Large view field and high-resolution imaging is a key problem that needs to be addressed currently in domains of scene monitoring, visual navigation, etc. This work introduces a liquid crystal electric scanning module for light source and image receiver through active illumination. The liquid crystal electric scanning module was developed by liquid crystal polarization grating (LCPG) and ferroelectric liquid crystal (FLC) component. Further, an active imaging system was set up verifying the image field extension. The target image with large view field and high resolution is obtained through timing control and stitching fusion. Resolution of 3840×480 and field-of-view of 52° was obtained. The results illustrate that the active illumination imaging based on liquid crystal electrical scanning can expand the resolution of imaging view field by 6 times. non-mechanical scanning imaging is achieved by providing a candidate method for large view field extension.

In order to reduce the impact of speckle noise on reconstructed phase quality in the field of digital holography, An improved non local mean filtering method for speckle suppression in digital holography is proposed. This method uses the Pearson correlation coefficient in statistics to improve the measurement method of sub block similarity in non local mean filtering, and divides the similarity coefficient into two different intensity domains based on its size, assigning different values to them, making the contrast of grayscale image denoising stronger. This method can not only further filter out speckle, but also better preserve the edge information of the image, which can solve the problem of image overfiltering in traditional non local mean filtering. The experimental results show that the improved non local mean filtering can effectively reduce speckle noise in digital holographic images, improve image quality and clarity, and perform better than most traditional digital image processing methods.

In the face of increasing data traffic demand in short-distance optical communication and the high cost of high-speed data center interconnection, a four-level optical signal generation scheme based on dual-polarization binary-phase-shift-keying (DP-BPSK) modulator is proposed . Experimental framework of the proposed scheme consists of a laser diode (LD), DP-BPSK modulator driven by binary data, polarization controller (PC), and polarizer. The DP-BPSK modulator driven by binary data without digital analog converter, making it structurally simple and easy to implement. To verify the feasibility of the proposed scheme, 4-level pulse amplitude modulation (PAM-4) signals are generated using this scheme and transmitted over a 65km standard single-mode fiber (SSMF) at different data rates. The performance of these signals is evaluated based on the experimental results, including the eye diagrams and bit error rate (BER), which indicates that the transmitted signals have a high quality. Therefore, the proposed scheme has promising application potential in future short-distance optical communication.

The 20mm carbon steel bright surface is a standard plate that demonstrates a cutting ability of 10000 watts. For verification, it employs a supersonic single-layer nozzle with an aperture of 1.2. The focus to defocus ratio is approximately +12.5, ensuring a superior cutting effect. However, using a hot nozzle for laser cutting heads during this process presents challenges for long-term stable cutting. Through optical software simulation of the laser head and actual beam analysis testing, results indicate that achieving a good cutting effect relies not only on the length of the focusing optical path but also on the total length of the optical path itself. The variation in cooling and light absorption devices within different cutting heads may be the primary reason that affects the outgoing beam under the same optical path.

Carbon fiber composite material is an important material for aircraft skin, and paint removal is the most important process before repainting the aircraft carbon fiber composite skin.Laser paint removal has the advantages of high efficiency, controllability, layering, and greenness, and is expected to become the main technical approach for removing paint from aircraft carbon fiber composite skin.It introduces the method and mechanism of laser layered controllable paint removal, summarizes the influence of process factors such as laser energy density, laser scanning speed, and laser overlap rate on the removal of aircraft carbon fiber composite skin coatings, proposes optimization ideas for laser layered controllable paint removal process, and summarizes the evaluation methods of laser paint removal effect.It lists the application of laser paint removal technology in the maintenance of surface coatings on aircraft composite materials, and looks forward to the development trend of laser paint removal technology for aircraft carbon fiber composite skin.

