2022 Vol. 51, No. 8
column
- Lasers & Laser optics
- Terahertz
- Phtotoelectric measurement
- Optical devices
- Image processing
- Optical communication and sensing
- Optical imaging
- Special issuse——Scattering imaging and non-line-of-sight imaging
- Infrared technology and application
- Special issue——Scattering imaging and non-line-of-sight imaging
- Lasers & Laser optics
2022, 51(8): 20210733.
doi: 10.3788/IRLA20210733
Terahertz (THz) wavelength lies in between millimeter waves and infrared waves in the electromagnetic spectrum. The existing optical waveguide and microwave millimeter waves waveguide technologies can be applied to the THz band. Because of the strong absorption of THz waves by water vapour and the limitation of manufacturing processes, THz devices were mainly planar structures and rectangular waveguides were commonly used for THz source and transmission. Therefore, the conversion structure between rectangular waveguides and coplanar waveguides has plays an indispensable role in determining the performance of components and systems. In recent research, the ridge waveguide has been used for impedance matching and electromagnetic field mode conversion to accomplish the high-efficiency coupling between THz wave rectangular waveguides and the coplanar waveguides. According to the simulation of CST microwave studio, the results show that the transmission coefficient (S21
2022, 51(8): 20210789.
doi: 10.3788/IRLA20210789
To evaluate the resolution, angular field of view (FOV), coalignment of fundus images and OCT scans, depth scaling and other key parameters of optical coherence tomography (OCT) equipment and ensure the accuracy and validity of the equipment output values. In this paper, a model eye simulating real human eye structure was designed and developed, including the main refractive structures, such as cornea and lens, and its parameters are traceable. A 3D resolution board for lateral and axial resolution detection was designed and fabricated based on 3D printing technology. A stepped concentric ring structure was designed and machined for FOV detection. At the same time, the cross fiber module for image matching detection and the parallel glass module for depth scaling detection were designed and manufactured, which can be adapted to the fundus groove of the model eye. Confocal Raman microscopy was used to trace the size of the 3D resolution board, and the minimum detectable values for lateral and axial resolutions were 9.7 μm and 5.7 μm, respectively. The sizes of the concentric rings and fiber diameter can be traced by a Nikon projector. The maximum detectable FOV is 109.03°, and the image matching minimum accuracy is 62.5 μm. The center thickness of the parallel glass plate was traced by a Nikon digital height gauge, and the measurement uncertainty was less than 5 μm. The test of commercial ophthalmic OCT equipment showed that the model eye metrology and calibration device based on 3D printing technology has the advantages of high accuracy, high integration, wide application range and strong stability, so it is suitable for metrology and calibration of ophthalmic OCT equipment.
2022, 51(8): 20210780.
doi: 10.3788/IRLA20210780
In this article, the problem of extracting star spots for star sensor in stray light is considered. Under this setting, the effect of extracting star spots becomes worse, which affects the accuracy and reliability of the estimated attitude. An extraction method based on optimal surface fitting is proposed for this task. First, the imaging characteristics of stray light in star sensor are analyzed, and the surface model with a closed-form solution is built. Then, the method of estimating optimal stray light background and extracting star spots is proposed. The performance of the proposed method is verified by the simulated star images and star sensor images. Experimental results show that the detection rate, false detection rate and centroid accuracy obtained by the proposed method are better than that obtained by the methods based on threshold and morphological, which shows that the proposed method can resist the disturbance of stray light.
2022, 51(8): 20210714.
doi: 10.3788/IRLA20210714
Industrial gases, represented by oil and natural gas, have penetrated people's lives and production processes. Gas leakage has become one of the major disasters in current industrial production, transportation and other fields. Meanwhile, methane emissions have become the main target of China’s "carbon emissions" strategic goal. Rapid and effective gas leakage detection technology and instruments have become the focus of research at home and abroad. In response to the improvement of the performance of the uncooled infrared focal plane array (IRFPA) in recent years, its low cost, long life and high reliability can adapt to industrial gas leakage of infrared imaging detection requirements of continuous work day and night, and a variety of gas leakage infrared imaging detection modes have been developed. Based on the analysis of different infrared imaging detection modes of industrial gas leakage, this paper designs and develops an infrared imaging detection experimental system of industrial gas leakage based on differential spectral filtering, analyses and puts forward five video image processing methods that need to be studied, and gives relevant processing models or typical processing examples. The results show that the imaging detection mode has the characteristics of high sensitivity and is an effective infrared imaging detection technology for gas leakage.
2022, 51(8): 20210793.
doi: 10.3788/IRLA20210793
Based on a high-precision atmospheric disturbance monitoring method for moving objects, speckle images and various satellite images were used as background, and an experimental study on the atmospheric disturbance caused by an airplane scale model was carried out with the airplane model under the impact of high-pressure air flow. It was verified that the refractive index gradient of atmospheric disturbance was 10−6 by visual optical detection method for atmospheric disturbance of moving objects under the conditions of various background images with different resolutions and different types. The visual atmospheric disturbance information in the same experimental condition was obtained by the traditional schlieren imaging experiment, which can directly display the information of atmospheric disturbance. Through contrastive analysis, the results showed that the atmospheric disturbance information obtained by the visual optical monitoring method was the same as the directly displayed information, so the correctness of the visual optical detection method on atmospheric disturbance in the background of satellite images was directly verified. The results of this paper verified that the correctness of the visual optical monitoring method for atmospheric disturbance of moving objects in the laboratory and the monitoring accuracy of atmospheric disturbance in the condition of the laboratory test.
2022, 51(8): 20210591.
doi: 10.3788/IRLA20210591
We studied the problems of large fluctuations in the dynamic friction torque data of lidar shafting and low precision of repeated measurements. The data cloud constructed based on the test spindle control system was fused with the GA-BP algorithm, and a self-updating control algorithm for lidar shafting friction torque detection equipment was proposed. The data cloud was constructed based on the actual speed, ideal speed, speed error and speed error change rate of the test spindle. The density and distance information were used to add and delete data, and the online control parameters were adjusted by the GA-BP algorithm. Taking the lidar shafting friction torque detection equipment to test the main shaft and the measured shaft system as the research object, the simulation experiment proves that this method improves the system’s anti-interference performance compared with the control system using the Z-N-PID algorithm. The friction torque is detected by lidar shafting friction torque detection equipment. The experimental results show that the proposed self-updating control algorithm reduces the average overshoot by 12.77% compared with the Z-N-PID algorithm, the data standard deviation after stability is reduced by 5.00%-40.63%, and the repeated measurement error is reduced by 24.20%-71.66%.
2022, 51(8): 20210750.
doi: 10.3788/IRLA20210750
In recent years, the field of civilian unmanned aerial vehicles has developed rapidly, leading to the frequent occurrence of unmanned aerial vehicle "black flying" incidents, which has brought considerable challenges to national security and social stability, and there is an urgent need to develop anti-UAV technology. In this regard, this paper proposes a follow-type directional jamming method and designs a vision-based UAV intrusion detection and automatic tracking and interception system. The HOG+nonlinear SVM scheme is used to identify the UAV, the ViBe moving target detection algorithm is added to improve the recognition speed, and UAV target tracking is realized through the KCF algorithm. Design and manufacture the hardware equipment of the UAV interception system, mainly including the tracking servo system, base and tray. Experiments show that the recognition accuracy of the system reaches 90.54%, the recognition speed is 20.56 fps, the interception platform can achieve the aim of the target UAV within 0.5 s, and the tracking effect is good. The system is tested on the built physical platform, and the results show that the system can realize the movement detection, recognition, tracking and interference of invading UAVs. The recognition accuracy is high, the real-time performance is good, and the system can automatically intercept the invading UAVs.
