In this paper, the noise and readout modes of space infrared telescopes are analyzed first. Then, the principles of four signal sampling techniques are introduced respectively: C correlated double sampling, Fowler sampling, slope sampling, and multiple accumulation sampling. On this basis, the advantages and disadvantages of four signal sampling techniques are compared and analyzed in four aspects, such as detector readout mode, noise reduction, data volume, and cosmic ray detection. Finally, the selection strategy of foreign space infrared telescope signal sampling technology is given, which is expected to serve as a reference for the development of China′s space infrared telescope.

The detection system based on Avalanche Photodiode (APD) arrays is highly suited for ultra-high sensitivity and ultra-high speed applications, and is widely used in active and passive imaging, LiDAR, medical detection, wavefront detection, optical fiber communication and other fields. The time to Digital Converter (TDC) is one of the core circuits, which completes the Time of Flight (ToF) quantification of the photons with high accuracy. In this paper, the principle of TDC circuit and the simplest direct counting structure are introduced at first, and then the development history and latest achievements of domestic and international TDC circuits applicable to APD arrays are viewed according to the three typical structures, of which the phase-interpolated TDCs are mainly introduced. Finally, the characteristics of three typical structures are compared, and the future research trends are summarized.

High-power narrow linewidth fiber lasers exhibit significant potential in precision measurement, LiDAR, spectral analysis, and nonlinear optical applications, thanks to their exceptional reliability, high electro-optical conversion efficiency, good coherence, and high beam quality. In this paper, the narrow linewidth polarized laser is investigated by using seed, multi-stage pre-amplification and main amplification. In the experiment, the narrow linewidth seed light in the 1056 nm wavelength band is amplified in multi-stages with a power output of 20 W, and then injected into the main amplification system with bidirectional pumping. The cladding pump stripping of the laser is directly fabricated on the melting point of the fiber, which can reduce the melting point and simplify the laser structure. By optimizing the ratio of pump power before and after the main amplification system, the output power of laser is 2.505 kW when the pump current is 11.2 A, and the optical-to-optical conversion efficiency of the fiber laser is 83%. And higher power output can be obtained by continuing to increase the pumping power at a later stage.

The application demand of solid-state lasers continues to grow, and traditional Nd∶YAG lasers are faced with high cost, high power consumption and poor mechanical properties due to the dependence on complex temperature control systems, which need to be solved urgently in order to expand applications. In this paper, an uncooled multi-wavelength VCSEL pumped solid-state laser design scheme is proposed, aiming to achieve high power stable output over a wide temperature region by optimizing multi-wavelength VCSEL combination. A three-wavelength VCSEL array was used as a pump source to side-pump Nd∶YAG crystals with a size of 6 mm×40 mm and a doping concentration of 1.0 at.%. Wavelength complementation of multi-wavelength VCSEL arrays effectively reduces the influence of temperature drift on crystal absorption efficiency. At the same time, the four-sided pump design improves the utilization rate of pump light range and the uniformity of particle number inversion. The experimental results show that the laser can work with high performance at 5~45 ℃, and the output power can still exceed 100 W at 45 ℃. Under the pump current of 80 A and repetition frequency of 20 Hz, the maximum peak power of 3∶2∶1 module reaches 302.8 W, and the overall fluctuation is 17.83%, which is better than that of single-wavelength module. Multi-wavelength modules maintain high stability at extreme temperatures through multi-band compensation mechanism.

The fault location and identification method of UHV transmission lines based on laser image processing technology is studied to enhance the fault location and identification effect. Firstly, a laser image of UHV transmission line is captured by single point laser scanning imager, and the laser image of UHV transmission line is denoised by Wiener filter algorithm. Subsequently, by using the improved multi-significance integration algorithm and K-means clustering algorithm, the significant color features and structural features are extracted from the denoised laser image, and the color features and structural features are fused to obtain the significant fault region of UHV transmission lines. Next, through the morphology of multi-scale contour structure elements, the significant fault region is processed and the edge image of the fault region is obtained. Based on the statistical analysis of edge image color distribution, the color decision model is constructed to highlight the fault region and extract the edge contour of the fault region. Finally, the fault location can be accurately identified by drawing the edge outline of the fault area in the original UHV transmission line laser image. Experimental results show that this method can effectively acquire the laser image of the UHV transmission line and complete the denoising process. It also successfully extracts color and structural features and generates the edge image of the fault area, thereby completing fault location identification. This method enables accurate identification of the fault location in transmission lines, regardless of the transition resistors involved.