To study the effect of spectral reconstruction algorithm on spectral reflectance reconstruction accuracy and chromaticity in order to meet the demand of image reproduction to a greater extent and avoid the phenomenon of isochromia. An inverse variance weighted regression spectral reflectance reconstruction algorithm was proposed by improving the traditional principal component analysis method. Firstly, the inverse variance weighting model is introduced to adjust the weight of factors. Secondly, the spectral reflectance training sample set is normalized and a new covariance matrix is calculated. Finally, the spectral reflectance is reconstructed by singular value decomposition of the weighted spectral reflectance sample set. Experiments show that the color accuracy of CIE DE2000 based on inverse variance weighted spectral reflectance reconstruction algorithm is increased by 3.3%, spectral reconstruction accuracy is increased by 2%, and good color reproduction effect can be achieved. The weighted algorithm can be used in spectral reflectance reconstruction, which is helpful to improve the accuracy and chrominance of spectral reconstruction.

Fourier Transform Spectrometer(FTS) has been extensively utlized in solar activity observation because of its ultra-high spectral resolution. During the process of spectral reconstruction using zero-crossing single sided interferogram, spectral are subject to frequency leakage, side lobes effects, and reuse of sampled data near the zero optical path difference resulting in spectral smoothing and distortion. In order to obtain more accurate solar spectra, it is necessary to apply weighted apodization operations to the zero-crossing single sided interferogram. An odd polynomial asymmetric weighted apodization function is utilized to carry out weighted and apodization operations on the zero-crossing single-sided interferogram. An investigation is conducted to assess the impact of employing diverse apodization functions in the construction of an asymmetric weighted apodization function for spectral reconstruction purposes. The simulated experimental results demonstrate that the use of odd polynomial asymmetric weighted apodization function effectively facilitates spectral recovery. Additionally, when compared with the weighted apodization methods proposed by Griffiths, Xiang Libin, and Sumner P. Davis, the method proposed exhibits a smaller error. Finally, the proposed method is further applied to the interferogram obtained from the Bruker IFS-125HR . Compared to other apodization methods, the use of the method proposed in this paper yields superior results in solar spectral recovery.

With the development and popularization of remote sensing imaging technology, a large number of bands in hyperspectral images make most application researches encounter Hughes phenomenon. With the rapid growth of hyperspectral image data, the computational complexity of the existing traditional serial algorithm is high, and it is difficult to deal with high-dimensional and massive hyperspectral image data. Aiming at the above problems, a band selection algorithm based on mutual information calculation under Spark platform is proposed. The band correlation and multiple correlation are defined by entropy and mutual information theory. The data column transformation is designed based on Spark RDD programming model, and the data set is divided into column matrix to reduce the computational load. The algorithm is parallelized on the Spark platform to improve algorithm execution efficiency. Experimental results show that the proposed algorithm achieves an overall classification accuracy of 94.5%±0.5, with good acceleration performance and improved data scalability.

Wavelength as an important parameter of lasers, in military applications and medical applications need to measure wavelength, traditional wavelength measurement devices are not only expensive, but also cumbersome to operate. A wavelength measurement method based on dual-elastic optical modulation technology is proposed to realize rapid measurement of wavelength, and one data point can be measured every 200ms. The laser under test is loaded into the optical carrier signal by the bullet light modulator and the λ/4 standard waveplate with calibrated optical path difference, and the phase delay of the laser passing through the standard waveplate can be obtained by analyzing the optical signal, and the wavelength information of the corresponding laser can be further solved. The experimental results show that the relative error of the wavelength of the 632.8nm laser is 0.1%, the standard deviation is 0.11nm, the accuracy is 99.9%, and the measurement of 532nm and 650nm wavelength lasers is also more accurate, indicating the universality of the method.