2022, 51(8): 20210778.
doi: 10.3788/IRLA20210778
Aiming at the problem that manual adjustment of camera parameters in structured light measurement was easy to lead to the randomness of image quality, which leads to the decline of calibration accuracy and the repetition of parameter adjustment, an adaptive parameter adjustment method for camera calibration in structured light measurement was proposed. Firstly, a set of camera automatic parameter adjustment device was designed. According to the image change mechanism of three parameter adjustment rings, three parameters of calibration plate area ratio, image clarity and image contrast were selected to define the focal length adjustment ring, focusing ring and aperture adjustment ring respectively. Secondly, in order to realize the high-precision calibration and adaptive parameter adjustment of the camera, aiming at the defects of the traditional Brenner function, an improved Brenner automatic threshold function was used to realize the accurate and rapid focusing of the image definition, segment the foreground and background of the region of interest of the calibration plate image, calculate the image contrast, and according to the calibrated reprojection error. The optimal adjustment interval of the calibration camera was determined, and the calibration parameters were adjusted by the adaptive parameter adjustment search control method. Finally, in order to improve the search and positioning speed of the motor during adaptive calibration, the parameter adjustment function model was established, and the focal length was calculated adaptively through the object distance and pixel length. The three-dimensional measurement parameter adjustment experiment shows that compared with manual calibration, the proposed parameter adjustment method can realize automatic parameter adjustment within 5 s, and the reprojection error is reduced by 66.57%.
2022, 51(8): 20210625.
doi: 10.3788/IRLA20210625
In view of light interference during indoor environment reconstruction, and phase value jump problem that occurred from the disaccord between the wrapped phase cycle and Gray-Code class cycle in phase unwrapping because of Gamma transformation in process of fringe projection and phase shift, an anti-global illumination reconstruction method based on adaptive interpolation filtering was proposed. The high speed projection method was used to reduce the influence of light source interference. Firstly, the binary defocused phase shift fringes and high frequency gray code fringes were projected onto the surface of the environment to be measured. Hilbert transform and high frequency decoding were used to solve the unwrapping phase. Secondly, the adaptive interpolation filtering algorithm was adopted to repair the unwrapping phase containing phase jumps. Finally, the morphological features of the environment to be measured were restored. The types of jump points were analyzed, and the interpolation filtering was selectively carried out to eliminate the phases jump and avoid the generation of repeated phase. Compared with other global filtering methods, our method can improve the efficiency by 90% under the condition of higher accuracy, and achieve the goal of high-speed and high-quality indoor environment reconstruction.
2022, 51(8): 20210580.
doi: 10.3788/IRLA20210580
To overcome the influence of body vibration and airflow disturbance on the alignment accuracy of the three-axis airborne optoelectronic system, a fuzzy sliding mode robust control method was proposed. First, the mathematical model of the three-axis airborne optoelectronic system was established according to the coordinate transformation relationship. Then, the fuzzy sliding mode robust control law was designed by introducing a fuzzy algorithm to estimate the interference value. Finally, the stability analysis was given, which can ensure that the three-axis airborne photoelectric system has high-precision tracking for the target orientation. The simulation results show that the proposed method has a better control effect than the fractional order control method, can track the command signal stably in 300 ms, and the maximum interference estimation error is only 0.2 N·m and has higher control accuracy, the maximum tracking error of pitch angle, roll angle and heading angle is only 0.5°, 0.7° and 0.4°, respectively, which greatly improves the alignment accuracy of the three-axis airborne optoelectronic system.
2022, 51(8): 20210757.
doi: 10.3788/IRLA20210757
Because of the divergence angle and linewidth effects, the filter’s transmission characteristics will change when a nonparallel beam irradiates the narrow-band filter. Especially at oblique incidence, the passband waveform of the narrow-band filter film is more likely to degenerate from rectangular to triangular, and negative phenomena such as the transmittance peak decrease appear. Although the known convolution model can simulate this variation numerically, there is no strict experimental verification for the model’s correctness and the accuracy of numerical analysis due to obstacles of preparation and measurement errors. For this verification, the corresponding errors are overcome through film optimization and measurement error correction. A high-performance 1064 nm narrow-band filter at an incident angle of 17° was fabricated by plasma-assisted reactive magnetron sputtering (PARMS). The transmission characteristics were measured by two spectrophotometers, Cary 7000 and Lambda 1050, separately. The spectra are coincident with the numerical simulation under different conditions. Therefore, the validity of the convolution model and the high accuracy of the numerical simulation are adequately justified.
2022, 51(8): 20210721.
doi: 10.3788/IRLA20210721
The packaging requirements of resistor arrays are high integration, high power, and deep low temperature. To make the resistor arrays work normally below 130 K when the heating power is over 100 W, an integrated package structure using liquid nitrogen for refrigeration is proposed. Finite element simulation and experimental verification are carried out. The results show that the overall error between the temperature distribution obtained by finite element simulation and the physical experiment is less than 7.67% when the thickness of the molybdenum heat sink and the ceramic electrode plate are both 2 mm and the heating power is in the range of 0.1-192.76 W. The error mainly comes from the body and interface thermal resistance of the package structure changing with temperature, while the constant thermal resistance is used in the simulation. The structure can work normally when the heating power is less than 211.90 W. Under the designed stable 100 W heating condition, the chip substrate temperature is not higher than 101.9 K, and the thermal stress is 5.66 MPa, which meets the design requirements.
2022, 51(8): 20210694.
doi: 10.3788/IRLA20210694
High-speed CMOS image sensors (CISs) have the advantages of high integration, high frame rate, low power consumption, and radiation difficulty. It is widely used in scientific experiments. When used in image measurement and diagnosis, CIS usually works at a synchronized mode triggered by an external signal. This mode, called the transient imaging mode, is quite different from the continuous imaging mode in which the sensor outputs images frame-by-frame at a specific frame rate. In this paper, the performance of a high-speed CIS that has 5T pixels and a global shutter is analysed in transient imaging mode, and the key performance of the sensor is tested using an EMVA1288 compatable device and compared with continuous imaging mode. The results show that in transient imaging mode, CIS has a larger dark current and a lower signal-to-noise ratio and dynamic range. However, the temporal readout noise and photo response nonuniformity are better. The test results could be used in scientific imaging system design and performance optimization.
2022, 51(8): 20210761.
doi: 10.3788/IRLA20210761
Time-resolved characteristics are a very important performance parameter of GaAs photocathodes used in pump detection and other fields. In this paper, the photoelectron continuity equation and the outgoing photoelectron flow density equation are calculated by solving the photoelectron diffusion model by the matrix difference method. The factors affecting the time-resolved characteristics of the GaAs photocathode include the recombination rate of the GaAs/GaAlAs rear interface, GaAs electron diffusion coefficient and GaAs active layer thickness. Then, the effects of these three physical factors on the time-resolved characteristics of the GaAs photocathode are systematically studied. The research results show that the GaAs electron diffusion coefficient and the GaAs/GaAlAs rear interface recombination rate have a nonlinear proportional relationship with the response rate of the photocathode, and the saturation response rate of the GaAs photocathode will appear as the two increase. The thickness of the GaAs active layer has the greatest impact on the response time of the GaAs photocathode. The response time of the GaAs photocathode can be reduced to 20 ps by appropriately thinning the thickness of the active layer, which can meet the fast response requirements for most photon and particle detection. This study provides necessary theoretical support for the experiment and application of a fast-response GaAs photocathode.