The measurement of laser scanner in different bands is affected by the reflection characteristics of atmospheric conditions, target surface and other factors, which makes the data cross-sensitivity between bands, resulting in data exhibiting uncertainty in the time series, thus diminishing the classification accuracy of the laser data. For this reason, a multi-band laser data classification considering time series fuzzy segmentation is proposed. Firstly, combined with principal component analysis and genetic algorithm, the features of multi-band laser data are extracted, the maximum feature vector is found out, and the time series of multi-band laser data is constructed. Secondly, the genetic algorithm is employed to optimize the laser data sequence, which mitigates the impact of of cross sensitivity on the classification results. Then, the fuzzy segmentation algorithm is utilized to divide the optimized laser data sequence into several time series segments, and in conjunction with the K-means algorithm, sequence segment clustering is completed to achieve precise classification of multi-band laser data and enhance its classification accuracy. The experimental results show that this method yields high classification accuracy and excellent classification effects when applied to multi-band laser data classification.

Aiming at the shortcomings of the conventional sky screen that cannot be used in low natural light or at night, a lase sky screen with all-weather operation is investigated in this paper. The detection sensitivity of the laser sky screen is directly proportional to the voltage amplitude of the projectile signal, which ultimately determines its performance and the accuracy of velocity measurements. Drawing upon the mechanism of the laser sky screen and photometric theory, the main factors affecting the detection sensitivity are analyzed, the calculation formula of the reflected luminous power when a projectile passes through different positions within the detection light screen, and the changing rules of the signal amplitude of different positions within the detected light screen are simulated and analyzed. Through the shooting test with 7 mm steel balls, the distribution of the signal amplitudes at different locations within the screen aligns well with the predicted results. This research establishes a mathematical model for sensitivity in the context of laser sky screen applications in testing fields, providing a technical reference for ongoing performance enhancements.

To fully study the temporal evolution mechanism of strong magnetic fields in laser-induced plasma, the mechanism of strong magnetic field generation in laser-induced plasma is investigated. By analyzing the mechanism of laser plasma interaction, the coupling frequency of incident and scattered light generated by multi light nonlinear Compton scattering and strong magnetic field during their interaction is analyzed, and the induction mechanism of strong magnetic field in laser-induced plasma is obtained. Under the induction mechanism, the magnetic field strengths of the strong magnetic field temperature gradient and density gradient are calculated when they are distributed in the strong magnetic field space, so as to obtain the specific temporal evolution mechanism of the distribution of the two in the strong magnetic field space. Specific application experiments show that the two mechanisms are verified by calculating the changes in the ion current density component and the distribution of electron density, and the entropy value results in 0.28 under the current fluctuation conditions, which has high stability.

Traditional pipeline leakage detection methods relying solely on pressure sensors often suffer from inaccuracies due to various factors, including environmental noise, soil conditions, and pipeline materials around the pipeline, causing inaccurate positioning results. To overcome these challenges, a multi-point leakage localization method for buried pipelines based on laser scanning benchmark correction is studied. Firstly, laser scanning technology is used to collect images of buried pipelines and implementing benchmark correction processing. Subsequently, the Canny algorithm is adopted to detect image edges and extract geometric features and the random forest algorithm is trained with the geometric features as input. The leakage points of buried pipelines are recognized by the random forest algorithm and multi-point leakage localization is achieved through coordinate transformation. The results indicate that the studied method has the smallest average error in locating the leakage point, demonstrating high positioning accuracy and stability.

