With the rapid development of autonomous driving and intelligent transport systems, vehicle-mounted LiDAR has become a key technology in this field. As a core component of autonomous driving, the efficient operation and accurate measurement of vehicle-mounted LiDAR play a decisive role in the overall performance of the system. Firstly, the basic concept of vehicle-mounted LiDAR and its structural characteristics are introduced. Then, the importance of various evaluation parameters and hardware parameters in evaluating the performance of vehicle-mounted LiDAR systems and their specific impact on the system performance discusses are discussed in detail. And the research progress of various parameters is summarized, and finally a series of ideas on optimizing the performance of vehicle-mounted LiDAR are concluded and the future development trend of vehicle-mounted LiDAR is outlined.

In order to cope with the impact of airborne directed energy weapons on air warfare, it is necessary to scientifically study and judge their development status. Firstly, the basic concepts, combat application scenarios, advantages and disadvantages of airborne directed energy weapons are studied, and the development of major airborne high-energy lasers and high-power microwave weapons in foreign countries is analyzed, and then the main practices of foreign countries in the development of directed energy weapons are studied. Foreign countries rapidly advance the development of airborne directed energy weapons through forward-looking layout, establishment of perfect management institutions, sustained investment, and attention to the construction of supporting test facilities, etc. The airborne high-energy laser weapons maybe the first directed energy weapons to be realized, airborne high-power microwave weapons will remain as the main form of the combat section of missiles and bombs in the short term. Airborne directed energy weapons should carry out mounted tests as early as possible, continue to overcome the miniaturization, high power-to-weight ratio, high efficiency ring control, electromagnetic compatibility protection and other difficult problems, breakthroughs in the mode of combat use, overall design and integration, test platform construction, test and evaluation and other key technologies, and sustained inputs, long-term layout of the synergistic development of the emphasis on the construction of a common air test platform, increase the exploratory flight test, and promote the technological through constant testing gradually mature.

For a laser with stable performance, the entire system is in a stable state of heat exchange during the working status, that is, the laser wavefront aberration can remain stable and unchanged. Based on this feature, the fabrication of free-form mirrors is proposed to correct the wavefront aberration of the laser and improve the beam quality. Firstly, the wavefront compensation principle, design and manufacturing process of the free-form surface mirror are introduced, then its wavefront compensation ability is theoretically simulated through mathematical modeling, and finally the wavefront compensation experiment is carried out in the slab solid laser. The result is that the free-form surface mirror improves the laser beam phase and far-field beam quality at an output power of 12.5 kW. Unlike anamorphic mirrors, free-form mirrors are not constrained by actuator spacing, and are therefore more effective at correcting higher-order aberrations, are less expensive, and do not add to the complexity of the system, each of which has its own advantages over an adaptive optics system.

Terrestrial laser scanning (TLS) is a widely adopted method for acquiring point cloud data, and ground filtering represents a crucial step in the processing of such data. Due to scanning angle variations and station setup conditions, the distribution range of non-ground points within TLS data tends to be significantly broader than that of ground points. Moreover, existing ground filtering methods often assume a uniform distribution of ground points throughout the entire scanning scene, a presumption not entirely applicable in the context of TLS. To address this challenge, this study proposes an iterative analysis approach for ground filtering utilizing relative density and based on the scanning lines of the ground-based point cloud. The methodology involves the restoration of the angular resolution and scanline information of the disordered ground laser point cloud. Subsequently, scanline-by-scanline relative density analysis is conducted to derive both the ground candidate point set and the non-ground point set. The ground candidate point set is incrementally integrated into the relative density analysis, iteratively combined with the scanline, until the number of newly generated non-ground points falls below the predefined threshold. Upon satisfying this criterion, the iteration is terminated, and the remaining candidate points are designated as the final ground point set. The proposed method is experimentally validated using three sets of data, and comparisons with existing approaches are presented. The results demonstrate the method's effective constraint on the range of ground points, showcasing a more accurate filtering effect, particularly in the transitional zones between ground and non-ground, such as wall footings, curbs, and poles. These results highlight the method's suitability for ground filtering in TLS data.

