Whether they are applied in tactical and strategic investigations in the military, in civil field mapping, fine agriculture, coastal resource exploration, or map navigation, aerial cameras can be seen everywhere. This article first exemplifies several typical aerial film cameras of the 20th century and introduces how they work. Then, the aeronautical digital cameras are divided into three categories according to their working methods. The principles and characteristics of these working methods are briefly introduced and some typical examples of aerial digital cameras are given. Finally, the development trend of aerial cameras is summarized and predicted.

As an advanced infrared detection equipment, the infrared early warning satellite (IEWS) sys-tem is an important part of the anti-missile early warning system. However, the false alarm problem of the IEWS system seriously affects the operational effectiveness of the overall system. Based on the definition and manifestation of the IEWS’s false alarm problems, the causes and classifications of these problems are analyzed. Related technologies and research directions for false alarm suppression of the IEWS system are also discussed. This research will serve as a reference for future work in related fields.

In this study, based on the variable speed scanning of the permanent magnet synchronous motor (PMSM) in the high precision servo system, we designed an improved auto disturbance rejection controller (ADRC). The aim of our design is to address the disadvantages of the complex parameters and the delay response of the trace differentiator (TD) and expansion state observer (ESO) module. The improvement simplified the TD and ESO module, and the adjustable parameters were minimized. This helps the motor to adapt to an environment with large internal and external interferences, and to achieve high precision and a rapid response. The improved ADRC was then employed in the servo pendulum scanning mechanism of an actual project, and its performance was compared to a traditional PID controller under similar conditions. The results confirm that the improved ADRC performs much better than the PID as follows: the 0°/s.10°/s response time is 75 ms, the overshoot is less than 6%, while the steady-state accuracy is within ±1%. Further, the speed fluctuation of the variable speed tracking process is small without overshoot, the scanning cycle time fluctuation is less than 0.0041 s, and the starting angle positioning accuracy is better than 0.0015°. The improved ADRC corresponded with the actual project index requirements and has certain reference value for other systems with PMSM to achieve variable speed tracking scanning.

This study proposes a new method to limit the use of the quadrilateral model, which is applied in pyroelectric passive infrared sensor (PIR) arrays for target trajectory measurement. To this end, a triangle perception model using three sensing platforms equipped with a dynamic PIR array is introduced to measure the moving target trajectory. The single-sensing platform consists of four PIR sensors. The adjacent sensors are evenly spaced in the horizontal direction at 90., and the PIR speed is 10./s. Firstly, the three sensing platforms are arranged to form the triangle sensing model, and then, the angle information perceived by the PIR sensors from the three sensing platforms is filtered. Finally, the filtered effective information is combined with the sensing platforms’own coordinate information and time information according to the corresponding trajectory pre-rendering algorithm to derive accurate target motion trajectories and motion velocities. The experimental results show that the method overcomes the geometric constraints of the four sensing platforms, reduces the cost, and improves the accuracy of the prediction trajectory from 1.5 to 1 m. Thus, the proposed method has considerable theoretical significance and practical application value.

Stealth performance is an important combat skill indicator for contemporary ships, thus affecting the vitality of a ship directly. Infrared stealth is one of the main components of ship stealth and is one of the key points of stealth design of advanced warships in various countries. In order to study how the infrared stealth performance of a ship may be improved, its infrared point source characteristics for the 3–5 .m band and its infrared face source characteristics for the 8–14 .m band are analyzed. The infrared radiation suppression principle and design method commonly used in ships are evaluated for two kinds of infrared radiation sources. The study defines how various infrared stealth technologies can be effectively applied in ship design. This research can serve as a reference for the design of infrared stealth for a ship.

