The optical wireless/radio frequency hybrid communication system compensates for the limitations of a single communication system, compensates for the shortcomings of radio frequency communication while maximizing the advantages of optical wireless communication, significantly improves the availability and reliability of the link, and provides a unique solution for future high-speed and high-capacity information transmission. The research progress of optical wireless/radio frequency hybrid communication system was reviewed in recent years, the working principles and applications of different hybrid communication system models were firstly introduced, then the challenges and solutions of the hybrid communication system were discussed, and finally the future development trend of optical wireless/radio frequency hybrid communication system was looked forward, aiming to lay the foundation for further research and development of optical wireless/radio frequency hybrid communication system.

Digital holographic microscopy is a combination of digital holography and microscopy, combining the advantages of both technologies, which provides a non-destructive, label-free, accurate and near real-time measurement method for quantitative 3D measurement in the micro-nano field. However, phase aberrations are additionally introduced due to component defects, misalignment, and environmental disturbances in the digital holographic microscopy measurement results. To obtain accurate quantitative phase measurement results, the origin and principal components of aberrations must be analyzed, and then compensate and corrected for aberrations. This review began with an introduction to the main sources and effects of aberrations in digital holographic microscopy imaging measurement. Then, the existing aberration correction methods were reviewed based on their different workflows and characteristics. Finally, the future development direction of aberration correction was prospected, which would provide useful references for researchers engaged in digital holographic detection research.

In indoor video viewing scenarios using visual display terminal (VDT), the VDT off-screen background light can reduce the discomfort caused by the contrast between light and dark inside and outside the screen, and the color as well as luminance properties of light will affect visual perception of people. The effect of indoor light environment on the visual perception of dynamic video viewing with VDT was explored, so as to create a VDT viewing light environment that can improve visual perception. The human factor engineering experiments were carried out based on psychophysical method, and the indoor light environment took the color/color temperature and luminance of the light as independent variables. In experiment 1, 3 kinds of color colors and 3 kinds of white color temperatures were set. In experiment 2, 8 kinds of luminance conditions were set, the video materials were categorized as high-dynamic video and low-dynamic video according to dynamic level, and the visual perception of the subjects watching the video using VDT under different light environment conditions was measured. The results show that the colored light is preferred, which conducts lower fatigue, higher comfort and other visual feelings than white light, among which the green light is the most comfortable condition. The luminance range of 9 cd/m2~30 cd/m2 is the most preferred, the condition range with best visual perception is 16 cd/m2~54 cd/m2, conducting lower fatigue, higher comfort, atmosphere and display color quality, and visual perception is worst when the luminance exceeds 330 cd/m2. The experimental results provide a reference for the study of the effect of indoor light environment on human visual perception, and provide practical guidance and suggestions for lighting design for improving visual perception of dynamic video viewing with VDT.

With the development of optical technology and modern medicine, the public acceptance of endoscope-based minimally invasive surgery is increasing. Doctors diagnose by observing the images of diseased tissues obtained from endoscopes, so the imaging quality of endoscopic optical systems is crucial. Most of the endoscopes currently on the market have clear images, but the details are not sharp enough. An endoscopic optical system with 2k resolution based on Zemax was designed to achieve better final image quality. By increasing the relative aperture of the objective lens, providing a new relay rigid lens optical system and matching adapter optical system, the entrance pupil diameter is 0.6 mm, the total length is 388.7 mm, the field of view is ±37.5°, the objective resolution is 32 lp/mm at an objective distance of 26 mm, and the objective angular resolution is 17/ c/(°). After considering the processing and assembly errors, the results of the tolerance analysis meet the actual use requirements.

Orbital angular momentum (OAM) has been increasingly investigated by researchers because it is expected to be a new physical quantity for communication multiplexing and has great potential for expanding channel capacity and improving spectrum resource utilization. Current terahertz vortex wave generation devices are limited by operating at only a single frequency, having a narrow bandwidth and having low conversion efficiency, so how to efficiently generate OAM in the terahertz band has become one of the key issues. An ultra-wideband reflective meta-atom was proposed, and a single-layer reflective metasurface was designed by combining the Pancharatnam-Berry phase concept and the phase superposition principle. The simulation results show that it achieves the conversion of circularly polarized terahertz waves into terahertz vortex waves carrying orbital angular momentum in a wide frequency range from 0.82 THz to 2.09 THz (with the relative bandwidth of 87.3%). The amplitude of the co-polarized reflection spectrum is higher than 0.97, the conversion efficiency is more than 94.7%, and the reflection phase covers 0°~360°. The Fourier transform was used to decompose each OAM mode in the reflected field, and the OAM mode purity was quantitatively analyzed, with the highest energy weight share of the dominant OAM mode l=?2 in all vortex waves at different frequencies, and the designed metasurface was further optimized to increase the energy share of the dominant mode. The designed metasurface has the advantages of high conversion efficiency, large operating bandwidth, and high main mode energy, which provides a reference for the efficient generation of wideband terahertz vortex waves.