Laser echo signal is a commonly used signal for circuit detection and transmission, and the signal strength is the key to ensure the detection effect of integrated circuits. Therefore, a method for enhancing circuit detection laser echo signal in asynchronous transmission mode of large data is proposed. The background noise of the laser echo signal is eliminated by using the multi-weight mixture distribution model. According to the communication mode of asynchronous transmission mode, a laser echo signal receiver is established to receive and retain complete signal cells. Using shaping pulse signal processing methods to complete signal accumulation and adaptive matched filtering, the enhancement of circuit detection laser echo signals in asynchronous transmission mode of large data is realized. Experimental results show that the signal enhancement results of the proposed method have high energy and spectral intensity at any wavelength.

In recent years, with the rapid development of deep learning, a large number of monocular depth estimation algorithms have emerged. However, the lack of geometric constraints such as disparity, the depth prediction accuracy limits the further improvement of the depth prediction accuracy of the algorithm and fails to meet the needs of practical applications, soa depth estimation network that integrates images with sparse laser points is proposed in this paper. Firstly, the depth prediction accuracy is improved by inputting the high-precision ranging results of a small number of laser points in real time. Secondly, in order to solve the problem of uneven distribution of LiDAR points from self-collected data, on the basis of the supervised network, the relative position estimation network is added to be trained jointly with the depth estimation network. And two loss functions of luminance consistency and depth reprojection are added at the same time. Finally, the self-collected data are utilized to conduct the experimental analysis, and the experimental results show that when 160 laser points areused, the absolute relative error of depth prediction can be reduced from 10.1% to 7.6%, and when 1280 laser points are used, the change of the absolute relative error of depth prediction tends to stabilize to 4.1%.

The overshoot synchronized jamming forwards the jamming signal into the laser guide head wave gate with a fixed amount of overshoot, the jamming success probability is basically fixed, and the jamming and guidance signals are in the wave gate at the same time, so that the guide head has the opportunity and conditions to take further anti-jamming measures. According the principle of real-time wave gate, a new jamming strategy based on wave gate decoy is put forward in this paper. Firstly, the jamming signal is designed to explore the mechanism of interference. Then, by analyzing the timing relationship and interaction process of the guidance signal, the interference signal and the wave gate, the signal distribution within the wave gate under the interference condition is obtained. Finally, typical parameters are selected, and two interference states, the synchronization jamming and the wave gate decoy, are simulated to obtain the characteristics of wave gate on signal admission under interference conditions. The relative advantage of wave gate-induced bias interference is verified with probability analysis, and the analysis results can provide a reference for the design of interference parameters and processes.

Tunable Diode Laser Spectroscopy (TDLAS) technology is now widely used for natural gas leakage monitoring at field stations due to its excellent sensitivity, accuracy and anti-interference properties. In order to overcome the limitation that a single TDLAS laser telemetry instrument cannot obtain the influence range of leakage gas diffusion, an intelligent monitoring method based on the collaboration of multiple TDLAS telemetry instruments is proposed in this paper. By scanning the leaked gas masses in different oblique planes, the outer contour equations of gas leakage in different oblique planes according to the Brianchon's theorem are obtained. The three-dimensional spatial leakage impact area of natural gas is reconstructed to carry out monitoring and early warning in real time.

To solve the problem of slow tunnel deformation and difficulty in obtaining effective experimental detection data leading to limited research on tunnel deformation detection technology, a digital twin method for tunnel deformation detection is proposed, and a high-fidelity tunnel twin model is establishedin this paper. The deformation of tunnel is simulated by finite element method, and the true value of tunnel twin model is obtained. A virtual simulation platform is built to realize the three-dimensional laser scanning of tunnel models in a virtual environment to obtain large sample detection data and assist in training deformation detection methods. In deformation detection, Geotransformer neural network is used to realize tunnel point cloud registration, and tunnel section point cloud is obtained by fitting tunnel central axis to realize tunnel deformation analysis. Experimental results show that the proposed method can effectively overcome the problem of tunnel deformation detection technology research limited by experimental sites. The average error of tunnel model surface reconstruction is 0.00253 mm and the maximum error is 1.1325 mm. Compared with the true value of deformation output by finite element method, the average error of deformation detection is less than 0.34 cm. It is verified that the deformation detection method has high accuracy and basically meets the engineering requirements.