Medium-to-high-energy laser weapons are increasingly being applied to counter unmanned systems, and the study of their damage mechanism and combat effectiveness has become more and more important. First of all, based on the relevant data of unmanned and anti-unmanned system test, the damage effect of laser weapon striking coyote UAV is analyzed. Then, according to the characteristics and damage mechanism of laser weapon, the formula for calculating the irradiation intensity of laser weapon and the three-dimensional temperature field simulation and calculation model of coyote UAV are established, and finite element transient thermal analysis is used to obtain the temperature distribution cloud diagrams of different parts of coyote UAV irradiated by laser weapon and the temperature dependence of coyote UAV with temperature. Further, an in-depth study and analysis of laser thermal ablation destroying the carbon fiber shell of the coyote UAV is carried out, and the damage threshold is given. Finally, the accuracy of the thermal ablation model of laser weapon destroying coyote UAV is verified by comparing and analyzing the experimental results with the simulation results, and relevant suggestions are given for the destructive power and future development of the anti-unmanned laser weapon. This study offers valuable insights for assessing the combat effectiveness of laser weapons and equipment, refining striking methods, and developing laser protection measures.

Single-photon laser ranging technology has gained widespread application across various ranging scenarios due to its high detection sensitivity. To investigate the impact of atmospheric transmission and background radiation parameters on the background noise at the 1064 nm wavelength under the single-photon detection regime, two atmospheric radiative transfer simulation tools, MODTRAN and CART, are used to calculate and compare the atmospheric transmittance and solar radiation parameters under different detection conditions along a horizontal path, and further simulate and analyze their impact on the background noise count rates. It is found that during daytime ranging, the closer to noon, the lower the background noise, which is more conducive to detection. Additionally, when the detection altitude exceeds 3 km, the influence of ground visibility on background noise is essentially negated, and the higher the detection altitude, the lower the background noise. Moreover, in scenarios with high detection altitude and short detection distance, target background radiation should not be neglected. This paper can provide a valuable reference for the background noise levels in the design of airborne single-photon laser long-range ranging systems, particularly under all-weather conditions and various detection scenarios.

The readout circuit is a key component of infrared detector components, and the noise has a significant impact on signal readout and the performance of the imaging system. Noise is inevitable during signal transmission, but noise performance can be optimized by noise reduction techniques and reasonable design. In this paper, starting from analyzing the noise in the readout circuit of infrared detectors, two correlated dual sampling techniques are compared based on CTIA input-level simulation: pixel-level correlated dual sampling and column-level correlated dual sampling. The aim is to select a more suitable correlated dual sampling based on the requirements and characteristics of different infrared detectors to reduce the reset noise, MOSFET noise, FPN noise of the readout circuit, and while taking into account the requirements of dynamic range, linearity, and power consumption.

Reducing the pixel pitch is a crucial approach to enhancing the performance of infrared detectors, and the reduction of pixel size plays an important role in infrared detectors to improve the resolution, reduce the cost of manufacturing and the heat generation, and lower the power consumption. However, the electrode, which serves as a vital link between the HgCdTe chip and the external readout circuit, poses challenges during preparation for small-pitch infrared detectors, often leading to stripping difficulties and inadequate electrode coverage. In this paper, the effects of angle, temperature and other conditions on the growth of the electrode are analyzed, and the results show that elevating the deposition temperature makes the deposited metal film layer with HgCdTe adhesion become better, and higher the deposition temperature, the better the sidewall coverage. The closer the deposition angle is to 45°, the thinner the sidewall is, and the thinner sidewall electrode can make the stripping process less difficult, and reduce the chance of contact with the electrode sidewall falling off in the hole. At the same time, the deposition angle is also an important parameter to control the roughness of the grown film, and changing the deposition angle yields a metal film layer with lower roughness. Under the condition of deposition temperature of T0 + 40 ℃ and deposition angle of 45°, the in-hole electrode structure with easy peeling, low roughness and good adhesion is successfully prepared, which improves the performance of HgCdTe infrared devices.

Infrared imaging requires non-uniform correction of the output of the infrared detector to obtain a relatively uniform and impressive image. The dark ring phenomenon occurs during the imaging process of long-wave infrared HgCdTe detector systems, and the mechanism is confirmed through analysis, and the imaging dark ring is eliminated through optimization and improvement. This method serves as a valuable reference for other applications utilizing long-wave infrared detectors in imaging.