Based on the infrared scanning image system theory, a continuous zoom area array scanning infrared optical system using 1 280×1 024 pixel@12 μm/F2 large area array medium-wave refrigeration sensor was designed. According to the requirements of the design technical indicators, the optical application parameters were analyzed, and then it was determined that the image scanning method was used to compensate the surface movement in the integral time generated by the movement of the scanning platform, so as to solve the thermal imaging tailing phenomenon during the scanning of the area array detector. The telescopic system adopted the structure forms of secondary imaging, negative component magnification and positive component compensation to realize continuous zoom, that was, the structure of the optical system was determined as the type of thrice-imaging. It was also necessary to make analytical adjustments to the cam curve and the hot/cold reflections of the scanning optical system in the design program. The optical simulation results show that the MTF value of the full field of view at the frequency of 42 lp/mm is greater than 0.3 under the condition of scanning galvanometer round trip, the cam curve is smooth without inflection point during the whole zoom process, and the maximum pressure angle is less than 50°. Finally, the imaging experiment test of the system was carried out. The test results show that the control system can complete the continuous zoom in the area of 60 mm to 600 mm, the scenery around the object is clearly visible in the zoom stage, and there is no cold reflection. At the same time, the imaging of the system without tailing phenomenon is clear and stable during the rotation scanning process. The system can be used in infrared systems that integrate continuous zoom search and tracking.

When the aspheric infrared lens is molded, the lens press-cutting time can be shortened by increasing the temperature of the molding stage, thus improving the molding efficiency. However, it is easy to produce the fog spots on the lens surface, like a bad lens. Through the analysis of the formation mechanism of lens fog spots, a non-contact preheating molding process was adopted to reduce the formation of it, and the molding experiments were carried out on a multi-station molding press, in which the elements of fog spots were detected and analyzed by using an energy spectrometer. In this molding experiment, the non-contact preheating method was used to increase the molding temperature from 206℃ to 211℃ when the preheating gap was 1 mm, with no fog spots formed on the lens surface, and the press-cutting time was shortened by 21 s. The results show that the non-contact preheating method in the multi-station molding press can effectively eliminate the formation of lens fog spots. The test results show that the volatilization of the lens material in the molding stage plays a dominant role in the formation of fog spots.

Multi-camera for 3D reconstruction can improve the accuracy and overcome occlusion, allowing for the acquisition of 3D position of targets from multiple viewpoints. In order to more accurately recover the distribution of targets in space, a convergent quad-vision camera 3D reconstruction system was introduced. A reconstruction platform was designed and built with four cameras evenly distributed around the target scene. After calibrating the relative pose of adjacent cameras in the system, the position and pose of each camera in a unified coordinate system were obtained through coordinate system transformation. The pose of the camera with the most transformations was verified, and the measurement results were consistent with those derived from transformation. A chessboard target array of size 66×65 was reconstructed, with a maximum relative error of 0.061% within a range of 45 mm. Compared with the fitted results, the root-mean-square (RMS) error was 0.319 3 μm. By using a metal block for reconstruction experiments, the shape could be recovered through its vertices. Experimental results show that the device can be used in high-precision and occlusion-resistant 3D reconstruction systems.

To address the problem of traditional unmanned aerial vehicle (UAV) imaging systems being unable to achieve the coexistence of large field of view and high resolution, a large field of view and high-resolution UAV-borne compound eye camera system composed of a curved sub-eye array, an optical relay system and an image detector was designed. The non-spherical design was used for the relay system to reduce the system volume. Each sub-eye had a focal length of 20 mm and a field of view of 10°. The relay system used a fisheye lens with a focal length of 7 mm to convert the curved focal surface formed by the sub-eye array into a planar image. The overall system had a field of view of 122°×106°, an F-number of 3, and a focal length of 3 mm, achieving a ground resolution of 0.8 m at a flying height of 1 000 m. The simulation results show that the modulation transfer function (MTF) of each optical sub-channel is greater than 0.3 at 208 lp/mm, and the image quality of the system meets the requirements within the given tolerance range. Compared to existing UAV-borne compound eye systems, the proposed system offers a larger field of view, higher resolution and smaller size.