Edge-emitting semiconductor lasers have significant differences in the direction of fast and slow axes, and have inherent astigmatism, which seriously affects the transmission distance of underwater communication. Therefore, a set of underwater laser optical antenna system consisting of fast and slow-axis collimators and Galilean beam expander mirrors is designed based on the Gaussian beam characteristics and collimated beam expanding principle in this paper, and the simulation tests of energy loss and divergence angle are also carried out. According to the test results, the divergence angle in the direction of the fast and slow axes of the semiconductor laser is compressed from 49 ° and 9 ° to 0.315 mrad and 0.180 mrad, respectively. And the antenna system can achieve underwater propagation over a distance of 100 m. The difficulty of calibration and fixation of the fast and slow axis collimating mirror in practice is reduced, with a Z-axis tolerance of within 20 m for the fast and slow axes, and a detector power attenuation of less than 3.9%. This design is compact, easy to process and assemble, with high practical application value, which helps to solve the problems of severe energy loss and low coupling efficiency in underwater long-distance propagation.

Electrode shaping technology is an important part of infrared detector, and ion beam etching technology is suitable for preparation of low-damage, high-uniformity and productive electrode systems due to its many advantages such as high anisotropy and high resolution. In this paper, the electrode structures of the planar and mesa devices are prepared by ion beam etching. The morphology and structure of the electrodes under different etching conditions are characterized by FIB and SEM, and the effects of different etching angles, energies as well as heat treatment on the infrared detector are studied. The results show that the ion beam etching technology has many advantages such as smooth sidewalls, high uniformity, strong stability, and high process repeatability. Moreover, ion beam etching can also achieve electrode isolation of mesa junction devices, but there are certain metal electrodes on the sidewall of the mesa, which require further optimization of the etching angle. On the effect of heat treatment on etching, the lattice damage caused by low energy etching can be repaired after high temperature activation. High energy etching causes both lattice and electrical damage, and heat treatment can only improve the performance of the PN junction to a certain extent. The Electrical damage forms a serious leakage effect on the surface of the PN junction, weakening the quality factor R0A of the detector.

In response to the problem that existing methanol gas detection methods cannot meet the rapidly growing demand for rapid detection in the fuel cell market, a detection system design and quantitative analysis were conducted focusing on methanol gas. Firstly, the light source was selected based on the infrared absorption characteristics of methanol gas, and its driving circuit was designed. The gas modulates the light source. Secondly, an orthogonal lock-in amplification system was designed using wavelet decomposition and lock-in amplification techniques. The lock-in amplification output signal was further processed using wavelet decomposition, achieving a detection limit of 9 ppm and a response time of approximately 2 s, enabling the detection of weak signals. Lastly, an analysis model was established based on linear regression with a signal determination coefficient of 0.979. Experimental results demonstrate that the designed methanol detection system has accurate predictive capabilities and high sensitivity, enabling rapid and quantitative detection of methanol.

To preserve image edge and background information during the fusion of infrared and visible images, an improved co-occurrence filtering algorithm is proposed in this paper. It is first analyzed that the co-occurrence filtering effect depends on the filter scale standard deviation and the image content. Secondly, the filtering scale is optimized based on skewness of pixel intensity and pixel energy, and filtering speed is improved by adjusting the threshold for pixel-to-pixel distance. Finally, the NSST algorithm uses different fusion methods for the low and high frequency subbands of the image, and the low-frequency subbands of the image are fused using Delaunay interpolation calculation, the maximum symmetric surround saliency method, and the sum modified Laplacian method is used for fusion of high-frequency sub-band images. The experimental simulation demonstrates that the fusion results of this paper's algorithm are richer in the edge detail part, no artifacts appear, and have obvious advantages in both subjective vision and objective indexes.