As the leading air control weapon in modern warfare, stealth aircraft has excellent ability of aerodynamic performance and extremely high battlefield concealment. Nevertheless, the aerodynamic thermal effect of aircraft skin and the unshielded part of exhaust plume still have a considerable infrared radiation level with the stealth aircraft moving at high speed, which provides an important basis for the infrared detection of the stealth aircraft. In this paper, the infrared radiation characteristics of stealth aircraft are studied for the photoelectric countermeasure technology in modern complex battlefield. Based on the in-house developed physically-reasonable photoelectric simulation system PRISM, the typical stealth aircraft geometric modeling, the skin temperature field calculation, and the exhaust plume physical field calculation are performed to obtain the zero line-of-sight radiation characteristics of the target. Combined with analysis of the atmospheric radiance transfer effect, the infrared radiation characteristics of the target at the detection distance of 20 km are calculated. The calculation results show that: 1) Using different infrared detection bands, the minimum values of the forward and backward radiation intensities of the target are located at the detection azimuth angles of 0° and 180°, respectively; 2) At the non-afterburning flight state, the target radiation intensity obtained by long-wave 8~12 m detection is higher than that of mid-wave detection; at the detection azimuth angle of 0°, the long-wave infrared radiation intensity is approximately 140 W/Sr higher than that of mid-wave; 3) At the afterburning flight state, while detecting from the tail direction, the target radiation intensity obtained by mid-wave 3～5 m detection is significantly higher than that of long-wave detection; at the detection azimuth angle of 0°, the long-wave infrared radiation intensity is approximately 400 W/Sr higher than that of mid-wave; 4) The aerodynamic heating effect on the skin is much more significant at the afterburning flight state; at the detection azimuth angle of 0°, the long-wave infrared radiation intensity is approximately 330 W/Sr higher than that of the non-afterburning state. The simulation results show that using the detection wavelength of 3～5 m in the mid-wave infrared and 8～12 m in the long-wave infrared, the PRISM system has good infrared imaging simulation capability for the stealth aircraft target under different flight states, which supports the infrared detection and photoelectric countermeasure research of the fifth-generation stealth aircraft.

In order to solve the problem of reduced registration accuracy due to various errors in the dual-station multi-target registration method, a minimum angle-based registration method is proposed. Firstly, the angle matrices corresponding to all the angle measurement lines in the dual stations are calculated, then the angle matrices are updated by scaling the trajectory information of each station, and finally the optimal combination of data associations is selected based on the principles of minimum angle and global optimum. The capability of the algorithm is evaluated by Monte Carlo simulation method, and the results show that the algorithm can not only enhance the accuracy of registration, but also drastically reduce computation time. When the distance between targets is 30 m, the correct rate exceeds 97%, and the algorithm's running time is approximately 0.016 ms. This algorithm outperforms other algorithms in terms of both accuracy and performance, providing an important theoretical foundation for improving the accuracy of multi-dimensional target positioning.

In this paper, the cooperative positioning error of a high-precision airborne infrared detection system for aerial point targets is studied. The principle of cooperative positioning error is analyzed, the influencing factors of error are sorted out, and the error model is established. The influence of the Time-Space-Base error and the Base-Transfer error to cooperative detection error is analyzed. The analysis results are verified through simulation. Based on the results of simulation analysis, suggestions are given on the methods to improve the cooperative detection accuracy.

Due to ever-increasing number and scale of substations, traditional inspection methods for infrared image acquisition are often hindered by factors such as light changes, noise, or other interferences, resulting in varying degrees of recognition bias in the detection effect, leading to a significant decrease in the overall detection efficiency and safety. To enhance inspection efficiency and accuracy, the infrared image target detection method for substation multi-rotor unmanned aerial vehicle inspection is proposed based on PCA technology. Inspection infrared images are captured within the determined coverage range of multi rotor unmanned aerial vehicles in substations, and the pixel information of the collected images is converted into a pixel matrix. The pulse amplitude and waveform envelope area UI signal power in the target inspection image features are calculated and combined with pixel filtering method to obtain the accurate target edges. On this basis, infrared image target detection of multi rotor unmanned aerial vehicle inspection in substations is achieved by adjusting the PCA parameters. The experimental results show that the proposed method boasts a recognition rate of up to 98.5% and an accuracy of 96%, indicating that it meets the expected design effects. This method effectively improves target detection accuracy and safety, enhances detection efficiency, and overall reliability. It exhibits excellent performance and holds high promotional value.