Multi-dimensional information acquisition is the future development direction of the low-level-light (LLL) night vision detection technology. Polarization imaging is a dimension in the field of photoelectric detection, and the development of polarization camera is the premise of studying polarization imaging technology. The electron multiplying CCD (EMCCD) device integrates polarization array structure, which has the advantage of LLL detection and the function of polarization dimension detection. Based on this device, the hardware circuit design and development scheme of polarization LLL integrated camera were discussed. The camera could complete the synchronous acquisition of polarization dimension information and light intensity information, and the original data was processed by polarization operation through FPGA. Then, the processed image data was transmitted to the PC. A test system was built to analyze the performance of the developed polarization camera. The experimental results show that, at 273 K temperature and 2 MHz readout frequency, the readout noise of the device is 8.81e-, the dynamic range is about 74 dB, the extinction ratio of the camera can reach 50.95, and the transmissivity can reach 60.16%. The camera can selectively output the degree of polarization image, the angle of polarization image, the image of light intensity and polarization fusion in real time, which greatly improves the recognition and detection ability of targets in the night environment.

In the design of lighting system, the uniform lighting of the receiving surface and the full use of light energy have always been urgent problems in the light source design. At present, in the field of LED light source design, the Sparrow Criterion analysis and differential equation calculation are usually used to optimize the lighting effect. The optimization level of these methods is relatively single, with a long cycle and a large error. In order to strengthen the optimization efficiency of the LED light source system and synchronously improve the illumination uniformity and energy utilization rate of the light source system, an optimization design algorithm based on the illumination uniformity evaluation function, energy utilization evaluation function and comprehensive evaluation function was was proposed. Firstly, the numerical analysis method was used to optimize and adjust the conical constant K and curvature radius R of the second side of the single light source system, so as to realize the synchronous optimization of the illumination uniformity and energy utilization rate of the whole reflective cup light source system. The study results show that the optimized system with the algorithm increased by 14.2%, the energy efficiency increased by 16.75%, and the proximity to the ideal value increased by 14.42%, which verifies the feasibility of the optimization method. On this basis, the influence of multi-light source system array spacing for illumination uniformity and energy utilization system was further studied, the optimal array spacing of light source array system, under the distance of the illumination uniformity and the ideal value proximity is 44.84%, energy utilization rate is 88.84%, finally achieving a LED light system in rectangular array with high uniformity and energy utilization.

Photo response nonuniformity (PRNU) noise is a unique noise introduced to optical imaging sensors during imaging and can be effectively applied to the source camera identification of compressed video. Due to the problem that existing algorithms do not produce significant effect on extracting PRNU of compressed video, an improved algorithm to extract PRNU was proposed. Firstly, the loop filter of video codec was removed, and the video frame was decomposed by double density-dual tree-complex wavelet transform. Then, the high frequency subband was estimated by bivariate shrinkage algorithm based on Bayesian threshold estimation, and the adaptive window Wiener filter was used for secondary estimation. Finally, after the noise residuals were obtained, they were aggregated by the maximum likelihood estimation method based on quantization parameter weighting, and the PRNU was estimated with video frames. Experiments on the VISION dataset show that the accuracy of the proposed PRNU extraction method in WhatsApp compressed video recognition is improved to 75% at 20 s.

In order to improve the detection accuracy of infrared targets, a Faster R-CNN infrared target detection algorithm introducing a frequency domain attention mechanism was proposed. Firstly, a parallel image enhancement preprocessing structure was designed to address the issues of edge blur and noise in infrared images. Secondly, a frequency domain attention mechanism was introduced into Faster R-CNN, and a new infrared target detection backbone network was designed. Finally, a path enhanced pyramid structure was introduced to fuse multi-scale features for prediction, and the rich location information of the underlying network was utilized to improve detection accuracy. The experiment was conducted on a dataset of infrared aircraft. The results show that the AP of improved Faster R-CNN target detection framework is 7.6% higher than that of the algorithm with ResNet50 as the main stem. In addition, compared with current mainstream algorithms, the proposed algorithm improves the detection accuracy of infrared targets and verifies the effectiveness of the algorithm improvement.