Installation errors in the process of erecting the seeker and target simulator are inevitable in infrared imaging guidance semi-physical simulation experiments. In order to improve the guidance precision and simulation credibility of the test, a static mathematical model and correction method for the installation error are established by analyzing the causes of the error. Analysis of the motion trajectory of the target simulator cell center allows classification of the installation error, following which the mathematical model of the installation error is derived. OpenCV is used to process the seeker guidance image. Next, we obtain the coordinate information needed to solve the error model, and finally, we modify the ballistic guidance model. The simulation verification is conducted to quantitatively analyze the influence of error correction on the miss distance, which has a certain optimization effect on guidance attack.

CNG composite gas cylinders are subject to alternating loads for a long time, making them prone to fatigue damage and internal defect formation. These defects decrease strength and cause safety concerns during use. Composite gas cylinders containing internal defects show no obvious macroscopic deformation, and thus, it is difficult to directly detect them. The current gas cylinder testing program lacks an effective means to rapidly detect internal defects in the winding layer, which may result in missed inspections of cylinders containing internal defects. This paper proposes a defect detection scheme based on a combination of the existing key problems associated with CNG composite gas cylinder testing and the existing gas cylinder testing standards and processes. The proposed defect detection scheme uses surface thermal imagery of the steam cleaning process inside the gas cylinder. The scheme uses the steam in the cylinder flushing process as the internal thermal excitation of the cylinder. Using the transient temperature distribution of the cylinder surface recorded by an infrared camera, an artificial neural network is applied to locate and quantitatively identify the defects in the cylinder winding layer. This experimental research shows that the artificial neural network can accurately locate and quantitatively identify the defects in the cylinder winding layer with high recognition efficiency, which is suitable for online detection of gas cylinders.

Laser spot thermography(LST) is a novel remote nondestructive testing technology. It can efficiently detect surface cracks. In this paper, a fast simulation method based on frequency domain summation and database strategy is developed to simulate the heat flow generated by the laser spot source and to investigate the relationship between crack size and temperature distribution. First, the feasibility of the new method is validated through comparison with a conventional method for both the time and the spatial domains. Second, suitable characteristic parameters are introduced, and a reconstruction algorithm based on a deterministic inversion method is developed. Finally, an infrared thermography testing system is established, and LST signals of surface cracks in a plate specimen are measured. The feasibility of the inversion method is validated by the accurate reconstruction result of crack size.

The hook tongue parts of railway locomotives undergo squeezing, flexing, and impaction over long time periods, causing material fatigue. Cracks in railway locomotives gradually expand over the long term, which can cause serious accidents. Thus, it is very important to detect such cracks. However, as the surface of a railway locomotive hook tongue is covered with rust, dust, oil, etc., conventional nondestructive testing technology cannot be applied directly to it. Ultrasonic thermography technology was used in this study to detect cracks in the coupler parts of locomotives. The technology was not sensitive to the shape of the surface and the rust, dust, and the other pollutants on it. The technology offers special application advantages in the detection of cracks and other defects. Crack flaws were detected successfully during the crack detection for a locomotive hook tongue, thereby verifying the detection ability of the technology.

At present, ultrasonic testing is widely used in rail crack detection. However, in the process of rail crack detection, there is a certain blind spot in this method, and cracks on both sides of the rail foot are not detected. Aiming at these shortcomings, an infrared thermal wave nondestructive testing platform for detecting cracks on the rail foot is proposed in this paper. Infrared thermal wave nondestructive testing for rail cracks is a new research area in the field of infrared nondestructive testing, and the establishment of the experimental platform mainly includes three parts: the selection of the thermal excitation source, the construction of the experimental platform, and the extraction of the infrared images. The technology is used to heat the surface of the rail foot through a thermal excitation source. According to the wave theory of the heat transfer from the surface to the inside of the rail foot, the transfer process can be affected by the rail’s physical characteristics and internal structure. If there are defects inside the rail, the distribution of the temperature on the rail surface will be affected according to the type of defect. The location of the internal defects of the rail can be determined according to the distribution of the surface temperature information of the rail, thereby achieving the goal of crack detection in the rail. Experimental results show that the surface temperature of the rail foot corresponding to the crack is higher than the corresponding rail foot surface temperature without cracks, proving that infrared thermal wave NDT(non-destructive testing) is feasible for rail crack detection.

