A remote measurement method for the mass concentration of fugitive-dust-emission particulate based on backward light scattering is proposed to overcome the problem that there is no effective measurement method for the mass concentration of particulates from open and fugitive-dust-emission sources such as construction sites. The measurement result of the proposed method is the average mass concentration of particulates of the cylindrical beam segment. The established theoretical model takes into account the backscattered light energy, mass concentration of particulates, and measuring distance. A portable measuring device is developed using a semiconductor laser as a light source and complementary metal oxide semiconductor image sensor as a detector, as well as an image processing program. The linear relationship between the mass concentration of particulates and output value of the system is verified by calibration experiments, which renders the calibration curve. Effects of large particle size and measuring distance changing within 100 m on the measurement results are compared and analyzed. At the same time, the fugitive emission source is selected for actual measurement. The results show that the experimental measurement device based on the new method can be applied to the remote estimation of the mass concentration of particulates in the fugitive emission air mass in the open field.

When we use wavelet transform to solve the denoising problem in pulsar noise signal, the choice of threshold and construction of threshold function determine the denoising effect. Herein, we analyze the distribution characteristics of noise wavelet decomposition coefficients by combining the wavelet transform properties. We construct a nonlinear two-parameter threshold function by combining the structural characteristics of the soft threshold and hard threshold functions. Furthermore, we use particle swarm algorithm to optimize the parameter size to change the position and bending degree of the threshold function adaptively, thereby obtaining a good threshold function denoising model. Based on the analysis on the variation in the noise wavelet decomposition coefficient with decomposition layer, the unified threshold selection strategy is improved. Then, a gradient attenuation factor is introduced to construct a threshold selection method based on the noise mean square error of each decomposition layer. The experimental results show that, compared to the traditional wavelet domain denoising method, the proposed method significantly improves the signal-to-noise ratio, peak signal-to-noise ratio, and peak-to-bit error of X-ray pulsar noise signals, supporting the new ideas of X-ray pulsar signal denoising.

A design method of compound free space optical/millimeter wave (FSO/MMW) antenna for point-to-point communication is proposed. A hybrid transmission line theory-ray tracing method (TLT-RTM) is proposed for rapid and efficient simulation of the FSO/MMW antenna, which contains an absorption dielectric material with electrically large size. Meanwhile, a compound antenna is optimized using TLT-RTM. The working wavelength of the compound antenna in optical spectrum is 1550 nm and the microwave frequency is 28 GHz. The aperture of the compound antenna is 200 mm and the effective focal length is 816.86 mm. The spatial frequency is 30 lp/mm when the contrast transfer function is reduced to 0.7 for optical wave. The gain of the compound antenna is 32.97 dBi and the half power bandwidth is 3.29° for millimeter wave. The compound antenna can be applied to transmitting optical and millimeter wave signals at the common aperture in point-to-point terrestrial links of 5G communication networks.

Traditional optical spatial modulation has low transmission rate and laser utilization and requires the number of lasers to be an integer power of two. To address these problems, we propose a generalized optical spatial modulation (GOSM) scheme suitable for wireless optical communication, which is combined with pulse position modulation and can simultaneously activate multiple lasers. Aiming at the high complexity of the maximum likehood decoding (ML) algorithm, we propose a signal detection algorithm based on ordered-block minimum mean square error (OB-MMSE). A balance factor is utilized to comprehensively consider the error performance and computational complexity. The proposed OB-MMSE algorithm is improved,and the weight is modified according to the characteristics of the GOSM signal. Moreover, an expression for the threshold selection in the lognormal turbulence channel is derived. Finally, the Monte Carlo simulation is utilized to verify the performance of the proposed solution, and the bit error rate and computational complexity of the proposed OB-MMSE algorithm are compared with those of classical ML and MMSE algorithms. Simulation results demonstrate that the proposed OB-MMSE algorithm can effectively reduce the computational complexity at the expense of a slight bit error rate reduction compared to ML algorithm. Furthermore, the proposed OB-MMSE algorithm can reduce the bit error rate compared to the MMSE algorithm. The proposed solution is applicable to systems with less receivers than transmitters at the cost of a slight increase in the computational complexity.

To address the shortcomings of the current cutter wear detection methods which have difficulty to detect in real time, a new method based on the fiber Bragg grating (FBG) array for cutter wear detection is proposed. A multi-channel FBG wear detection system is built experimentally. By analyzing the positioning and wavelength division multiplexing capabilities of FBG, an embedded optical fiber sensor which can be used in cutter wear detection field is obtained. Four FBG arrays with 3 mm grating length are arranged separately with equal interval and demodulated simultaneously. The online real-time monitoring of wear length is realized, and the wear detection error is less than 0.23 mm.

A fiber grating ultrasonic sensor based on coupling cone structure is proposed. Numerical simulations and optimization of the ultrasonic coupling cone structure are performed, and the influence of fiber-grating length on the ultrasonic detection performance is analyzed. In conjunction with edge-filter-demodulation technology, the proposed ultrasonic sensor is applied to the identification of defects in a 6061 aluminum alloy plate. The experimental results show that the proposed ultrasonic sensor can effectively detect the Lamb wave transmitted in the aluminum alloy plate. By analyzing the variations in amplitude of the temporal waveform and S0 mode of the Lamb wave, hole-type defects and defect size in the aluminum alloy plate can be readily determined. The proposed ultrasonic sensor has a number of advantages, including high sensitivity, flexible and adjustable positioning, and reusability, all of which are key factors for its potential application in the field of structural damage identification.