2022, 51(8): 20210918.
doi: 10.3788/IRLA20210918
Based on the equivalent electrical and optical heating process, radiometers are employed for the metrology of irradiation powers. Working at the liquid helium temperature, the cryogenic radiometer is designed to reduce the nonspontaneous heating by the electric components in the system and is thus currently the most accurate irradiation power metrology measurement facility. During the calibration process of an ideal cryogenic radiometer, the core device-absorption cavity should demonstrate an equivalent temperature increase for the same optical and electrical heating power. However, practical heating routines lack equivalency due to the divergence in the temperature gradient from the complicated optical-matter interactions in black coatings. Herein, utilizing the ray-tracing method, we investigate the tilting angle-dependent spatial optical field distribution in the absorption cavity. With the inclined base angle of the absorption chamber controlled at 60° and the absorption rate of the coating reaching 0.95, the energy of the laser is absorbed in the first and second reflection processes of 98% and 1.9%, respectively, with a ratio of 51.2∶1. The coincidence of the optical and electrical heating paths could thus be realized by placing heaters simultaneously on the inclined bottom plate and the lower side of the absorption cavity. Furthermore, by calculating the time-dependent system temperature with a single inclined bottom heater and calculating the double heater arrangement, an optical-electrical nonequivalency induced by the different heating paths of approximately 0.005% is indicated. Our method constructs an equivalent heating routine for optical and electronic sources, indicating a nonequivalency of 0.005% induced by the different arrangements of heaters. Multiheaters applied with delicate power are recommended to optimize the temperature discrepancy.
The satellite-based infrared hyperspectral Geostationary Interferometric Infrared Sounder (GIIRS) can achieve high vertical resolution observations of atmospheric temperature and humidity parameters, which provide a more accurate initial field for numerical weather forecasting. Based on GIIRS observation radiation, a back propagation (BP) neural network and deep learning convolutional neural networks (CNNs) are used to retrieve atmospheric temperature and humidity profiles, and the focus is on the construction of the CNN model and the optimization of parameters, thus obtaining the network model configuration with the highest retrieval accuracy. The training samples are divided into three schemes according to different surface types and the influence of whether there are clouds (scheme 1: no classification, scheme 2: land or ocean surface, scheme 3: clear or clouds) and modelling, retrieving and testing. The results show that the two retrieval algorithms both have good retrieval precision. Relatively speaking, the CNN method has a smaller retrieval bias, root-mean-square error and mean relative error at all altitudes, and the retrieval precision is higher. The temperature retrieval of the CNN method is greatly improved in the high level at 10-200 hPa, and the maximum values of the three classification schemes are 1.15 K, 1.06 K, and 1.02 K, respectively, and the humidity retrieval of the CNN method also shows improvement in the lower troposphere at 500-1000 hPa, and the averages of the three classification schemes are 0.43 g/kg, 0.41 g/kg, and 0.34 g/kg, respectively. The third scheme (clear or clouds) of the BP neural network method has the best retrieval precision of temperature and water vapour mixing ratio profiles, and the first scheme (no classification of sample data) of the CNN algorithm has the most accurate retrieval results.
2022, 51(8): 20210709.
doi: 10.3788/IRLA20210709
In the complex environment, such as cloudy days, foggy days, night, weaker light illumination and other conditions, the image has a lack of contrast, and the whole is dark. In view of this problem, an image enhancement algorithm based on trigonometric function transformation and IRDPSO is proposed. The image enhancement method mainly consists of four steps. First, the color image is converted to a gray image. Then, the contrast of the grayscale image is improved by trigonometric function transformation. Then, the image is enhanced by the Laplacian operator. Finally, a color restoration process is applied to the image. Aiming at the parameters in trigonometric function transformation and the parameter selection problem of the Laplacian operator, the improved random drift particle swarm optimization (IRDPSO) algorithm is combined with an image enhancement algorithm, the fitness function is constructed by information entropy and image standard deviation, and the parameters are optimized. The proposed algorithm is compared with four other algorithms. The experimental results show that the proposed algorithm is simple, the image information entropy is enhanced, the standard difference is large, the color distortion of the image is small and the enhancement effect is better than that of the other algorithms, and the quality and contrast of the image are improved.
2022, 51(8): 20210581.
doi: 10.3788/IRLA20210581
Aiming at the problem of synthetic aperture radar (SAR) attribute scattering center estimation, a method based on the firework algorithm was proposed. First, segmentation and decoupling of high-energy regions in the SAR image are performed in the image domain to obtain the representation of a single independent scattering center in the image domain. Afterwards, based on the parametric model of the attribute scattering center, an optimization problem was constructed to search for the optimal parameters of the separated single scattering center. At this stage, the firework algorithm was introduced to optimize the parameters. The algorithm has strong global and local search capabilities, and avoids falling into the local optimum thus ensuring the optimization accuracy and the reliability of the estimation of the scattering center parameters. The single scattering center after solution was eliminated from the original image, and the residual image was segmented into high-energy regions. And the attribute parameters of the next scattering center were estimated by inertia. Finally, the parameter set of all scattering centers on the input SAR image was obtained. In the implementation, the parameter estimation verification was performed based on the SAR images in the MSTAR dataset. The comparison of the parameter estimation results with the original image and the reconstruction of the original image based on the estimated parameter set reflect the effectiveness of the proposed algorithm. In addition, the experiment also validates the SAR target recognition algorithm based on the estimated attribute parameters. By comparing the recognition performance with other parameter estimation algorithms under the same condition, the performance superiority of the proposed method in the attribute scattering center parameter estimation was further demonstrated.
2022, 51(8): 20210956.
doi: 10.3788/IRLA20210956
Aiming at the characteristics of complex working mode and high coupling with flight state of rocket based combined cycle (RBCC) power system, a trajectory optimization model for RBCC powered hypersonic vehicle was established. At the same time, the trajectory optimization design framework and solution strategy for RBCC powered aircraft were established based on convex optimization theory. On this basis, the maximum mechanical energy at the end of the rising section was simulated. The simulation results show that the relevant models and trajectory optimization methods are feasible, and the optimization results accord with the working characteristics of RBCC power system. The trajectory optimization method proposed in this paper can effectively deal with the trajectory optimization of RBCC assisted aircraft in the ascending phase under complex working modes, and provides some new ideas for this kind of trajectory design and optimization in the future.
2022, 51(8): 20210681.
doi: 10.3788/IRLA20210681
Different types of detectors have different imaging mechanisms, and the information represented by the image is also different in some ways, which results in the information of a scene cannot be completely descripted through a single image. Therefore, it is an important technology to extract complementary information of multi-source images, remove redundant information and synthesize a composite image which can express scene accurately and completely. Image fusion is an effective solution to this kind of problem. In this paper, an infrared and visible image fusion based on multi-layer image decomposition is proposed. Firstly, using the edge-preserving characteristics of weighted mean curvature filtering and the smoothing characteristics of Gaussian filtering, a multi-layer image decomposition model was constructed. Secondly, the source images were decomposed into small-scale layers, large-scale layers, and base layer. Thirdly, an energy attribute fusion strategy was adopted to merge the base layer, an integrated fusion strategy was adopted to merge the large-scale layers, and a max-value fusion strategy was adopted to merge the small-scale layers. Finally, the fused image was reconstructed through the sum operation of the three fused layers. Experimental results demonstrated that the proposed algorithm can effectively reduce the probability of noise generation and overcome the shortcomings of missing information in the fused image.