Affected by the high turbidity, insufficient illumination and poor uniformity of the underwater environment, the images obtained by imaging mechanisms have defects such as low contrast, blurred details and color distortion. To handle above problems, an underwater image enhancement algorithm based on a dual-head enhancement and non-uniform correction was proposed. The dual-head enhanced network was constructed to extract multi-scale features from shallow information and to fuse the context information of different channels, which was conducive to the enhancement of low contrast of underwater images. Furthermore, the constructed non-uniform correction network was used to perform nonlinear weighted fusion of different channels and positions of the image, which was conducive to the recovery of color consistency and brightness. Compared with the 10 algorithms, the optimal value of the peak signal-to-noise ratio and structural similarity in the UIEB test set was improved by 4.02 dB and 0.120, decreased by 1.51 on the CIEDE2000 index, and decreased by 2.13 dB, 0.025 and 0.48 on the LUSI test set, respectively. Experimental results show that the proposed algorithm has a significant enhancement effect for non-uniform underwater images, and is more in line with the characteristics of the human eye.

The automatic classification and recognition of conical yarn paper tubes has been a hot topic in the intelligent manufacturing of this component. A yarn paper tube classification method based on multiple fusion optimized template matching was proposed to address the problems that traditional image classification methods could not balance speed and accuracy, as well as high cost of deep learning, difficult deployment, and high hardware requirements. Several improved algorithms and strategies were adopted and three times data dimensionality reduction was used to accelerate the template matching speed. First, the optimization algorithm, successive elimination algorithm (SEA) used for motion estimation was used in template matching, and the threshold of this algorithm was improved to adaptive threshold for enhancing the robustness of the algorithm. Then, the wavelet pyramid was used to further reduce the amount of operations to improve its speed. Finally, the cross gray scale feature was used instead of the traditional sum of absolute differences (SAD) algorithm to calculate the performance index, and the strategy of stopping the iterative search in advance was used to further filter the data and set the cumulative error threshold to stop the search in advance. The matching experiments show that the improved algorithm guarantees the accuracy and the matching speed reaches about 0.126 s. The comparison and ablation experiments show that, under the premise of ensuring the accuracy, the speed of the algorithm is nearly 11 times higher than that of the traditional SAD algorithm, compared with some other classical methods in the speed are also improved, which verifies the effectiveness of the method.

Cracks are the most important type of pavement diseases, and the accurate crack segmentation is an important decision basis for national preventive maintenance management of roads. To address the problem of crack segmentation accuracy of existing models for pavement under complex background, an end-to-end crack segmentation model based on convolutional neural network was proposed, which used a layered structure of ConvNeXt encoder to extract multi-scale features. A pyramid pooling module was used to further obtain the global priori features by the top layer of features, and the feature fusion was performed through a pyramid structure with lateral connections and top-down. A weighted cross-entropy loss function was employed to enhance the detection performance of model for the crack and background imbalance problem. In addition, a crack dataset UCrack with 2 876 cracks covering multiple crack types and a wide range of backgrounds was created to provide rich features for model learning. Experiments show that, compared with other best-performing models, the model recall and F1 score on the UCrack test dataset are improved by 2.68% and 6.89%, respectively. The test on the CrackDataset dataset achieves recall of 85.68% and F1 score of 80.11%, which implies that the model has better generalization capability and can cope with pavement crack segmentation with complicated scenarios.

A compressed ultrafast imaging system based on compressed sensing and streak camera was simulated. The original 3D image, denoted as I (x-y-t), was encoded and modulated by using digital micromirror devices (DMD), and subsequently transmitted to a slit full-open streak image converter. By means of deflection via a deflecting electric field, the multiple images at various time points were superimposed, resulting in the generation of the final integral image on the CCD. To reconstruct multiple original images I (x-y-t) from the CCD integral images, a total variational restoration algorithm was employed. The process of image acquisition and the restoration algorithm within the compressed ultrafast imaging system was simulated, and the eight dynamic 2D images depicting laser transmission through an air medium were obtained. Each image is exposed for a duration of 12.5 ps, and the reconstructed signal demonstrates a similarity of 0.92 when compared to the original signal.