We propose a radio-over-fiber (ROF) link delay measurement scheme based on time, frequency,and ROF signal simultaneous transmission to meet the large-range and high-precision delay measurement requirements of ROF links. One pulse-per-second (1PPS) is processed with subcarrier modulation, so that the ROF signal and the delay measurement signal are transmitted at the same wavelength, avoiding the interference of the 1PPS signal to ROF signal and achieving high-precision delay measurement and ROF transmission simultaneously. We build up an experimental system to measure the absolute delay of the ROF signal during the 25 km fiber link at severely changed temperature, which verifies the compatible characteristic of the ROF system and the time-delay measurement system. The experimental results show that the proposed scheme can measure high-precision and large-range link delay without ROF signal degradation.

Considering the influences of self-phase modulation and cross-phase modulation on the propagation characteristics of guided light in few-mode fibers, we present the analytic solution of the corresponding nonlinear coupled mode equation, which is used to calculate the nonlinear coefficients of few-mode fibers and analyze the nonlinear compensation in few-mode optical fiber communication systems. Taking four-phase phase shift keying (QPSK) signal systems which supports two linearly polarized (LP) modes as an example, the influences of mode loss and nonlinear effects on the mode division multiplexing system is analyzed by simulation, and the compensation effectiveness for inter-mode phase modulation and the adaptability of the compensation algorithm are also discussed in detail. Research results show that, for correct demodulation of QPSK signals after compensation, the maximum allowable misalignment of mode loss increases with the increasing reference value, and the nonlinear compensation effect in the few-mode optical fiber communication system is limited by the inter-mode nonlinear coefficient. The maximum allowable deviation of the inter-mode nonlinear coefficient is 0.146 W -1·km -1.

This study presents a microfiber-based Mach-Zehnder interferometric optical structure. The fiber-optic humidity sensing, which employs the wavelength corresponding to the interference peak as the sensing parameter, is realized using a thermal reduction method. The thermal reduction method changes graphene oxide (GO) film, which precovers the fiber, into a reduced graphene oxide (RGO) film. The sensor can achieve a maximum average sensitivity of 0.2768 nm/%RH in relative humidity range of 45%-95%. The response and recovery time of the sensor in humidity sensing are 6 s and 30 s, respectively. The humidity response and temperature response of the sensor exhibit different characteristics, and the sensor has good time stability and recoverability in humidity sensing. This study provides a novel interference-type graphene-based fiber-optic sensor fabrication method using the microfiber-based interference structure and process engineering that changes GO into RGO.

Aiming at scenes with large laser frequency offset,we study an integer frequency offset estimation and compensation method for a coherent optical offset quadrature amplitude modulation based filter bank multicarrier (CO-FBMC/OQAM) system. We expand previous researches and investigate the fractional frequency offset (FFO) by designing a hybrid training sequence structure. Based on this training sequence, we can precisely estimate the FFO and effectively implement the integer frequency offset (IFO) estimation. Further, numerical simulations are used to examine the effectiveness of the proposed method with respect to the CO-FBMC/OQAM system. The results denote that the maximum IFO can be accurately estimated to be 12 times that of the subcarrier frequency interval and that the bit error rate after frequency offset compensation is lower than the forward error correction limit. The proposed method can provide a useful reference for the research and development of the CO-FBMC/OQAM system.

To improve the effect and classification accuracy of semantic segmentation of remote sensing images, a two-channel image feature extraction network combining with ResNet18 pre-training model is designed. Images with multiple features are combined, and the combined feature map has stronger ability to express features. At the same time, batch normalization layer and maximum pooling with location index are adopted to optimize the network structure and improve the classification accuracy of surface object. The accuracy and Kappa coefficient of this method are compared with those of other neural network methods by experiments. The results show that the proposed network structure achieves an overall accuracy of 90.68% when the number of data samples is small, and the Kappa coefficient reaches 0.8595. Compared with other methods, the proposed algorithm achieves better semantic segmentation effect, and greatly reduces the overall training time.

Using the YOLOv3 architecture, we propose a recognition method for fast low-altitude unmanned aerial vehicle (UAV) detection based on the dual channel (Dual-YOLOv3). In this method, the infrared and visible UAV images are simultaneously input into the deep residual network for feature extraction, and the extracted feature maps are fused to enhance the expression ability of the features. Then, the multi-scale prediction network is used to determine the classification and the position regression of the UAV targets. Finally, we obtain the detection and recognition results. Comparison experiments are conducted on the real collected dataset of dual-band UAVs. The results show that the mAP (mean of average precision) of Dual-YOLOv3-D with average fusion is improved by 6.1% as compared with that of YOLOv3 with the single data source; the detection speed is approximately 27 s -1.

