by combining the rolling guidance and Gaussian filters. The weight maps are then optimized by guided filters of different scales. The optimized maps are used to instruct the fusion of the base and detail layers. Finally, the fused image is reconstructed by combining the merged sub-images. The method of this paper is superior on the six indicators, such as nonlinear correlation information entropy and phase consistency, compared to the classical methods such as non-subsampled contourlet transform(NSCT), image fusion with guided filtering(GFF), and two-scale image fusion based on visual saliency(TSIFVS).

Currently, maritime target detection has been widely used in the civil and military fields. However, the difficulty of target detection is increased due to the large fluctuations of seawater, the small imaging area of the target, and the insignificant features. To eliminate these problems, a Gaussian mixed-Markov random field target detection model is proposed, which uses the Gaussian mixed model to adjust the learning rate and to suppress the interference of the dynamic background. Then, using the result of the Gaussian mixed model to calculate the infrared image as the observed value of the Markov random field, a Markov random field model is established. The Markov random field model can solve the existing defects of the Gaussian mixed model. The experimental results show that the method in this paper can achieve good detection results.

Cloud phase classification plays an important role in meteorological forecast and climate research. The image of meteorological satellite FengYun-4 (FY-4) has more channels and better resolution than FY-2. So it provides new remote sensing data for the study of the cloud phase. This study uses a brightness temperature cloud phase index to obtain cloud phase data. Thereafter, using the cloud phase data and ensemble learning algorithm, we develop a cloud phase classification model. By applying the cloud phase classification model, the predicted classification accuracy of water cloud and ice cloud are 91.69% and 76.10%, respectively.

Image super-resolution algorithms based on convolution neural network can be classified into two steps: image size enlargement and image detail recovery/enhancement. During the detail recovery process, the convolution layer learns the feature directly from the input image and takes the feature as the input data of the next convolution layer. In this study, a novel convolution neural network algorithm is proposed to enhance the feature expression ability of input and channel images in convolution layers by the selective gray transformation of the input and channel images. The experimental results demonstrate that the super-resolution reconstruction effect of the proposed method is superior to several typical algorithms in both conventional infrared images and the infrared images collected from our laboratory, and the proposed method can be applied to recover more details.

An infrared image edge detection method based on edge characteristics combined with K-means is proposed in this study to solve the problem of edge extraction caused by the blurring of infrared image edges. First, human visual characteristics are combined with gray distribution characteristics at the edge of the infrared image to construct a data set reflecting its structural characteristics. Second, K-means is used to classify the data set into edge and non-edge points to extract the image edges. Third, the edge is refined using a two-step method to achieve infrared image edge detection. The experimental results show that the proposed method can extract the complete external contour of the infrared image through the adaptive threshold and retain the internal edge information, which can extract the weak edge and effectively suppress noise interference.

The infrared simulation technology of resistance array has been developed into an established infrared imaging simulation method, which not only has a larger scale but also employs a higher level of manufacturing technology. Large-scale commercial resistor array devices have been developed and applied in the development of several weapon systems, especially in foreign countries. Domestically, considerable progress has been made in this aspect, but some legacy issues related to research on traditional nonuniformity testing methods have not been well resolved. For example, Moiré fringes, edge effects, mapping, and alignment problems appear in experiments, and few researchers have proposed detailed and feasible treatment measures. In this study, an iterative nonuniformity test method based on point spread function estimation is proposed for solving the problems of Moiré fringes and edge effects. In addition, the simulation verification of the mapping ratio exceeding 1:1 is carried out. The effects of different mapping ratios and nonuniformities on the correction effect are compared, and the theoretical basis for the next experiment in this study is given.

Based on vision-based pose measurement during the trans-shipment of large optical modules, a non-public field of view(FOV) pose detection method for multi-cameras based on distance and angle constraints is proposed in this study. The method is developed by using two circular edges of the same plane at the bottom of the target of the installation module to eliminate the environmental constraints of close-range docking of large objects. While docking, the sphere of the transfer vehicle was correctly docked with the target cone hole. The two cameras were fixed in the hole of the sphere, and the circular features of the edge of the cone hole were collected. The position relationship between two cameras was obtained by multi-camera calibration in non-public FOV study on non-cooperative circle characteristic pose measurement using multiple cameras without public FOV imaging and the position and altitude information of multiple cameras were confluent. Finally, the false solutions in the pose calculation were eliminated using the constraints of two coplanar circles and two cameras' position relations. The experimental results show that the method can accurately calculate the pose. The calculation process is concise, and the results are reliable and effective. The error of the attitude angle of the circular edge feature is less than 0.5 degrees, and the calculation error of the center of the circle is less than 1.0 mm at a working distance of 1140 mm. The proposed method has practical applications in measuring the position and altitude of large targets within close range.