In order to meet the demand for all-day observation in near-Earth space by star sensors, star sensors based on short-wave infrared (SWIR) detectors have been widely used. However, noise such as stripe non-uniformity and defective pixels are present in SWIR images, which degrade the quality of the images. To suppress the influence of the above noise, a noise suppression algorithm for SWIR star image is proposed in this paper. Firstly, the two-point method is used to make a preliminary non-uniformity correction to reduce the non-uniformity between pixels in the same column. Then, the influence of the stripe non-uniformity noise is removed by an improved column-Top-hat algorithm. Finally, the star point is extracted by the connected domain algorithm based on center point diffusion. The experimental results show that the proposed algorithm can suppress the influence of noise well within two magnitudes, and the extraction error of the star points can be kept within 0.3 pixels, i.e., 2". Meanwhile, the algorithm is designed for a single-frame images, which is easy to implement and can satisfy the requirements of real-time processing.

The radar cross section (RCS) of a photoelectric turntable through software simulation. Based on the principle of high-frequency locality of scattering, the RCS prediction of the target is completed. Simulate the RCS of the photoelectric turntable in the S, C and X bands, under 0~3 incident residual angle. Decompose the complex optoelectronic turntable, study the RCS characteristics of each part, and carry out stealth design of the optoelectronic turntable. A simulation analysis was performed on the turntable after the stealth design was completed. After the stealth design, the proportion of RCS with an average value greater than 0.5 m2 was approximately 18.18%. The stealth characteristics of the photoelectric turntable were significantly improved.

To study the influence of long-wave laser on the detection performance of infrared imaging detector, interference experiments on infrared detectors are carried out using a 10.6 m laser. According to the image acquisition results, with the increase of laser power, the type of interference can be categorized into spot-invariant zone, expansion zone and damage zone, and the corresponding power threshold of each area is 9.35×10-6, 2.99×10-4 and 9.35×10-4 mW/cm2, respectively. The differences of spot characteristics under varied laser power are mainly attributed to the difference of laser action mechanism. The interference effect before the damage zone is mainly generated by electronic effect, while the damage zone is dominated by thermal accumulation. The results of this study enrich the understanding of the interference effect of long-wave laser on long-wave infrared imaging system, and provide a basis for the application of long-wave laser interference.

Broadband transmission terahertz time-domain spectroscopy plays a significant role in research fields such as material carrier dynamics and fingerprint spectrum identification. Due to the support required for low-dimensional materials, the transmission characteristics of substrates are crucial in the study of the interaction between terahertz waves and low-dimensional materials. To investigate the optical properties of different substrate materials in the terahertz range, the terahertz transmission signals of three common substrate materials are tested at first. The refractive index and absorption coefficient of each material are then calculated within the effective spectral range. The results show that CVD diamond maintains small-dispersion refractive index and absorption coefficients (less than 10 cm-1) in the frequency range of 1 THz～18 THz, making it suitable for use in broadband terahertz time-domain systems. While, fused quartz and magnesium oxide crystals exhibit significant dispersion in the broadband terahertz range, leading to a broadening of the transmitted time-domain signals, and they are only suitable for terahertz time-domain spectroscopy system studies in the low-frequency range (less than 3THz). Thus, the results provide an important reference for research based on broad-spectrum terahertz time-domain spectroscopy.

The proposed algorithm utilizes an improved YOLOv8L model to detect rotating objects (such as ships and aircraft) in complex remote sensing images with arbitrary orientation, large scale variation, and dense array of objects. By incorporating a rotating frame with angle, the algorithm achieves more accurate target localization. Firstly, the decoupling angle prediction head is incorporated into the network's head section to accurately forecast the angular information of the target object. Secondly, by integrating a coordinate attention mechanism module, the model's capability to suppress noise is significantly enhanced. Lastly, an adaptive spatial feature fusion module is introduced in the neck section to effectively address inconsistencies in feature information fusion across different scales and retain valuable information for optimal fusion. The experimental results demonstrate that the proposed algorithm achieves a detection accuracy of 73.85% on the DOTA dataset, surpassing the original YOLOv8L model by 3.53%.