A method of unifying the normal orientation of point clouds in multi-layer Riemannian graphsis presented to address the challenges for existing normal propagation methods of point clouds sampled from curved surfaces in quick processing of massive data. In this method, the point clouds are recursively divided into subsets to obtain the core point sets. The surface variability of the core point sets controls the recurrence number, and a multi-resolution model of tree structure is constructed for the point clouds. The nodes of the point-cloud multi-resolution model are traversed from top to bottom, and the multi-layer Riemannian graph of the point clouds is thus constructed from the subset of non-leaf nodes. Using the sequential traversal method, the normal unification of the sample points in the top-layer Riemannian graph is transmitted downwards. For each Riemannian graph unit, the minimum spanning tree algorithm is used to obtain the normal unification of the sample points. The experimental results demonstrate that this method can effectively improve the computational efficiency and memory utilization in processing massive point clouds and ensure the accuracy of the normal propagation of sample points in complex feature areas.

This paper describes a method for eliminating atmospheric low frequency disturbances by designing a camera imaging system. Precision optical measurement engineering is usually performed outdoors, so it is difficult to avoid systematic errors caused by atmospheric disturbances. The atmospheric disturbance can be divided into two parts, i.e., high frequency disturbance and low frequency disturbance. The high frequency interference can be eliminated by image processing methods such as filtering. The optical measurement error caused by the atmospheric low frequency disturbance can be eliminated by establishing the constraint condition of the opposite view camera imaging system. We conduct an experiment with high-speed cameras to eliminate atmospheric disturbances, and use the planar mirror reflection imaging to complete the calibration of the camera system. Comparing the results of the experimental group and the control group, the measurement error is reduced from 2.99% to 0.35%. The results show that the camera imaging system has a good correction effect in the low frequency disturbance cancellation in the atmospheric disturbance.

Adding a narrowband filter in a night vision system can considerably reduce the signal-to-noise ratio(SNR) of output images. To solve this problem, a true-color night vision system based on minus filters is designed. Two comparative experiments involving the detection of a standard colorimeter and natural scenery using the true-color night vision system based on narrowband filters under different ambient illumination are performed. The SNR is indirectly evaluated using the correlation coefficients between the edge maps of the reference and output true-color night vision images. In experiment 1, the results show similar correlation coefficients for the two systems when the ambient illumination is 0.51 lx. For illumination levels of 0.12, 0.04, and 0.01 lx, the correlation coefficients of the proposed system are 14.9%, 26.8%, and 128.0% higher, respectively, than those of the system with the narrowband filters. In addition, the correlation coefficient of the proposed system is also higher than that of the traditional system in experiment 2. Therefore, compared with the traditional true-color night vision system, the true-color night vision system based on minus filters can work under conditions of lower illumination and produce true-color night vision images with higher SNR.

This work proposes a strategy of designing the optical heteromorphic window which comprises a pair of symmetrical conformal internal surface and correction external surface that are determined using ray tracing. An experimental system is set up to analyze the characteristics and correction of image distortion of the optical heteromorphic window. A correction model of two-order polynomial imaging distortion is proposed and then applied to distorted image correction. The results show that after passing through the optical heteromorphic window, the parallel light has obvious deflection, resulting in uneven brightness distribution and bright and dark spots. At the same time, the image of the calibration board is translated, zoomed, and rotated, and its distortion characteristics at different positions are different. By constructing the correction model, the distorted image is corrected, and the corrected image is highly coincident with the original image. The coordinate difference of each corner point is less than 1 pixel(7.4 μm), demonstrating that the correction model has high precision. The design of the optical heteromorphic window and the development of the correction model contribute to obtaining an accurate internal flow field structure in the inward-turning inlet.

In this study, we propose a chromatic confocal measurement method that employs a color camera. The chromatic confocal measurement technology is extensively used in microscopic detection, biomedical applications, and other fields because of its sub-micron or even nanometer axial resolution and the advantage of obtaining height information without axial scanning. Furthermore, a color conversion algorithm is proposed and optimized by simulations to establish the corresponding relationship between the axial height and color. Experimental results indicate that the proposed color conversion algorithm can establish a good linearity between the axial height and color, and the linear judgment coefficient is R2=0.9979. We evaluate a step with a height of 100 μm and observe that the measurement accuracy can reach the sub-micron level. We also measure the coin surface and observe that our color conversion algorithm can reconstruct the three-dimensional surface topography of the coin after correcting a series of errors.

Strain results obtained using common two-dimensional digital image correlation (2D-DIC) method usually have rather poor measurement accuracy owing to rigid out-of-plane displacement. This study proposes a modified 2D-DIC method based on 45° dual-reflector imaging technique to improve the strain measurement accuracy. The speckle patterns of the front and rear surfaces can be recorded in a single image using dual-reflector imaging. The effect of rigid out-of-plane displacement is automatically eliminated by taking the average strain of corresponding points from the left and right images. Two groups of tensile tests are conducted to verify the feasibility of the proposed 2D-DIC method. Experimental results show that: for uniform deformation, the biaxial results obtained using the proposed 2D-DIC method are in good agreement with those obtained using strain gauges; from the viewpoint of the nonuniform deformation, the strain fields of the proposed 2D-DIC method are in agreement with those of the finite element method. Therefore, the proposed 2D-DIC method has excellent strain measurement accuracy, and it is a convenient, effective, and highly accurate strain measurement method.