The target coordinates of the projectile have always been the parameters that are often measured in the field of external ballistic testing of barrel weapons. Aiming at the problems of complex system and heavy main detector of the existing six light screens array sky screen vertical target, an integrated double-N-type six light screens vertical target measurement scheme is proposed. Three detection light screens are integrated in an optical lens of each main detector, and two main detectors form two N-type three light screens detection arrays in the air. When the projectile passes through six detection light screens in turn, the corresponding two main detectors are equipped with the circuit of three light screens sky screen target outputs six projectile signals in turn. The projectile signals are collected by the data acquisitioninstrument, and the collected projectile signals are processed by the projectile signal processing algorithm to obtain the time value of the projectile passing through the six detection light screens. Further, the target coordinates value of the projectile are calculated through the corresponding detection light screen parameters and target distance parameters. The measurement error of the system's target coordinate is analyzed, and the accuracy of the system's projectile target coordinate measurement is verified by two different kinds of caliber live ammunition tests.

In order to solve the disadvantages of conventional electrical flowmeter resist electromagnetic interference ability, based on the Carmen vortex street and light interference principle, A fiber optic Fabry-Perot vortex flowmeter is proposed for the HVAC system, the flowmeter using the characteristics of the periodic vortex around fluid, the connection between velocity and interferometer output light intensity, with the change of light intensity frequency reflect the flow rate, realize the flow rate sensing. The finite volume method is used to simulate the flowmeter, reasonably select the best detection point, and compare the simulation data with the theoretical value, which proves the rationality and feasibility of the flowmeter design.

Aiming at the problem that both accuracy and speed of the present three dimensional positioning techniques in the visible light communication system are still not good, an indoors positioning method for visible light communication system based on deep learning is proposed. Firstly, a neural network is designed to encode the fingerprint data to two dimensional array, and the convolutional neural network is utilized to learn the relationship between the fingerprint array and the target position; Then, the hyperparameters of the convolutional neural network are tuned automatically by the particle swarm optimization algorithm, thereby the training difficulty of the deep neural network is reduced. Besides, a method of dividing the training set、verification set and test set for the visible light positioning dataset is designed, it helps to mitigate the overfitting problem of the neural network, and improve the positioning accuracy. Simulation results show that, the average positioning error of the proposed method is 0.024m in 6×6×4m3 indoors environment, and the average positioning time is 0.478s.

The 3D measurement method based on phase unwrapping of structured light is widely used because of its high accuracy. However, the phase will be folded when the phase exceeds 2π, so the traditional 3D reconstruction of structured light requires phase unwrapping. The unwrapping phase of phase measurement profilometry at discontinuous depth is complicated. When there is a large depth difference on the surface of the measured object or when multiple planes are measured, because the wrapping phase range is［0, 2π］, there is a problem of folding multiple 2π in the phase difference calculated at the discontinuity, resulting in unwrapping failure. Phase measurement profilometry can not accurately express the position information of the object at this time. A three-dimensional measurement method of structured light based on defocus unwrapping is proposed. The 24-step phase shift method is used to obtain the wrapping phase, and the number of wrapping phase 2π is determined by time defocusing method to assist the unwrapping calculation. A corresponding platform is built and experiments are carried out to verify the proposed method. Experiments show that the proposed method solves the problem that the phase measurement profilometry can not accurately express the position of the object when the depth drop is large. The method can be used to obtain the depth information and details of the scene with large depth drop.

A new error analysis method is proposed for target location of airborne optoelectronic reconnaissance systems. Firstly, the target positioning equation was derived, and next the relationship of the positioning error and error source is obtained with the first order small perturbation method,and then the positioning error is qualitative analyzed, and it is concluded that the projection of attitude error on the baseline vector of target is the main source of positioning error. Furthermore, the scenario analysis method is intruduced assuming that the probability of the target appearing in space is equal, and then the the positioning error is quantitatively analyzed with monte carlo simulation, moreover, fixed scene method was introduced as a comparison,the results show that the positioning error obtained by the former has more numerical statistical significance. It is of great significance for the system demonstration and performance improvement of the photoelectric platform with this method.