2022, 51(8): 20210702.
doi: 10.3788/IRLA20210702
3D point cloud data processing has played an essential role in object segmentation, medical image segmentation, and virtual reality. However, the existing 3D point cloud learning network has a small global feature extraction range and cannot obtain local high-level semantic information, which leads to incomplete point cloud feature representation. Aiming at these problems, a classification, and segmentation network of object point cloud based on semantic information compensating global features was proposed. Firstly, align the input point cloud data to the specification space, and perform the preprocessing of the input conversion of the data. Then, the expanded edge convolution module was used to extract the features of each layer of the converted data and superimpose them to generate global features. In the local feature extraction, the extracted low-level semantic information was used to describe the high-level semantic features and effective geometric information, which was used to compensate for the missing point cloud features in the global features. Finally, the global feature and local high-level semantic information were combined to obtain the overall feature of the point cloud. The experimental results show that the method in this paper is superior to the current classic and novel algorithms in classification and segmentation performance.
2022, 51(8): 20210708.
doi: 10.3788/IRLA20210708
The output spectrum characteristics of a linearly chirped fiber Bragg grating (LCFBG) under localized point heating with different heating temperatures, widths and positions were investigated. The numerical simulation shows that the heating temperature and heating width applied onto the LCFBG have an obvious influence on the transmissivity and central wavelength of narrow-band transmission peaks in the transmission bandgap. The central wavelengths of the transmission peaks have a good linear relationship with the local heating positions of the LCFBG and can shift in the whole transmission bandgap region. The chirp coefficient of the LCFBG determines the wavelength tuning velocity of the transmission peaks induced by the change in the heating position. Based on the theoretical results, the spectral characteristics of the LCFBG are investigated experimentally using a commercial thermal printhead as a local heating source. The narrow-band transmission peaks are realized with high performance in terms of reproducibility, stability and potential multiwavelength tunability. The experimental results are in good agreement with those of the numerical simulation within the experimental error.
2022, 51(8): 20220028.
doi: 10.3788/IRLA20220028
Aiming at the defects of high energy consumption, susceptibility to electromagnetic interference, high cost and difficulty in laying of existing security sensor systems, a smart optical fiber sensor security alarm system with low energy consumption, high sensitivity and no electromagnetic interference is proposed. The system sensor adopts a microbent-type step fiber structure. Based on the analysis of the relationship between the optical energy loss of the microbent fiber sensor and the relative refractive index difference function of the resonant frequency, the structural parameters of the sensing unit are optimized. The experiment first tested the interference suppression algorithm. From the waveform distribution, it can be seen that the noise is greatly suppressed after using this algorithm. On this basis, the system was used to test the interference of different pseudotargets. A 650.0 nm laser with a power of 2.5 mW, a fiber power meter, a microbend fiber holder and a microbend fiber sensor with a core of 9 μm were selected to build a fiber microbend sensing experiment, and the photoelectric response characteristics of 4 different security states were determined. analyse. The results show that as long as the corresponding signal analysis methods are adopted for different interference types, the probability of system misrecognition can be effectively reduced. It can be seen that the optical fiber microbend sensing system has the advantages of high sensitivity, low energy consumption, anti-interference, etc., and meets the design requirements. It has good application prospects in the field of intelligent security.
2022, 51(8): 20210713.
doi: 10.3788/IRLA20210713
The waveguide polarizer is a key component of an on-chip integrated coherent optical system, and it has attracted much interest to design a waveguide polarizer with an ultrahigh extinction ratio, low excess loss and compact size in photonic integrated circuits. A tilted Bragg grating-based polarizer on a silicon-on-insulator platform was proposed and designed by one-dimensional photonic crystal band gap theory. The energy band structure distribution for the TE and the TM modes were calculated using the energy band theory of one-dimensional photonic crystals, and the overlap gap between the forbidden band of theTE mode and the transmission band of the TM mode were used to determine the grating structure parameters. As a result, the TM mode light could pass through the Bragg grating waveguide with a low excess loss, while the TE mode shows almost complete reflection, introducing an extremely high polarization extinction ratio. The 3D FDTD simulation results suggest that a 16 μm titled Bragg grating-based waveguide polarizer could achieve an ultrahigh extinction ratio of more than 37 dB at the central wavelength of 1550 nm over a broad bandwidth of 70 nm, and the excess loss of the device is less than 0.64 dB. With an increasing length of waveguide to 25 μm, the extinction ratio could further reach up to 46 dB. The effects of the tilt angle and etching deviation on the performance of the polarizer were also studied, and the results show that the designed structure has a good fabrication tolerance. In addition, the polarizer only needs one-step etching with a simple fabrication process.
2022, 51(8): 20210697.
doi: 10.3788/IRLA20210697
In order to improve the performance of traditional stochastic parallel gradient descent (SPGD) algorithm for wavefront distortion correction, a novel SPGD optimization algorithm based on AdaBelief optimizer was proposed. The algorithm integrated the first-order momentum and second-order momentum of the AdaBelief optimizer in deep learning into the SPGD algorithm to improve the convergence speed of the algorithm and enable the algorithm to adaptively adjust the gain coefficient adaptively. In addition, adaptive dynamic clipping of the actual gain coefficient was carried out to avoid the oscillation caused by the extreme value of the actual gain coefficient. Simulation results show that under the 37-element deformable mirror (DM), the novel SPGD optimization algorithm can effectively correct wavefront distortion under different turbulence intensities, and the Strehl ratio (SR) of different wavefront distortions after correction is improved to 0.83, 0.47 and 0.31, respectively. In addition, the SR of the proposed algorithm only needs 149, 229 and 230 iterations to reach the threshold under different turbulence intensities. Compared with the traditional SPGD algorithm and other optimization algorithms, the proposed algorithm has a faster convergence speed, and has certain advantages in stability and parameter adjustment.
2022, 51(8): 20210765.
doi: 10.3788/IRLA20210765
In order to improve the accuracy of cavity length demodulation of Extrinsic Fabry-Perot Interferometric (EFPI), a demodulation method based on the approximate cosine function of the reflection spectrum was designed based on Lissajous-Figure and standard elliptic curve fitting. The two sets of light intensity signals were fitted into standard elliptic curves by coordinate transformation to reduce the required parameters; The empirical mode decomposition was used to analyze the data. The extreme point obtained after the baseline was taken into the elliptic curve to solve the problem. The discrete data points were moved by 5, 10, 15, 20 and 25 points respectively to test the influence of five groups of different phase shifts on the demodulation results, and the group with the smallest error was selected for the transverse load experiment of EFPI sensor. The stress of 5-25 N was applied respectively, the calculated cavity length difference was compared with the theoretical cavity length difference by the demodulation method of fitting elliptic curve. The results show that the actual cavity length difference is proportional to the load, the average error is about 5.690%, and the cavity length of EFPI can be obtained accurately.
2022, 51(8): 20220231.
doi: 10.3788/IRLA20220231
Efficient sensing on resource-limited platforms is a hot research topic in the field of information processing. Different from conventional array image acquisition, single-pixel data recording and compressed sensing-based image reconstruction effectively reduce the bandwidth, but the reconstructed images generally contain many data irrelevant for high-level vision tasks. Single-pixel sensing is an emerging technique that directly infers high-level semantics from one-dimensional encoded measurements without multidimensional image reconstruction. Compared with the conventional first-reconstruction-then-perception scheme, the sensing efficiency is greatly improved. It has broad applications in many fields, such as remote sensing, intelligent transportation, biomedicine, and the national defense military. This overview focuses on the history and development of single-pixel sensing and introduces its technical architecture and research progress in computer vision applications. Finally, we outlook the development trends, hoping to provide some highlights for future studies in this direction.