The core of the nonlinear laser ultrasonic crack detection technology based on laser excitation/detection lies in the fact that it makes the crack to be periodically opened and closed by using mechanical/laser irradiation to apply a load on the sample/crack. However, many factors such as the complex crack morphology and crack wall roughness affect the results. Aiming at this problem, a black glass plane and a convex surface of a plano-convex lens are used to simulate crack walls, by changing the relative position between the black glass and the lens to simulate the real crack closure process. The pulse point laser source is used as the ultrasonic excitation source to excite the ultrasonic wave on the black glass surface, the ultrasonic wave is detected by the laser vibrometer to quantitatively promote the closure process of the black glass simulated crack, and the peak-to-peak value of each modal signal under different push distances is recorded. The experimental results show that the black glass is pushed in a state where the black glass and the convex lens are not in contact at all. With the increase of the black glass push distance, the pressing force between the black glass and the plano-convex lens increases, and the peak-to-peak values of the direct longitudinal wave signal and transverse wave signal have a tendency to become larger. When the pressing force between the black glass and the plano-convex lens is small, the peak-to-peak value of the mode-transition signal of the longitudinal wave to the transverse wave first increases and then decreases, and the peak-to-peak value of the reflected longitudinal wave signal decreases.

According to the characteristics of interference fringe region and compared with many conventional edge detection methods, a judgment function is proposed for the automatic extraction of speckle interference fringe regions based on second-order gradient entropy functions. By analyzing different speckle interference fringe images, an optimum entropy size interval of a test sub-region and adaptive threshold intervals of different interference fringe patterns are determined. The automatic extraction of the stripe region is finally completed through connected region segmentation. The method is validated experimentally. Experimental results show that more accurate image entropy is obtained when the size of sub-region entropy is above 15 pixel. The fringe region and speckle background region can be segmented accurately when the adaptive threshold is within a range of 0 to Qmax-1.25, where Qmax is the maximum gradient entropy in the image, thereby achieving automatic extraction of the speckle interference fringe region.

To accurately and rapidly extract the center of the structured-light stripe, we propose a center extraction method based on the back-propagation neural network (BPNN). The basic principle of stripe-center extraction using the BPNN, the method that calculates the ideal center points for network training, and the network-weight tuning algorithm are presented successively. Factors affecting the center extraction accuracy, such as the number of hidden layer neurons m, number of hidden layers h, and training samples are investigated. The center-extraction results show that the network can achieve a better stripe center when m=3 and h=1, and the training sample is a random stripe with noise. From the comparison analysis, it can be concluded that the proposed method can achieve higher center-extraction accuracy than both the Steger method and the gray gravity method. The average center-extraction time for a stripe image with the size of 1280 pixel× 960 pixel is 0.04 s, which is only 0.27% of the time required by the Steger method. This further demonstrates that the proposed method has the advantages of high precision and high efficiency. Therefore, it is adequate for sub-pixel center extraction of complex light stripes.

Industrial computed tomography (CT) is an effective tool for measuring the dimensional characteristics of lattice structures in additive manufacturing parts. However, currently there is no uniform method to evaluate the dimensional measurement errors of industrial CT. Therefore, in this paper, we first evaluate the dimensional measurement errors of industrial CT using a coordinate measuring machine and a hole plate standard; then, we propose a method for conducting the periodic dimensional measurements of the lattice structure based on contour features. Finally, the effectiveness of the method is verified via an example. The result shows that the maximum permissible error of the industrial CT can reach ±(50+L/400) μm, which meets the current testing requirements. The contour feature extraction method can be applied to measuring the periodic dimensional features of lattice structures.

Polarization-sensitive optical coherence tomography (PS-OCT) is a functional imaging technique for biological birefringence tissues. The information contained in the biological tissue can be extracted by analyzing the phase delay. Herein, the influence of polarization state of single incident light on the phase delay accuracy caused by tissue birefringence is analyzed. Initially, the theoretical model is proposed. Subsequently, simulations using MATLAB are performed and finally the theoretical model is verified by experimental measurements. Results obtained by MATLAB along with experimental results show that, when a sample with a fixed amount of phase retardation and a fixed direction of optical axis, and when the orientation is 0° and 90° for the incident linearly polarized light or 45° for the incident elliptically polarized light, the phase retardation measurement error has the smallest value.

In this study, a slot-structured feedback-coupled waveguide microring resonator is proposed to optimize the performance of a microring resonator. Further, the performance parameters of the resonator are considerably improved by the introduction of an additional light field based on the add/drop-type microring and the usage of a slot waveguide. The effect of the improved structure on the phase, free spectral range, and output performance is analyzed using the transfer matrix method, and simulation analysis is performed using the three-dimensional finite difference method software named FDTD. The results denote that the free spectral range of the improved structure increases from 14.5 to 29 nm and that the absolute value of the extinction ratio increases from 21 to 31 dB, which is helpful to improve the measuring range and sensitivity of the corresponding sensor.

A thin-disc multipass laser amplifier enables a seed laser to frequently pass through the gain medium to extract energy. Such an amplifier can output a high average power, high pulse energy, and high beam-quality laser, which plays an important role in a high power short-pulse laser system. In this paper, a Yb∶YAG thin-disc multi-pass laser amplifier that can amplify a seed laser over the course of 20 passes is designed and constructed. An amplification of a high-repetition frequency short-pulse laser is performed, and it is found that the thin-disc multi-pass laser amplifier can effectively guarantee the beam quality of the output laser. In addition, spectral mismatch is observed to have an influence on the single gain of a short-pulse laser.