Infrared images and visible light images record different aspects of the nature of a ground object, such that the fusion of two such images of the same object can compensate for a lack of information from a single data source. However, due to the distinct imaging principles involved, the difference between the same-scene images produced by a gray image sensor and a visible light sensor is large, resulting in mismatched images that are difficult to fuse. In this paper, a matching method based on the analysis of the common features of infrared and visible light images using SIFT and ORB feature detection is proposed. The SIFT operator and the ORB operator are used to simultaneously perform feature point detection. First, the same name is obtained, using RANSAC, for SIFT matching. The points are filtered, and the nearest neighbor neighboring nearest neighbor algorithm is used to obtain the ORB matching points. Then the SIFT matching points are used to geometrically constrain the distance and angle of the ORB matching points to further reduce the mismatch. Ultimately, the feature points are evenly distributed and the reliability is higher, solving the poor-matching-effect problem. The performance of the proposed method was compared with that of SIFT using four sets of infrared and visible images, with the proposed method achieving a number of correct matching feature points approximately 3.7 times, 3.2 times, 3.6 times, and 3 times higher than those achieved with SIFT. This significant performance improvement indicates the effectiveness of the proposed method.

To solve the problem of low recognition rate and high false alarm rate in the study of small pedestrian target detection in infrared image, this paper studies YOLOv3, one of the best target detection algorithms, and based on it proposes a small pedestrian detection algorithm that meets real-time requirements. Based on the fact that the classification accuracy is still insufficient in YOLOv3, this article studies the idea of feature reweighting from SENet, and introduces the SE block into YOLOv3, which improves the feature modeling ability of the network. The feasibility of the algorithm is verified by experiments with infrared images collected in actual complex scenes. The experiment results show that the improved network has higher accuracy and lower false alarm rate in small pedestrian detection task, and the algorithm maintains real-time characteristics of the original algorithm.

Traditional polarization image fusion is notorious for poor visual effects and insufficient retention of texture details. To address these problems, a new method of polarization image fusion using wavelet-based contourlet transform(WBCT) is proposed. Initially, the polarization intensity image and polarization degree image are obtained by the Stokes method for the 4 pre-processed polarization angle images. After decomposition by WBCT transform, the low-frequency coefficient is fused using the PCA transform method, and the high-frequency coefficient is fused using the regional characteristic energy fusion rule. Finally, the fused high- and low-frequency coefficients are converted by WBCT inverse transform to obtain a final fusion image with polarization characteristics. Results indicate that the image observation is comfortable in subjective vision. Moreover, comparison of the selected methods reveals an improvement in the evaluation data of the fused images in terms of objective evaluation indices.

Traditional methods of image dehazing can distort color in areas such as the sky, white clouds, and bright areas. To address these problems, a three-step method is proposed for removing image hazing using a multi-scale convolutional neural network (MCNN) and classification statistics. First, the MCNN is used to estimate the transmittance of the image. Second, the estimated transmittance is classified and the pixel values of the sky, white clouds, and other bright regions in the dark channel are determined. Finally, the radiance of the scene is smoothed by a low-pass Gaussian filter to produce a restored haze-free image. Experimental results show that this method preserves the color in bright areas after the image is defogged, retaining the natural appearance of the image. The proposed method achieves improved dehazing on both synthetic and real images.

In the applications of linear compressors, flexure bearings maintain axial periodic motion of the piston without offset in the radial direction. This is very important for the seal clearance of the compressor. The performance of different thicknesses, number of slices, spacings, and spatial arrangements of flexure of the bearing component were compared on the basis of finite element analyses. The performance of radial stiffness and the torque characteristic has been especially considered. The conclusions drawn from this study can be used to guide the design of a flexure bearing component.