2022, 51(8): 20210659.
doi: 10.3788/IRLA20210659
In this paper, a baffle with an ejector structure is designed to block the high-temperature parts in the infrared suppressor. At the same time, the baffle structure injects ambient cold air to cool its own surface to significantly reduce the infrared radiation of the infrared suppressor. The effects of bow-shaped baffle configuration on the aerodynamic performance, temperature field, and spatial distribution of infrared radiation intensity of the infrared suppressor are studied by numerical simulation. The results show that compared with the nonbaffle structure (Case 0), the baffle structure increases the pumping coefficient of the two-dimensional ejector nozzle by 115% and the thermal mixing efficiency of the infrared suppressor by 273%. Nevertheless, the total pressure recovery coefficient of the infrared suppressor decreases by 7%, and the peak values of the wall and gas infrared radiation intensity are reduced by 46% and 72% within the 3-5 μm band, respectively. Compared with the single bow-shaped baffle (Case 1) structure, the better-designed double bow-shaped baffle (Case 3) can eject ambient cold air with a pumping coefficient of approximately 0.1 and reduce the average surface temperature of its cold side from 638 K to 415 K. The peak values of the wall and gas radiation intensity decrease by 84% and 80% within the 3-5 μm band. In general, the surface temperature of the bow-shaped baffle cold side is affected by the internal eject flow of the double bow-shaped baffle, the stagnation vortex downstream of the bow-shaped baffle cold side, and the cold backflow at the narrow edge end face of the two-dimensional mixing duct.
2022, 51(8): 20210929.
doi: 10.3788/IRLA20210929
According to the vacuum and cryogenic test requirements of remote sensors, a set of infrared target background simulators that could work stably in low temperature and vacuum environments was designed and built. The simulator is mainly composed of cold diaphragm, vacuum and low temperature surface source blackbody and three-dimensional electric moving table. The cold diaphragm simulates the detection background, and the micro holes distributed on the cold diaphragm are used to simulate the detection point targets. By effectively controlling the thermal insulation and temperature control between the target simulator and the background simulator and the thermal insulation between the background simulator and the remote sensor to be tested, the stable test is realized. In addition, combining simulation optimization with practical experience, the influence of the thickness of the cold stop plate, the target phase and the collimator of the simulator is removed through simulation calculation, which effectively reduces the measurement uncertainty of the system. The simulation analysis method and the verification results in this paper have reference significance for the detection experiment of signal-to-noise ratio of infrared remote sensor point target detection.
2022, 51(8): 20220391.
doi: 10.3788/IRLA20220391
The engineering application of automatic target recognition is the key technology to realize the long-range and precise strike after the image terminal-guided missile is launched. The development history, identification method, technical level and application effect of automatic target recognition of precision-guided weapons at home and abroad are summarized. The recognition methods and application scenes based on target features and template matching are analysed, and two types of engineering verification effective methods are identified. The automatic target recognition method combines the automatic target recognition process, such as task planning, main execution content, and the impact of planning quality on different recognition methods. To meet the needs of intelligent development of precision guided weapons in the future, the engineering application of deep learning recognition technology has become a new trend. To solve the balance problem between the efficiency and application accuracy of deep learning algorithms, this paper focuses on the analysis of network pruning, weight quantization, and low rank. The key technologies of real-time acceleration inference such as approximation and knowledge distillation; for network model training, ideas for effectively solving problems such as insufficient training samples or difficulty in obtaining military target samples are proposed. With the wide application of multiband and multimode composite guidance technology, information fusion provides a new technical approach for the engineering application of target recognition. How to adapt to various complex scenes and artificial active interference is a major challenge for image terminal guidance. The robustness of target recognition under interference conditions is expounded, which is an engineering problem that needs to be urgently solved in the application of automatic target recognition technology in image terminal guidance.
2022, 51(8): 20220656.
doi: 10.3788/IRLA20220656
The cloud scene in the space-based infrared observation scene has the characteristics of geometric structure dynamic change, scale dynamic change, radiation dynamic change and is coupled with the space-based dynamic detection link, which will have a great impact on the detection efficiency of the system. Therefore, it is very important to carry out research on cloud scene simulation methods for the design of space-based infrared optical satellite systems. This paper proposes a dynamic cloud image simulation method based on the time series smoothing multiscale superposition method to solve the problems of low computational efficiency and large memory usage of traditional simulation methods in large-scale dynamic cloud image simulation applications. The interframe interpolation method is used to realize the change in the shape and structure of the dynamic cloud layer, which improves the computational efficiency by more than 10 times. Realistic simulation of the overall structural change in the position and shape of the clouds realizes the simulation of large-scale dynamic cloud images.
2022, 51(8): 20210725.
doi: 10.3788/IRLA20210725
The problem of infrared image target recognition based on classifier decision fusion was proposed. The sparse representation-based classification (SRC) and convolutional neural network (CNN) were used as the basic classifiers. For the test sample, it was first classified based on SRC, and the reliability of the decision was judged based on the output decision variables. When it was determined that the recognition result is reliable, the recognition process ended and the target category was output. On the contrary, some candidate categories with higher confidence were selected according to the results of SRC, and CNN was employed to confirm the classification result in the next stage. In addition, the CNN output result and SRC were subjected to linear weighted fusion processing, and the final target category decision was made according to the fusion result. The proposed method integrated the advantages of both SRC and CNN classifiers to comprehensively improve the performance of infrared target recognition. At the same time, this hierarchical decision fusion method avoided the two classification processes for all samples, and could ensure the overall efficiency of the recognition algorithm. The experiment was carried out using five types of infrared images of common vehicle targets in daily life, and the original sample conditions, noise sample conditions and occlusion sample conditions were set respectively. By comparing with some existing methods, the results reflect the effectiveness and reliability of the proposed method.
2022, 51(8): 20210914.
doi: 10.3788/IRLA20210914
Infrared dim and small target detection is an important part of the infrared search and tracking system (IRST). Generally, in a complex background environment, infrared dim and small target detection often has the problem of a high false alarm rate and low detection rate. To solve this problem, an improved weighted enhanced local contrast measurement (IWELCM) detection framework is proposed. First, by combining the local contrast mechanism with the signal-to-clutter ratio (SCR) calculation, an enhanced local contrast measurement is proposed to enhance the SCR of the infrared image while enhancing the suspected small target region. Second, an improved weighting function is proposed to enhance the target and suppress the background by taking advantage of the characteristics of the target in infrared images and the significant difference between the target and the surrounding background. Finally, an adaptive threshold segmentation method is used to extract real targets. Experimental results on different scene datasets show that compared with the seven existing methods, the proposed method can effectively extract real dim targets from interference objects under complex backgrounds and has better detection performance.
2022, 51(8): 20210957.
doi: 10.3788/IRLA20210957
To solve the problems of fuzzy details and low contrast of low-quality infrared images, a parallel multifeature extraction network for infrared image enhancement is proposed, and a structural feature mapping network and a two-scale feature extraction network are designed. The structural feature mapping network is used to establish the global structural feature weight to maintain the spatial structure information of the original images. The two-scale feature extraction network using multiscale convolutional layers and the attention mechanism fused dilated convolutions is applied to enhance the attention on contextual information, improve the feature extraction capability for regions of interest, and simultaneously learn feature information of different scales, complete the exchange of information of the two scales, and then generate a target enhancement map to achieve adaptive enhancement of detailed texture of target areas. Experiments have proven that the proposed method can effectively improve contrast, avoid overenhancement, enrich image details and textures, and reduce artifacts and halos. Compared with typical traditional methods and deep learning methods, the PSNR and SSIM on the BSD200 dataset are increased by approximately 37.35%, 2.1% and 25.94%, 3.15%, and increased by approximately 30.62%, 1.04% and 24.83%, 2.08% on real infrared images. The proposed method also has good generalization performance on low-quality images with different contrast factors as well.