A novel mid-infrared fiber laser is reported based on an anti-resonant hollow-core fiber filled with carbon dioxide gas. A tunable 2-μm semiconductor laser amplified using a thulium-doped fiber is used to pump a low-loss anti-resonant hollow-core fiber with a length of 5 m, which is filled with carbon dioxide gas at low pressure. Particle beam inversion is responsible for obtaining the single-pass fiber laser output at 4.3 μm, which is the longest wavelength that has yet been reported for continuous wave fiber lasers at normal temperature, except for supercontinuum lasers. At a pressure of 500 Pa, the maximum laser output power of the R(30) absorption line is 82 mW and the slope efficiency is approximately 6.8% (relatively coupled pump power entering the hollow-core fiber), whereas the maximum laser output power of the R(28) absorption line is 63 mW and the slope efficiency is approximately 5%. This study provides a potentially effective pathway for obtaining compact and efficient 4-μm fiber gas lasers.

With the aim of overcoming the limitations of traditional circuit-board integration methods, a copper-clad board-line forming technology based on femtosecond laser is proposed. Single-factor and orthogonal experiments are performed on a copper-clad laminate using femtosecond laser. Among influencing factors such as laser power, frequency, scanning speed, number of scans, and defocusing amount, the number of scans has the largest influence on the etching depth and surface roughness, while the laser frequency has the smallest influence on both. By etching the copper-clad laminate with optimized laser parameters, the surface copper layer can be removed completely to obtain a high-quality etched region without damaging the substrate underneath.

By employing double-walled carbon nanotubes as a saturable absorber to start mode locking, we experimentally demonstrate dual-wavelength operation of a passively Q-switched, mode-locked (QML) Tm∶LuAG bulk laser at the wavelengths of 2017 nm and 2027 nm. Herein, the laser is pumped by a wavelength-tunable Ti∶sapphire solid-state laser, and when the absorbed pump power is greater than 2292 mW, the laser enters a stable QML state of operation. By using an output coupler with transmittance of 3%, when the absorbed pump power reaches 6.7 W, the QML output power is 1.28 W, corresponding to a slope efficiency of 22.39%. The repetition rate is 102 MHz, which corresponds to a single-pulse energy of 12.55 nJ.

Although single-crystal black phosphorus (BP) can be prepared by the mineralization method, there have been few reports on the growth process of BP under non-vapor transport conditions. In this paper, a simple synthetic approach based on Sn-I-assisted mineralization is developed to produce high-quality orthorhombic single-crystal BP in a quartz tube. Through different temperature variations, we study the growth process of single-crystal BP under non-vapor transport conditions. The results show that by using the appropriate conditions, the mineralization method can be used to produce high-quality orthorhombic single-crystal BP. During the cooling process from 620 ℃ to 500 ℃, Hittorf’s phosphorus is formed. It is shown that 500 ℃ is a critical temperature for BP growth, which properly prolongs the holding time, promoting the growth of single-crystal BP. Finally, the growth process of BP under non-vapor transport conditions is clarified.

Aiming at the characteristics of the intensity inhomogeneous and diversiform parathyroid lesions in the ultrasound images of the parathyroid gland, we propose a hybrid level set model for parathyroid gland segmentation based on local entropy of images. The proposed model uses both global and local image information. To address the problem of the inhomogeneous intensity distribution in ultrasound images,local entropy of images is used to determine the weight of the global term to improve the model’s adaptivity. In addition, two scales are adopted to prevent over-segmentation and calculation inefficiency on the large and small scales, respectively. Experimental results show that the proposed model can adapt to different ultrasound images of parathyroid gland, which makes the evolution curve converge to the target contour automatically. In addition, this model has high segmentation accuracy and computational efficiency.

Chlorella pyrenoidosa is used as the subject and the photosynthetic activity parameters of this type of algaes are used as a toxicity evaluation index. The responses of different photosynthetic activity parameters to the acute toxicity of phenol are studied over 72 h and 70 min. The results show that phenol has significant inhibitory effects on the photosynthetic activity parameters Fv/Fm, rP, α, Ek, and JVP II. Further, under the acute toxicity of phenol, the toxic responses of the aforementioned photosynthetic activity parameters are stable over a short time, where 5 min can be used as a response time for the toxicity analysis of phenol. Finally, the photosynthetic parameters Fv/Fm, rP, Ek, and JVP II show a good dose-response relationship to phenol toxicity and each parameter responds differently to the toxicity of phenol. Across a concentration range of 0.2-1.2 g/L, the inhibition rates of Fv/Fm, rP, Ek, and JVP II are -3%-19%, 9%-67%, 15%-74%, and 17%-37%, respectively.

To overcome the disadvantages of the existing microscopy autofocus technology, this study proposes a method for detecting the defocusing distance and orientation of a sample according to the distance and direction from the center of the field of view (FOV) of the focusing band in a tilt plane image, which is acquired using a tilt camera. The feasibility of this method is verified by constructing an experimental microscope autofocus system. Results show that this system can quickly obtain a defocusing distance and orientation by detecting the amount of horizontal shift from the center of FOV of the focusing band in a single-frame tilt plane image, which can be determined according to a calibration curve between the defocusing distance and focusing band's horizontal-shift value. Autofocus can then be achieved in applications using motor drive. The optical structure presented herein is simple and cost-effective. It can be directly used in a conventional, trinocular microscope-imaging system and can thus be applied to the autofocus process required in online, in situ, large FOV, and high-resolution detection in various fields.