With the continuous development of machine learning technology, the research on object detection technology is becoming increasingly popular. To address the issues of low accuracy and poor real-time performance in target detection, a single stage object detection algorithm CenterNet is adopted to achieve rapid recognition of targets. A CBAM attention mechanism is added to resnet50, the backbone network of the algorithm, to improve the recognition accuracy of the network on the target. In the output module of the network, a new GSConv convolution module is used to improve the detection speed without loss of accuracy. The improved algorithm is validated on the infrared datasetand its detection accuracy reaches 82.91%. The results show that that the improved CenterNet algorithm can accurately and efficiently accomplish the recognition of small infrared targets.

To address the problem of difficulty in recognizing and tracking targets using infrared thermal imaging cameras in a complex and rapidly changing battlefield environment, a moving target recognition and tracking algorithm based on infrared image processing is proposedin this paper. The algorithm mainly consists of two parts: detection and tracking of mobile targets. Firstly, the Gaussian background modeling method is used to extract moving targets. Secondly, Kalman filtering is applied to locate and track moving targets, and finally, the Hungarian algorithm is used to determine the attribution of target points. The experimental results show that compared with the SORT tracker, the proposed algorithm improves MOTA by 1.4%, MT by 11.9%, reduces ML by 6.5%, IDs by 33.3%, and FN by 13.6%, which improves the tracking accuracy and successfully realizes the tracking of multiple moving targets. The algorithm in this paper has broad application prospects in military fields.

In order to solve the problem of assembly position deviation caused by external stress interference during the working process of the robotic arm, a monitoring system based on a combination of multiple fiber optic grating sensors is designed in this paper. Based on the range of motion angles of the robotic arm, the stress field distribution characteristics of the outer and inner robotic arms are simulated and analyzed after applying stress in different directions at two characteristic positions. Based on the distribution characteristics of the stress field, a multi-FBG sensing array is designed, and the corresponding relationship between different FBG responses and external interference stresses is calculated. The experiment used 16 FBGs for online monitoring of the gripping process of the FS-MP1C small machinery, with a random external interference stress set to 2~20 N. The response linearity of 16FBGs is above 0.99, with maximum positive and negative wavelength responses of 1354 pm and -984 pm, respectively. In 100 layered interference tests, the detection rate of X-axis and Y-axis interference stress is better than 80.0%, and the detection rate of Z-axis interference stress is better than 97.5%. The average false detection rate of the system is less than 4.0%. It can be seen that this design can achieve real-time monitoring of external interference stress online, which has certain practical value.

In response to the problem of low wavelength scanning resolution of side hole fiber Bragg grating sensors in high-temperature and high-pressure annular mirrors underground, the traditional sensing optical path for frequency demodulation is improved, and a laser frequency based side hole fiber Bragg grating pressure sensing system suitable for underground annular mirrors is designed, which can perform long-distance sensing underground and effectively improve its resolution. In addition, combined with self-injection locking technology, it separates the sensor from the fiber laser unlike the traditional beat frequency demodulation optical path that uses lasers as sensors, making it easy to be applied in underground environments. The system uses a linearly chirped fiber Bragg grating as a dispersion compensation unit and a reflector on one side of the laser, transforming the wavelength change caused by pressure on the fiber Bragg grating into the cavity length change of the resonant cavity, thereby improving the detection sensitivity of the system. Moreover, the structure and measurement principle of the method used are explained, and the measurement results and accuracy are analyzed and calculated. The experimental results show that the system has high sensitivity and measurement accuracy with a pressure sensitivity of 0.12553 MHz/MPa. The proposed method has the advantages of a simple demodulation system, good stability, and adjustable sensing distance.