2022, 51(8): 20220261.
doi: 10.3788/IRLA20220261
Optical imaging through scattering media is a long pursued yet unresolved problem. Researchers propose and develop kinds of methods and techniques, from the earliest time gating and spatial filtering techniques, which utilize only ballistic photons, to subsequent wavefront shaping, scattering matrix measurement and speckle autocorrelation imaging by taking advantage of scattered photons, to the popular deep learning methods latterly. Although all methods and techniques are verified by proof-of-concept experiments with thin scattering media, such as diffusers, zinc oxide layers and slices of biological tissue, they all fail rapidly as the thickness increases. The longstanding thickness challenge is still a bottleneck. In the commentary, I summarized and compared the methods and techniques in the field, reviewed the mainstream viewpoints, i.e., wavefront is completely scrambled after scattering media, analyzed the reason for the failure of existing methods and techniques through thick scattering media, and discussed the potential research directions to solve the problem ultimately in future.
2022, 51(8): 20220305.
doi: 10.3788/IRLA20220305
Limited by the methods of information acquisition and signal processing, traditional optical imaging technology can only image targets within the visual range. With the development of new imaging equipment and high-performance computing, nonline-of-sight (NLOS) imaging technology, which integrates optical imaging, computing technology and image processing, makes it possible to image beyond the field of view. Based on the differences in imaging mechanisms, we divide the existing NLOS methods into three categories: methods based on spatial coherence, two-dimensional intensity information and time-of-flight. We analyse the principles and implementations of different NLOS technologies. We focus on the time-of-flight methods and compare their imaging performance under the open dataset, which includes multiple types of targets and indoor and outdoor scenarios. Furthermore, we build a nonconfocal transient imaging system based on a detector array, capture the single-shot nonconfocal transient images and analyse the results of nonconfocal NLOS methods using these captured images. Finally, we prospect the future direction and application of nonline-of-sight imaging.
2022, 51(8): 20220256.
doi: 10.3788/IRLA20220256
Optical scattering inherent in biological tissue prohibits optical technologies from being widely used in biomedical applications. Wavefront shaping treats optical scattering as a deterministic process, enabling the control of scattered light by point-by-point phase compensation through spatial light modulators. Among various wavefront shaping technologies, digital optical phase conjugation controls the largest number of degrees of freedom and has the fastest speed, which is suitable for biomedical applications such as live-tissue imaging, manipulation, and therapy. This paper will describe the development of digital optical phase conjugation, discuss the main technological challenges encountered, and speculate on future applications.
2022, 51(8): 20220322.
doi: 10.3788/IRLA20220322
Scattering imaging has attracted widespread attention because of its ability to clearly image through scattering media such as biological tissue. In recent years, scattering imaging based on speckle autocorrelation has developed rapidly because of its noncontact nature, lack of prior information and single-frame imaging characteristics. However, speckle autocorrelation imaging is limited by the optical memory effect (OME). When the distance between multiple targets is beyond the range of OME, the autocorrelation information of different targets is aliasing in the correlation domain, resulting in a sharp drop in image quality. Based on the basic principles of the optical memory effect and speckle correlation imaging, firstly, we introduce the imaging techniques related to speckle autocorrelation and speckle correlation. Then, the main technologies and related applications of expanding the OME range are shown. Finally, we summarize the current problems of wide-field imaging technology based on speckle correlation and make suggestions for future developments and applications.
2022, 51(8): 20220563.
doi: 10.3788/IRLA20220563
More scattering imaging methods have been proposed to realize imaging using scattered optical signals. Deep learning plays an important role in the field of imaging through scattering medium with its powerful data representation ability and information extraction ability. Compared with traditional scattering imaging methods, deep learning-based scattering imaging methods have great advantages in imaging speed, imaging quality, information dimension, and other aspects. However, the problems of model training, model generalization also restrict the development of this method. Therefore, more and more studies jointly model physical processes with data-driven-based methods and use physical priors to guide neural network optimization. Compared with the simple data-driven method, the physical-data joint modeling method greatly reduces the dependence on the amount of data and the number of neural network parameters, which can effectively reduce the difficulty of data acquisition and the requirements for experimental environment under the premise of ensuring the imaging quality. The joint modeling optimization method realizes the generalization of the medium and the type of hidden targets. At the same time, the training strategy of those methods is also being optimized which is realized from the supervised to semi-supervised and then to unsupervised. The proposed different models and supervision strategies greatly improve training efficiency. Those advantages improve the method of imaging through scattering medium based on the deep learning scenario application possibility out of the laboratory while reducing the cost of hardware and time.
2022, 51(8): 20220307.
doi: 10.3788/IRLA20220307
Scattering is an ordinary phenomenon in optical imaging. The imaging light is scattered by scattering media, such as smoke, water and biological tissues, existing in imaging path. The influence of scattering disturbs the imaging target information from orderly pattern to random speckles on imaging plane. How to break the limitation of scattering media is an essential problem in the field of optical imaging. Holographic technology can record and reconstruct all the information of objects, and play an important role in light field information obtaining and interpreting. In recent years, traditional holography and correlation holography theories have been applied to the field of scattering imaging, and a series of outstanding results have been achieved. This paper mainly introduces and summarizes the theoretical principles, development and latest achievement of holography technology in the field of scattering imaging. And the vista of holographic scattering imaging is also discussed.
2022, 51(8): 20220266.
doi: 10.3788/IRLA20220266
The rapid development of scattering light modulation has led to many interesting applications in recent years. Imaging through a scattering medium and optical illusion are two of the most attractive examples, while they usually do not appear together on the same topic. Here, the inner relation between them will be further discussed, and a bifunctional scattering light modulation method that can realize scattering imaging and optical illusion is introduced. With the help of a high-resolution spatial light modulator, a highly efficient phase retrieval process and phase conjugation technique, well-designed modulation patterns are found to manipulate the scattering wavefront and realize the function of imaging through a scattering medium or optical illusion. The whole system can be completed in several seconds. Therefore, it can be done with a slow variated scattering environment for scattering imaging or a slow variated scene for dynamic optical illusion. The theory and proof of concept experiment prove the feasibility of the proposed method. The potential applications will be found in the area of imaging through turbid environments, camouflage, anti-detection, complex light modulation and so on.
2022, 51(8): 20220299.
doi: 10.3788/IRLA20220299
Imaging techniques such as speckle correlation and wavefront modulation are efficient and important to overcome the scattering effect caused by inhomogeneous media. However, the field of view of these techniques is limited, and the dynamic scattering media degrades the image quality due to the dependence on the memory effect. The shower-curtain effect is a common effect that is not limited by the field of view and the dynamic scattering medium. In recent years, with the development of various computational imaging techniques, the shower-curtain effect has been applied to different scattering scenes to overcome the scattering effect, combined with other imaging recovery methods, and has shown some unique advantages compared with traditional scattering imaging techniques. This paper summarizes the evolution of the physical model of the shower-curtain effect based on the modulation transfer function, analysing the influence of optical depth and aperture sizes. The applications of the shower-curtain effect and the Fourier domain shower-curtain effect in the field of scattering imaging are depicted. The difference and relationship between the Fourier domain shower curtain effect and other imaging techniques based on a phase iterative algorithm are discussed, and the possibility of combination with other computational imaging techniques is proposed.