In comparison with traditional immersion lithography, extreme ultraviolet (EUV) lithography at a wavelength of 13.5 nm has become a promising technology. While imaging resolution has been greatly improved, aberration tolerances must be strengthened as they scale with wavelength, and a greater understanding of the effect of aberration on EUV lithography imaging is urgently needed. Focusing on the wave front characteristics of four kinds of typical aberrations, this study establishes corresponding aberration models according to their characteristics to explore the influence of aberration on lithographic imaging critical dimension and best focus bias. The maximum allowable range of single aberrations under required focus depths is provided. The total values of the four kinds of aberrations are controlled within 0.04λ, and the analysis is repeated to determine the requirements the aberrations needed in actual demand from the simulation. Based on these results, total aberrations should be controlled within 0.025λ, about 0.34 nm.

A lithographic tool-matching method using a differential evolution algorithm and a micro mirror array (MMA) source model is proposed herein. In this method, the MMA source model is added, and the light spots of micro mirrors are optimized by the differential evolution algorithm to achieve lithographic tool-matching. Compared with other matching methods for the freeform illumination system, the proposed method can directly optimize MMA parameters and reduce matching errors in the process of MMA generating light source. A one-dimensional line/space mask is adopted for matching under quasar and freeform illumination. The simulation results show that the root-mean-square of critical dimension error decreases by more than 80% after matching. The proposed method outperforms the matching methods based on the genetic algorithm and particle swarm optimization algorithm. Further, the convergence is accelerated. Moreover, the proposed method can effectively control the pupil fill ratio and keep it constant before and after matching.

A feedback optimization design method based on surface energy mapping is proposed herein. By pre-calculating the energy distribution on the target surface, the target surface mesh unit is redistributed to build a new free-form surface lens profile. A series of lenses is designed using this method, and the simulation results show that when the ratio of the target surface radius to height (DHR) is equal to 2 and ratio of the lens height to the LED width changes from 1∶1 to 1.5∶1, the nonuniformity is reduced by 8.97%-11.95%. Moreover, when the ratio of lens height to LED width is 1.5∶1 and DHR changes from 1.8 to 2.2, the nonuniformity is reduced by 7.60%-16.49%. Thus, the proposed method can effectively improve the illumination under an extended light source. The design process does not depend on the simulation software utilized, and it is simple and easy. The number of iterations is small.

With an aim to overcome the problem of excessive data transmission bandwidth in near-eye display systems, this study proposes a multiscale pyramid model to realize multi-resolution display in the human visual region. We apply the characteristics of the spatial change rate of the human visual region to the data transmission process. Based on a multi-scale pyramid model, a microdisplay controller for the near-eye display system is designed, realizing the encoding and decoding processes of the video image. The feasibility of this controller is verified on a 1600×1600×3 full-color high-definition OLED-on-silicon microdisplay. Experimental results show that the multi-resolution image fusion algorithm based on a multi-scale pyramid meets the visual perception requirements of human eyes and solves the boundary line effect appearing in the subsampling process, effectively reducing the data transmission bandwidth. The proposed algorithm satisfies the requirements for the real-time rendering performance of the microdisplay in the near-eye display field.

The probability density, the transition frequency and the longitudinal optical (LO) phonon spontaneous emission rate of electronic states in the two-parameter asymmetric Gaussian (AG) potential two-level system are studied by using the Pekar variational method, and their single-parameter parabolic potential approximation are discussed. Numerical results show that the selecting the two-parameter AG potential to describe the restricted effects of electron in quantum dot can more accurately reveal the quantization characteristics of the wave property of electronic states, the statistical regularity of electron motion and the LO phonons spontaneous emission rate, and the results given by the single parametric parabolic approximation are relatively sample and rough. The influence of dispersion and electron-phonon coupling of materials on the probability distribution, quantum transition frequency and the LO spontaneous emission rate in the two-level system cannot be ignored.

In this study, an adaptive remaining useful life (RUL) prediction method is developed based on the expectation maximization (EM) algorithm to solve the problems of insufficient prior information and lack of historical data with respect to the newly developed photoelectric products. Currently, two common problems are associated with majority of the existing RUL prediction methods. First, there is an underlying assumption in degradation modeling that a random parameter estimated at the current time is exactly equal to the posterior estimation of the random parameter at the previous time. Second, the historical degradation data are assumed to be available for parameter estimation based on which the initial model parameters can be determined for multiple photoelectric products of the same type. The RUL prediction accuracy is limited by data availability. Herein, we construct a novel degradation model under the state space model framework and derive the analytical form of the RUL distribution. Subsequently, we propose an adaptive parameter prediction method based on the EM algorithm to overcome the problems of insufficient prior information and lack of historical data. Finally, we conduct an experimental study with respect to the actual degradation data of a GaAs laser and fiber-optic gyroscope to denote that the proposed method improves the RUL prediction accuracy and can be effectively applied to the newly developed photoelectric products.