Smoke screen has become one of the main jamming methods in modern battlefields due to their advantages of a simple deployment method and a high cost-effectiveness ratio. However, there are fewer methods for assessing the jamming effectiveness of smoke screen and lack of quantitative assessment means. In this paper, a method for evaluating the effectiveness of smoke screen jamming based on image features (HD-EEMSSJ, HOG & Depth-Effectiveness evaluation of smoke screen jamming) is proposed, and real experimental data are obtained and the evaluation effect of the method is tested through the field test. Starting from the guide tracking mechanism, the direction gradient histogram features, depth features, cosine similarity and brightness features of the image are weighted and fused to obtain a quantitative evaluation result HD-EEMSSJ index, which can more accurately and keenly reflect the dynamic interference of the smoke screen, and provide a reference basis for the grading of the interference effect in the later stage. The results of multiple sets of experimental data verification show that the HD-EEMSSJ index provides better assessment than the traditional image quality assessment methods PSNR, RFSIM, SSIM and the EEMSSJ method proposed by the authors, with accuracy improvements of 533.15%, 170.2%, 26.4% and 3.25%, respectively.

With the escalation of war and the increasing tension in the international situation, the demand for detecting a specific location target in unmanned aerial vehicle (UAV) airborne electro-optical pods is also becoming increasingly strong. To fulfill the feedback closed-loop control of traditional electro-optical pods, encoders, gyroscopes, and many other sensors are usually added to the system, which not only makes it difficult to meet the requirements for the size and weight of the pod, but also affects the center of gravity of the system, further increasing the difficulty of control. In order to solve the above problems and meet the high-precision and lightweight real-time tracking requirements of unmanned aerial vehicle (UAV) airborne optoelectronic pods for a certain target, a sliding film observer is innovatively applied to the permanent magnet synchronous motor three loop control algorithm to replace traditional physical sensors to achieve the geographic tracking function of electro-optical pods. On the basis of traditional three loop control of motors, a sliding film observer is used to observe the angle and speed information of the motor instead of the physical sensors, and the convergence law function is optimized based on the traditional sliding film observer, reducing the vibration of the system output and improving the overall stability accuracy. The experimental results show that the stability of the sliding mode observer using the sat function as the approaching law is significantly improved compared to the sign function used in traditional sliding mode observers. The ratio of the improved overshoot to output is decreased from 5.65% to 0.32%, which helps to improve the accuracy of unmanned aerial vehicle (UAV) airborne optoelectronic pod geographic tracking.

Aiming at the technical challenge of accurately detecting ship targets in complex battlefield environments, combined with the characteristics of information complementarity between ship targets and background and interferences in different spectral bands, a multispectral infrared ship detection algorithm based on YOLOv8-n is proposed in this paper. Firstly, the backbone network is designed as a multi-stream network to extract multispectral image features separately, setting the stage for subsequent feature fusion. Secondly, the cross-fertilization residual block (SaCF) is constructed in the feature extraction stage, and the single-spectral segment feature maps are enhanced by capturing the potential correlation between different spectral segments through the self-attention mechanism of the Transformer. Finally, an adaptive hierarchical fusion module (AFM) based on the attention mechanism is designed, which guides multispectral feature fusion by generating fusion weights through the attention mechanism to improve the network's ability to recognize ship targets. The experimental results show that compared with the single-spectrum ship target detection algorithm, the detection accuracy of the multispectral fusion ship target detection algorithm proposed in this paper can reach 94.8%, which is 6.1% higher. The improved algorithm exhibits superior detection performance and is capable of handling ship target detection tasks in complex environments.

Hyperspectral unmixing aims to identify the spectral characteristics of substances (endmembers) and spatial distribution (abundance) features of substances (end-elements) from a blind source separation scenario. To address the challenges posed by a large number of mixed pixels in hyperspectral images, which can reduce unmixing accuracy, and the difficulty in accurately estimating the number of endmembers when hyperspectral data is contaminated with noise, a hyperspectral unmixing model that combines low-rank relaxation and separable total variation prior information is proposed in this paper. Firstly, the local similarity of the logarithmic function is utilized to relax the nuclear norm-based low-rank expression, thereby suppressing minor components. Then, the anisotropic total variation is redefined as a separable expression to smooth the spectral characteristics and spatial abundance features. Finally, a set of efficient solvers is designed to obtain a closed-form solution. The experimental results show that the proposed unmixing model can effectively improve the unmixing accuracy while suppressing the noise, which verifies the effectiveness of the model.