2022, 51(8): 20220404.
doi: 10.3788/IRLA20220404
Light detection and ranging (LIDAR) is a kind of optical sensor with accurate positioning and efficient identification ability that can quickly acquire three-dimensional information of targets. Therefore, LIDAR plays an increasingly important role in military reconnaissance, unmanned driving, space docking and other fields. However, in complex environment such as fog, smoke, sea and so on, scattering effect in light field causes serious degradation of the received signal in traditional LIDAR. Under these environmental conditions, the performance of traditional LIDAR will decrease rapidly, or fail to work. Aiming at the degradation characteristics of received signal in scattering environment, the transmission model of Mie scattering transient light field of Monte Carlo was firstly established. Then, the time-domain distribution law of the transmission light field was simulated by computer software. According to this law, the filtering algorithm of the time-domain signal de-scattering effect was studied. Finally, a kind of penetrating LIDAR based on TCSPC was built in laboratory. Through the imaging experiments in fog simulation environment, the results verify that the penetrating LIDAR method has a good effect on improving the quality of target image reconstruction. This study provides a base for the further applications of LIDAR in complex scattering environment.
2022, 51(8): 20220215.
doi: 10.3788/IRLA20220215
Different from the static characteristics of solid scattering media such as ground glass, the scattering effect of turbid media on light beams is reflected both in the space and time domains. Most traditional scattering imaging methods are inapplicable to dynamic turbid media. To address this issue, a deep learning-based method is proposed to reconstruct objects in the presence of turbid media. The imaging quality of the proposed neural network under the conditions of different turbid media and turbid media with different concentrations is studied. The generalization ability of the neural network is tested. The experimental results demonstrate that high-quality imaging is achieved by the proposed network. Moreover, the network shows strong generalization ability and robustness under the mixed training of speckle images of turbid media with different concentrations.
2022, 51(8): 20220072.
doi: 10.3788/IRLA20220072
The phase retrieval algorithms can be used to recover the field at the distal end of a fiber from the intensity at the proximal end of the fiber. The response of the fiber can be described by the transmission matrix. In the experiment, a sufficient number of samples are sampled from the output intensity distribution with different input conditions to measure the transmission matrix. Obviously, the position distribution of sampling points, including the sampling number and interval, affects the measurement of the transmission matrix, and the accuracy and efficiency of the phase retrieval algorithm are related to the transmission matrix. We propose that the sampling interval should be greater than the speckle size to ensure the independence of different rows of the transmission matrix; therefore, image quality can be guaranteed with fewer sampling points at higher reconstruction efficiency. The experimental results show that when the sampling interval is less than the speckle size, the number of sampling points required for light field reconstruction decreases significantly with increasing sampling interval under the same image reconstruction quality. When the sampling interval is greater than the speckle size, the number of sampling points required changes slowly and finally remains approximately 3.5 times the number of pixels of the input image. When the sampling interval is fixed, with the increase in sampling points, the time consumed by the phase retrieval algorithm first decreases and then increases, so there is an optimal sampling interval and sampling points.
2022, 51(8): 20220418.
doi: 10.3788/IRLA20220418
Visual information is an important means for human beings to perceive the surrounding environment. With the great expansion of human “field of view” by optical imaging and image processing technology, the way people acquire images has broken through the limitations of the naked eye. The scattering effect leads to a significant decrease in the working distance of the optical imaging system, making it difficult to effectively observe long-range targets. Human perception of image information is usually completed by focusing, correction and stereoscopic view synthesis, which are coupled with each other. Among them, the processes of focusing and binocular image information correction can be optimized by means of optical systems and digital image processing. With the improvement of contrast under strong scattering background, the image information under scattering conditions can be perceived and analyzed. However, limited by current technology, the ability of machine stereoscopic vision is difficult to reach human level, resulting in the human visual system still being an important terminal for image perception and analysis. It is foreseeable that in order to achieve accurate acquisition and analysis of optical image information under low visibility conditions, it is still necessary to develop a global optimization technology for stereoscopic vision through the combination of human vision and machine. This study mainly introduces the physical limitations and key factors influencing the optical imaging and image fusion under turbid atmosphere or water, and presents an outlook on the role of human stereopsis in improving optical imaging capabilities.
2022, 51(8): 20210800.
doi: 10.3788/IRLA20210800
The basic characteristics of the wavefront aberration of Yb:YAG slab laser were analysed. Combined with spot shape and power density, a double deformabe mirror combined of water cooled 1D DM of 13 units and 2D DM of 95 units was proposed to correct the wavefront aberration of Yb:YAG slab laser. According to the characteristics of the output laser, the calibration demand analysis and calibration capability analysis were carried out. Based on this, the simulation and optimization design of the 1D DM and 2D DM were improved. The beam quality of the laser was improved from 9.03 to 1.98 in the correction experiment. The beam quality correction ability of the adaptive optical system with double DM combination mode for Yb:YAG slab laser was verified.
2022, 51(8): 20210779.
doi: 10.3788/IRLA20210779
Femtosecond lasers with high repetition rates play important roles in advanced manufacturing, such as high-speed laser ranging and three-dimensional imaging. Among them, high-order harmonic mode-locking based on femtosecond fiber lasers is one of the important methods to obtain high repetition rates above GHz. Based on a nonlinear polarization rotation (NPR) mode-locked Ytterbium (Yb) fiber laser with dispersion compensation from intra-cavity grating, a stable 143 MHz fundamental frequency mode-locked pulse sequence was obtained when the pump light was 180 mW. When the pump power was increased to 1 W, the highest 20th harmonic (2.86 GHz) mode-locked pulse train was obtained. The Allen deviation and phase noise of the output pulse repetition rates of the Yb fiber laser were studied systematically when it was running at high harmonic mode-locking and fundamental mode-locking respectively. The repetition frequency locking accuracy can be maintained at a stability of 10−13 Hz@1 s in the 7th harmonic mode locking state. This study provides an experimental basis for high harmonic mode-locked femtosecond laser pulse sequence to be used for precise measurement.
2022, 51(8): 20210679.
doi: 10.3788/IRLA20210679
Beam combining is a key technology to achieve high-power output of quantum cascade lasers. Based on the polarization characteristics of lasers, the experimental principles and methods of polarization beam combining were studied. The polarization beam combining device was composed of a wire grid polarizer and a mid-wave half-wave plate to perform polarization combining of two 4.05 μm quantum cascade lasers. The transmission rate of the mid-wave half-wave plate to 4.05 μm laser and the relationship between the transmission rate and reflectance of the wire grid polarizer to 4.05 μm laser and the angle of incidence were tested. When the angle of the wire grid polarizer was 30°, the transmittance was 81%, the reflectivity was 91%, and its beam combining efficiency reached about 86%. The beam quality after combining was tested and analyzed by a beam quality analyzer. The results show that the beam after beam combination has better beam quality under the condition of ensuring beam combination efficiency.