To meet the demand of 3D real-time dose verification in radiotherapy, the 3D dose measurement technology based on scintillator luminescence was proposed. Based on the principle of scintillator luminescence by radiation, the 3D dose distribution was converted into 3D light distribution, and the 3D light distribution was measured and reconstructed by camera and optical emission tomography. The iterative algorithm was needed for 3D reconstruction based on optical emission computed tomography, and the system response matrix was an important parameter for iterative reconstruction. A calculation method of system response matrix based on point cloud distribution was proposed on the basis of pinhole imaging model, which converted voxels into random point clouds and calculated the number of point cloud projected in the pixels as the response of voxels to pixels. In the comparison of simulated imaging, compared with the traditional calculation method based on projection area, the proposed method suppressed the stripe-like error on the simulated images, improved the uniformity and gradient uniformity of simulated images, and improved the simulation accuracy, which was conducive to improving the accuracy of 3D reconstruction.

Ultra-short and ultra-intense pulsed lasers (femtosecond lasers) possess extremely high peak power, and hold broad application prospects in laser inertial confinement fusion, high-energy physics, laser micro-processing and other fields. The peak power of femtosecond pulsed lasers is a crucial parameter for evaluating the performance of ultra-short and ultra-intense pulsed laser systems. A peak power measurement method of terawatt-level femtosecond pulsed laser based on the spectral phase coherent direct electric field reconstruction was introduced, along with the composition and working principles of the measurement device. A set of peak power measurement device of terawatt-level femtosecond pulsed laser was constructed, and the sources as well as main factors of measurement uncertainty influencing the measurement results of peak power were analyzed and discussed. The repeatability of the peak power measurement is 2.9%, and the measurement uncertainty reaches 17.6% (k=2), which effectively addresses the issue of peak power measurement of terawatt-level femtosecond laser.

To further improve the success rate of detecting and identifying airborne targets under few shot conditions, a few shot target detection method based on background suppression and classification correction was proposed. Firstly, aiming at the problem that the background foreground of incoming air targets was easy to confuse, a background suppression module was introduced in the front end of the regional candidate network, which enhanced the foreground features by suppressing the background features and reduced the influence of the target background on detection. Secondly, the feature aggregation module was inserted after the background suppression module to focus on the target features, and to alleviate the problem that the target features were difficult to extract and not obvious due to few shot conditions, so as to correct the classification parameters of the network model. Finally, a contrast branch was introduced into the detection head network for enhancing the similarity within classes and uniqueness between classes, which alleviated the problem of high similarity between classes and large differences within classes of incoming targets, and realized the further correction of the network classification. The experimental results show that the proposed algorithm performs best in the 1, 2, 3, 5 and 10 shot experiments, with average accuracy reaching 28.3%, 32.8%, 39.9%, 42.9% and 56.2%, respectively, which improves the detection performance of few shots airborne incoming targets.

In order to improve the driving efficiency of photoelastic modulator (PEM), a method of impedance matching parameter calculation based on dynamic parameter measurement of PEM was proposed. The relationship between PEM modulation amplitude and driving voltage was analyzed theoretically, and the equivalent circuit model of PEM and its resonance matching network were established. On this basis, the relationship between PEM resonant driving voltage and various parameters was derived, and the measurement system and verification method for the dynamic test of PEM were also designed. Theoretical simulation and experimental comparison of various characteristic curves were conducted on a PEM with a resonant frequency of 44.822 kHz, which verified the reliability of the dynamic measurement system, and the PEM optimal matching parameters were obtained by numerical simulation. Near the optimal matching parameters, the different matching parameters were selected to measure the actual resonance driving voltage. The correlation between the measurement results and the simulation curve reaches 0.996 4, and the change trend is basically consistent before 10 μF. The peak resonance driving voltage reaches 510 V, which is better than other driving matching methods and close to the theoretical maximum, and the relative error is less than 1.16%. The optimal matching parameter calculated by the PEM equivalent dynamic parameters can achieve the maximum driving efficiency of PEM.

White light microinterferometry has obvious advantages in measuring the topography of planar step structures. However, due to the limitation of the numerical aperture of the objective lens, the reflected light on the surface of the sample is weakened with the increase of the slope when measuring the curved surface sample, and the contrast of the interference signal decreases, which leads to the increase of the error of topography measurement. Based on the theory of surface transfer function (STF), the inverse filter can be calculated to correct the topography measurement error of curved surface samples. However, the gain of the inverse filter of the existing method is limited, which is unable to elevate the high-frequency signal in the spectrum, and the improvement of the maximum measurable slope is limited. To address this issue, the modulus of the virtual STF calculated by the characteristic parameters of the white light interferometer was used as the amplitude gain function, and the phase of the measured STF obtained by the Fourier transform of the measured interferogram was used as the phase compensation function. A virtual-measured fusion inverse filter was formed, which realized the correction of the curved surface topography measurement error of white light interferometer. Using this method to correct the topography measurement results of the microsphere, the maximum measurable slope after correction is increased from 8.09° to 21.20°, and the root mean square error is reduced from 0.545 5 μm to 0.175 9 μm, which achieves the purpose of improving the maximum measurable slope of curved surface sample and reducing the measurement error, and effectively improves the measurement range of the instrument for the curved surface sample.