Herein, a bioprobe based on hollow fibers with electrical and optical delivery channels is proposed to realize low attenuation transmission of mid-infrared light at the wavelength band ranging from 5 μm to 10 μm. Cyclic olefin polymer (COP) is used to isolate the front-end of the probe from water and the necessary sealing technology is designed and optimized. The loss of bioprobe with length of 20 cm and inner diameter/outer diameter (ID/OD) of 0.7 mm/1.5 mm is 1.38 dB at a wavelength of 5.1 μm. By controlling the sealing process, COP sealed windows with different shapes are fabricated to modify the output beam. The focal length and far-field divergence angle for these different configurations are analyzed by measuring the output beam profiles. This approach will provide more ways and means for neuroscience research and biomedical application.

This study proposes a novel method for designing an integrated absorption-transmission flexible ultrathin electromagnetic window, which can absorb the unpolarized incident waves over a wide range of angles and is almost transparent at a given frequency band. The experimental results demonstrate 93% absorption at 4.46 GHz and 98% transmittance at 2.86 GHz, indicating an insertion loss of 0.09 dB. The total sample thickness is 0.288 mm, which makes the structure flexible and easy to conform to the curved target. Furthermore, a method for designing a broadband-integrated absorption-transmission electromagnetic window is proposed. The simulation results denote that the absorption can reach 90% at 7.7-12.2 GHz and that the transmittance is 90% at 4.35 GHz. The proposed broadband structure performs appropriately over a wide range of incident angles.

In this work, the amplification-superposition principle of high-order moiré imaging is analyzed. Based on the first-order geometric-transformation-moiré method, an improved design and analysis method for moiré magnifiers by distinguishing the unit amplification and periodic amplification from the moiré imaging is proposed. Our method is used to simulate high-order moiré imaging in MATLAB. By designing and fabricating various high-order moiré magnifiers, an experimental analysis of high-order moiré imaging is also carried out. The results embody the amplification-composition effect of high-order moiré imaging, thereby validating our method.

This study proposes a method for suppressing phase noise of an optoelectronic oscillator (OEO) based on self-gain modulation effect of a gain-saturated semiconductor optical amplifier (SOA). The SOA is added into the OEO loop and operates in gain-saturated state by adjusting the optical attenuator and drive currents. Partial amplitude noise in modulated optical signal is suppressed due to the SOA's self-gain modulation effect, thereby improving the signal-to-noise ratio of the loop and reducing the phase noise of generated microwave signal. Furthermore, the composition of phase noise in the OEO and the noise-suppression principle of the SOA are analyzed and experimentally verified. The experimental results indicate that when we add a gain-saturated SOA in a 5-km-long single-loop OEO, the near-end phase noises of 10 GHz microwave signal are -84.5 dBc/Hz and -113.9 dBc/Hz under 0.1 kHz and 1 kHz, respectively, i.e., an improvement of 3 dB over that without the SOA. The experimental results are in agreement with the theoretical analysis.

To overcome the limitation of distortion and quality deterioration in whiskbroom scanning images, we propose a geometric correction and image enhancement method that combines the resolution inversion with deep convolutional neural network (DCNN) architecture. During the whiskbroom scanning process, the total whiskbroom scanning angle and unit field of view angle of a space camera are invariable, and each pixel of the detector on the image plane corresponds to the ground scene pointed by the camera boresight. Suitably, these help in restoring compressed pixels accurately. Furthermore, we adopt real-scene remote sensing panchromatic images as the sample to train the DCNN for remote sensing panchromatic images. Then, image blurring during the process of inversion is solved, and the visual effect of the corrected image is enhanced. In our experiment, the distortion corrected imagery restores the geometric characteristics of the ground scene to a large extent. The no-reference image quality evaluation indicators are used to evaluate our proposed network architecture, network trained on generic image set and interpolation method. The experimental result indicates that our proposed network realizes the best performance of image enhancement among the three methods with a great restoration effect of the whiskbroom scanning images.

To address the problem of high resource consumption and difficulty of hardware transplantation involved in utilizing deep convolutional networks for real-time detection of remote sensing building, a semantic segmentation network based on the mixed method of binary and floating-point parameters, i.e., mixed binary U-shape network (MBU-Net), is proposed. To compress the model size, the weights of a float U-shape network (FU-Net) are binarized. The output layer weights that account for a small number of parameters are replaced by floating-point type parameters to resolve the poor detection accuracy and low training speed in a global binary network. Experiments using the QuickBird satellite remote sensing dataset show that the pixel accuracy of MBU-Net is 82.33% and the harmonic average of the recall rate and accuracy rate (F1 score ) is 73.15%. Compared with the FU-Net,the MBU-Net can ensure the detection accuracy. The size of model is greatly compressed, the detection speed is increased by 6.29 times, and the power consumption is reduced to 37.78%, further demonstrating that the MBU-Net is superior to other similar methods (Deeplab and ENet). This finding has important practical engineering value for the real-time detection of remote sensing buildings.