2022, 51(8): 20210774.
doi: 10.3788/IRLA20210774
To finely describe the internal spatial structure characteristics of femtosecond laser filaments, the forward propagation process of ultrasound induced by optical filaments is first simulated in fine detail, and then different photoacoustic tomography image reconstruction algorithms, such as the universal back projection algorithm (UBP), delay and sum (DAS) and superiorized photo-acoustic nonnegative reconstruction algorithm (SPANNER), are used to perform reverse reconstruction image of filaments. The results theoretically verify the feasibility of using a multiple linear array detection to reconstruct the axial r-z section of a single filament and multiple filaments. The results show that the maximum frequency of the ultrasonic signal induced by a single filament and multiple filaments at a detection distance of 3 mm is approximately 5 MHz. Photoacoustic tomography can accurately retrieve the single filament position and r-z section profile, but the reconstruction effects of different image reconstruction algorithms are quite different. The UBP algorithm has obvious artifacts in the reconstruction of filaments; the DAS algorithm overestimates the diameter of light filaments due to the "finite aperture effect"; the SPANNER has the best effect on multiwire image reconstruction because it uses optimal theory to improve the nonlinear conjugate gradient operator and realize nonnegative and anisotropic total variational regularization, which can effectively avoid noise interference. The results of this study have certain reference value for revealing the structural characteristics of laser filaments and promoting the laser filamentation based atmospheric application research.
2022, 51(8): 20210786.
doi: 10.3788/IRLA20210786
To acquire multidimensional characteristic information of ancient architectures, such as spatial structure, historical evolution and health status, this paper developed a hyperspectral LiDAR (HSL) system that implemented continuous spectrum wavelength selection from 550 nm to 1050 nm by an acousto-optic tunable filter (AOTF). 5 GHz/s high-speed acquisition card recorded the full waveform, including the transmitted and the echo waveforms. A two-mode step scanning strategy, including static single-point testing and zigzag scanning mode, was designed to ensure the accurate acquisition of three-dimensional spatial information. The reflectivity stability, signal-to-noise ratio (SNR), and scanning accuracy tests were conducted in an experimental environment, which indicated that our HSL system was stable and reliable. The 3D reconstruction distribution of ancient building components was presented with a single wavelength quantized voltage value, and the component material classification was conducted by a random forest (RF) classifier with hyperspectral reflectance. The results show that the system can obtain reliable 3D spatial and supercontinuous spectral information, providing multidimensional feature data for ancient architecture modelling.
2022, 51(8): 20210651.
doi: 10.3788/IRLA20210651
Visual/LiDAR odometry can estimate the process of an autonomous driving vehicle moving in multiple degrees of freedom based on sensor data and is an important part of the positioning and mapping system. In this paper, we propose a real-time tightly coupled odometry system that integrates vision, LiDAR, and IMU for autonomous driving vehicles and supports multiple running modes and initialization methods. The front end of the system applies a modified CUDA-based ICP for point cloud registration and traditional optical flow for vision feature tracking and uses the LiDAR points as the depth of visual features. The back end of the system applies a factor graph based on a sliding window to optimize the poses, in which state nodes are related to the poses from vision and LiDAR front end subsystems, and edges are related to preintegration of IMU. The experiments show that the system has an average relative translation accuracy of 0.2%-0.5% in urban scenes. The system with both LiDAR and visual front end subsystem is superior to a system that only contains one of them. The method proposed in this paper is of positive significance for improving the accuracy of the autonomous driving positioning and mapping systems.
2022, 51(8): 20210732.
doi: 10.3788/IRLA20210732
The number of echo photons in deep space laser ranging is rare because of the long distance, so it is of great significance to study the method of increasing the number of echo photons to improve the success probability of ranging. In this paper, a tip/tilt mirror is added to the transmitting optical path of the laser ranging system of the 1.2 m Telescope of Yunnan Observatory, and the pointing position with a large number of echo photons is searched by quickly and accurately controlling the propagation direction of the laser beam. First, the tip/tilt mirror scanning system is designed, and then the system is simulated and analyzed to simulate the variation of the deflection angle and energy distribution of the outgoing beam with the deflection angle of the tip/tilt mirror and the search effect by using the tip/tilt mirror. Finally, the actual observation experiment is carried out on the ranging satellite. The actual measurement shows that the minimum resolution of the two-dimensional tip/tilt mirror used by the system is 0.2″. After beam expansion by the laser emission system, the minimum search step of 0.005″ can be realized, and the control frequency can reach more than 100 Hz. The actual observation results show that the method of using a tip/tilt mirror to improve the echo rate is effective, and the higher the target orbit height is, the more obvious the effect. Therefore, it can be applied to a deep space target laser ranging system.
2022, 51(8): 20210799.
doi: 10.3788/IRLA20210799
The two materials, steel and aluminum, are difficult to weld because of the large differences in physical properties and chemical composition, resulting in steel and aluminum welding becoming difficult. To obtain high-quality steel/aluminum joints, seven laser scanning paths were used to perform lap joint spot welding experiments on two metals, DP780 duplex steel and 5083 aluminum alloy. The effects of the laser scanning path on the macroscopic morphology, metallographic organization, microhardness and shear strength of the steel/aluminum joint were studied. The results show that the change in scanning path has a greater impact on the joint compared to conventional welding. Swing welding joints have better joint quality and better weld surface formation. Steel/aluminum joints are mainly composed of martensite and ferrite. The use of laser swing spot welding joints with obvious grain boundaries, a small amount of lamellar pearlite at the junction of martensite and ferrite, and there is no significant difference in the grain types of the weld, so the mechanical properties of all parts of the weld are the same, reducing the stress concentration phenomenon after the force is applied. The mechanical properties of the swing spot welded steel/aluminum joint are enhanced, the maximum microhardness of the steel side joint can reach 450 HV, 1.06 times that of conventional, and the shear strength is 83 N/mm, 2.12 times that of conventional welding.
2022, 51(8): 20210693.
doi: 10.3788/IRLA20210693
A three-dimensional reconstruction system for underwater lasers is proposed, which is composed of a camera, green linear laser and turntable. The three-dimensional reconstruction of the target area is realized by analyzing and processing the image scanned by the system. In the aspect of point cloud processing, this paper combines the alpha shape boundary extraction algorithm and Delaunay triangulation to realize the filtering and reconstruction of point clouds. Aiming at the problem of viewing angle error caused by light refraction on different media surfaces in the experiment, a refraction correction algorithm is proposed, and the error experiment is carried out with a standard ball of known size. The results show that at a working distance of 500-1200 mm, the system can restore the three-dimensional morphology of underwater target objects and regions, and the reconstruction error is less than 0.6 mm, which meets the design requirements and provides a new reference for underwater three-dimensional reconstruction technology.
2022, 51(8): 20210720.
doi: 10.3788/IRLA20210720
In terrorist attacks, explosive attacks are the most common terrorist attacks. Explosive attacks have seriously threatened the daily life of the public, so the detection of explosives has attracted increasing attention. Through laser-induced breakdown of RDX and TNT at atmospheric pressure and low pressure, it was found that two characteristic spectral lines of atomic lines and molecular lines, CN (421.3 nm) and C2 （516.2 nm）, were the most valuable among all the spectral lines of organic explosives. The results show that the spectral line intensity is related to atomics proportion and molecular structure of the sample, and molecular lines are more valuable than atomic lines. Compared with the atmospheric pressure, the relative standard deviation of RDX decreases from 5.1% to 1.8%, and the relative standard deviation of TNT decreases from 15.7% to 2.7% under low pressure. A low pressure environment can effectively improve the analytical precision of LIBS to detect organic and increase the accuracy of spectral analysis, which helps LIBS to improve the detection and analysis precision of organic explosives.
2022, 51(8): 20220453.
doi: 10.3788/IRLA20220453
2022, 51(8): 20220493.
doi: 10.3788/IRLA20220493