In the field of smart logistics, the intelligent depalletizer takes advantage of information acquired by vision sensors to guide machine arm to grab the express box on the tray, so the accurate express box boundary detection is crucial to the grab point performance of the machine arm. The disorderly distribution、express label and printed content of the express boxes have an adverse effect on the detection precision of express box boundary, aiming at this problem, a express box boundary detection method based on deep vision is proposed. Firstly, the coarse-grained boundary of the express box is computed based on the depth image, thus the boundary detection ability of the express box is enhanced, the pose recognition ability of the express box is improved as well. Then, the coarse-grained boundary image and RGB image are fused to as the input of U-Net model to perform semantic segmentation, the U-Net model is trained with a mixed loss function combining level set loss and cross entropy loss, in order to improve the detection precision of the express boxes. Experimental results show that the proposed method improves the boundary detection precision of the express box, and the detection error is below 7 millimeter.

In order to satisfy the need of high imaging quality, stability and rejection of stray light in aerospace optical systems, a scheme of optimized borderless mirror structured based on Opto-Mechanical Integrated Technology is drafted in this journal article. The optical surface of the scheme is realized by the technology of surface-sintered glass on titanium alloy to achieve the diameter-to-thickness ratio of 16∶1 of the body of optical surface of the blank of the mirror. The difficulty and cost of machining is significantly lower than silicon carbide and beryllium mirrors. According to the result of analysis of static force and frequency,it can be concluded that the mirror is structurally stable,the influence of gravity andassembly stress is neglectable. The measured values of error of the optical surface of the sample are: Peak-to-valley value＜0.65λ. Root mean square value＜0.12λ(λ=632.8nm). The stability was verified in the environmental test. According to the result of analysis of stray light, the illuminance transmittance on sensitive angles will descend to around 5% to 20% of the traditional Opto-Mechanical separated design. The design has been successfully applied in orbit, and the scheme provides technical access of realizing the need of high optical stability and rejection of stray light on aerospace imaging devices that can be references.

Sub-wavelength focusing lenses are widely used in optical applications such as optical microscopy, imaging, and lithography. The focused optical field with sub-wavelength structure has additional axial aberrations that severely affect the quality of optical imaging at oblique incidence. A high numerical aperture (0.970) optical metalens design method is presented, which can simultaneously meet the sub-wavelength tight focusing and broadband operation at oblique incidence. Optical field control functions with wide-angle response meta-atoms are used, combined with corrections to the oblique incident optical field by aperture stop. The numerical simulation results show that the metalens with 5μm aperture stop, sub-wavelength tight focusing can be achieved within the incidence angle ±30°, and the peak full-width-at-half-maximum range is 0.600~0.885λ. Sub-wavelength focusing is achieved in the incident wavelength range of 550~750nm with an operational bandwidth of 200 nm.

The conventional optical storage system uses Run Length Limited (RLL) modulation technology, which is limited by the optical diffraction limit and has great difficulty in capacity enhancement. Multi-order optical storage technology uses a new multi-order recording medium or multi-order modulation technology, which can significantly increase the density and capacity of optical storage without changing the optical parameters. In order to improve the density and capacity of high-order optical storage, the multi-order modulation coding optimization method is studied for optical disc storage, and the 4th-order RLL (1,7) modulation coding method is proposed, which can improve the maximum recording density up to 2.4bits, increase the capacity of optical disc by 50%, and have certain error correction capability compared with the 17PP coding method currently used in Blu-ray disc. The maximum recording density can be 2.4bits, the disc capacity can be increased by 50%, and the error correction capability can be improved.

In response to the problem of generating bright spots caused by uneven lighting or smooth reflective materials on the workpiece, a differential feature attention guided polarization image highlight region removal algorithm is proposed, which uses a two-stage network structure to obtain high-quality highlight removal results. The first stage utilizes U-Net network to extract multi-level high-level and low-level features; In the second stage, a differential feature attention guidance module is designed to establish a correlation model between specular reflection and diffuse reflection in the feature space, supplementing and enhancing the original features of the diffuse reflection layer image. In addition, a dataset for polarization highlight removal was produced to verify network performance. Quantitative and qualitative experiments have shown that the proposed algorithm has a better ability to remove highlights than existing algorithms.