In this study, we present the inversion of land surface emissivity (LSE) in the China land area based on the mid-infrared and thermal infrared channel day/night data received by the FengYun-2G (FY-2G) geostationary meteorological satellite. The atmospheric correction of the FY-2G data is based on MODTRAN, which is a radiation transfer model, using the atmospheric profile data, including data with respect to the temperature, humidity, and ozone, provided by the European Centre for Median-range Weather Forecast (ECMWF). The modified Minnaert’s bidirectional reflection distribution function model is used to calculate the hemispherical reflectivity of the mid-infrared channel in the surface direction. Further, the LSE distribution characteristics can be obtained with respect to the different surface vegetation types in China based on the temperature-independent thermal infrared spectral index. Finally, the LSE inversion results obtained from the images of China’s land area are verified by selecting the surface emissivity products from Moderate Resolution Imaging Spectroradiometer (MODIS). The daytime and nighttime results are observed to be in good agreement with the existing LSE products in MODIS. The absolute LSE inversion errors of the hot infrared channels 1 and 2 during daytime are -0.0057 and -0.0068, respectively, and the root mean square errors (RMSEs) are 0.0095 and 0.0103, respectively. Furthermore, the absolute LSE inversion errors of the hot infrared channels 1 and 2 during nighttime are -0.0010 and -0.0035, respectively, and the RMSEs are 0.0094 and 0.0096, respectively. Simultaneously, the LSE inversion results at different time slots on the same day are analyzed. These results indicate that the LSE at nighttime is lower than that at daytime.

In this paper, the primary sources of AGRI stripe noise are analyzed, and an image-degradation model for this noise is established. A method of stripe-noise removal based on histogram matching and anisotropic total-variation regularization is proposed. The method first implements histogram matching to suppress the nonuniformity response between detector pixels, and then implements the anisotropic total-variation-regularization model to remove the remaining stripe noise. Qualitative and quantitative indices are used to evaluate the processing results of various methods. The evaluation results show that, compared with the existing leading stripe-removal algorithms, the proposed method achieves a superior stripe-noise-removal effect while effectively protecting the details of the original image.

The frame-transfer blurring effect is a key factor that affects the precision of polarization measurement accuracy of highlight-target imaging via a frame-transfer array CCD camera. To improve the precision of spaceborne polarization cameras, it is of great significance to carry out studies on the measurement and correction method of the frame-transfer blurring effect. Considering the GF-5 satellite directional polarization camera (DPC) as an example, this paper investigates the generation mechanism and features of the frame-transfer blurring effect. The frame-transfer blurring effect is divided into the response-difference type, which is unrelated to the light conditions, and the smear type, which depends on the light conditions. To correct the features of the frame-transfer blurring effect in on-orbit imaging by the DPC, two correction models are proposed: the correction model of smear frame-transfer blurring effect based on the matrix and dark line methods, and the correction model of response-difference frame-transfer blurring effect based on the dark current channel. Finally, the optimal correction sequence and the feasibility of correction by the response-difference and smear frame-transfer blurring effects are verified by an integrating sphere. Additionally, the correction accuracy of the frame-transfer blurring effect in the DPC on orbit is verified using sunlight. Experimental results show that the proposed method reduces the influence of the frame-transfer blurring effect in the DPC on the polarization measurement accuracy of highlight targets, such as high reflective cloud and solar flare, from 7.28% to 0.43%, satisfying the calibration requirement that the DPC polarization measurement accuracy is <2%.

The point cloud registration method that uses point features may fail owing to its inability to obtain corresponding points when the point cloud data collected by different stations has the occlusion problem. Therefore, a registration adjustment model is established in this study to iteratively calculate the translation vector and rotation matrix based on the equivalence of the plane normal vectors between the reference and unregistered stations; subsequently, the scale factor is evaluated based on the analytic geometry theory, and the medium errors with respect to the unit direction vector and moment vector deviations of the homonymous lines after registration are considered to be the indexes for evaluating the point cloud registration accuracy. The experimental results denote that the registration adjustment model can realize point cloud registration under the occlusion condition. Furthermore, the results denote that the medium errors of the moment vector deviations of the homonymous lines can be reduced to 0.0247 m after registration. This model not only retains the advantages of the dual quaternion regardless of the initial values of the parameters and the fast convergence rate, but also eliminates the restriction that the two endpoints of the lines need to be corresponding points.

A simplified polar coordinate method based on the non-cosine film thickness formula is proposed for characterizing film thickness distribution. Herein, control of the uniformity of optical film thickness formed by single source electron beam evaporation is studied. Simultaneously, the position of the mask plate is calculated. Compared to the traditional method of placing the mask directly above the evaporation source, the proposed polar coordinate method is used to calculate mask position, which is more conducive to controlling the uniformity of film thickness distribution. Considering an evaporated H4/MgF2 combination as an example, the mask positions and shapes of high and low refractive index materials are calculated, and single layer films are prepared using these two materials. The measured spectral uniformity deviation is better than 0.3%, thus demonstrating the correctness and feasibility of the proposed method.

Based on the redundant property of projection data, the common reconstruction algorithm for the detector-displaced scan weighs the projection data for normalization function, and then reconstructs CT images using a standard filtered back projection method. However, in the condition of a narrow weighting region, the circular weighting artifact is generated in the center area of the image because of the fast attenuation of weighting function. This study proposes a correction scheme for weighting artifacts. First, a virtual detector is used to extend the weighting region. Second, the missing projection data corresponding to the virtual detector can be interpolated by conjugate and forward projection. Finally, the interpolated projection data is reconstructed by the detector-displaced scan reconstruction algorithm. The detector-displaced scan projection data with various weighting region sizes is reconstructed herein. The experimental result shows that the proposed correction method can effectively suppress the weighting artifact.