In order to improve the accuracy of change detection in co-registered high-resolution remote sensing images, a Siamese network combining mobile convolution and relative attention (MCRASN) was proposed based on ChangeFormer. A multi-stage combined encoder was constructed to replace the original network encoder by using vertical layout combined with mobile convolution and relative attention to efficiently capture the required multi-scale detailed features and pixel correlation information, and the difference module was improved to be a learnable distance metric module for distance calculation. At the same time, the equalized focal loss (EFL) loss function was introduced to solve the problem of imbalance between positive and negative samples in the dataset to achieve accurate change detection. The experimental results show that the proposed MCRASN method has better change detection performance on the LEVIR-CD dataset, with precision, recall, F1 score and overall accuracy of 93.94%, 89.26%, 91.54% and 99.18%, respectively, which is superior to previous methods.

Aiming at the problem of detection and positioning of reference plane obstacles, an embedded image detection system using angle intersection method to measure two-dimensional coordinates was designed. The two-line method was adopted to calibrate the linear array CCD image sensor by two-dimensional coordinate measurement system, and the angle intersection method was used to calculate the coordinates of the measured object, so that the uncorrected two-dimensional coordinate measurement results were obtained. The control variable method was used to measure the coordinates of X axis and Y axis, respectively, the Matlab software was used to process the data, and the polynomial linear fitting of the measurement errors of X axis and Y axis was carried out respectively to obtain the coordinate correction formula, in which the corrected two-dimensional coordinate errors became significantly smaller. The experimental results show that the two-dimensional coordinate image measurement system based on angle intersection can measure two-dimensional coordinates in real time, accurately, quickly and reliably, and provides a feasible scheme for two-dimensional coordinate measurement of reference plane obstacles, which has certain application values and significance.

Aiming at the increasing demand for signal high-precision solution methods of grating interferometric displacement sensors, an improved method of displacement solution based on ellipse fitting compensation and arctangent algorithm was proposed. The estimation of signal error parameters was realized by Fourier transform and normalized elliptic parameter fitting method, the orthogonal compensation of the signal with errors was carried out by constructing a linear error compensation model, and the signal was linearized with the arctangent algorithm to finally achieve high-precision displacement solution readout. The simulation results of Matlab show that this method is highly effective for the signal orthogonal compensation effects, and the maximum relative error of displacement solution for linearization is less than 0.2%, which provides an effective way and method to improve the displacement solution precision of grating interferometric sensors.

Aiming at the shortcomings that the current aircraft type identification method is easily affected to environmental influences, a novel aircraft type identification method based on fiber optic Bragg grating (FBG) sensing array of smart runway was proposed. The distributed vibration response of the aircraft taxiing was collected by using the FBG array buried horizontally under the pavement. By analyzing the time-history impulse response features of multiple measurement areas, the time differences between the main and auxiliary landing gears passing through the optical cable were determined. The taxiing trajectory of the aircraft was sensed by the FBG array buried longitudinally under the pavement, through which the taxiing speed of the aircraft was determined by polynomial fitting. The aircraft type was identified based on matching relationship between the test value and the theoretical value of the main and auxiliary landing gears of the aircraft. The aircraft information in the test flight and the initial two-month operation of a certain airport were used for method verification. The results show that the identification accuracy of the proposed identification method can reach 98.44%, which can effectively distinguish the B757, B738, A320 and A321 models.

Aiming at the temperature effect of half-wave voltage of Y-waveguide modulator on resonant fiber optic gyroscope (RFOG) based on broad spectrum light source, the effect of temperature-induced half-wave voltage characteristics of Y-waveguide modulator on RFOG was studied. The effect law model of voltage characteristics on scaling factors of RFOG system based on broad spectrum light source was established. The model shows that the temperature-induced half-wave voltage characteristics of Y-waveguide modulator will lead to the change of the scaling factor of RFOG system based on broad spectrum light source. A half-wave voltage measurement system of Y-waveguide modulator used for broad spectrum light source was established, and the measurement accuracy of the system reached 1 mV. The influence of the temperature-induced half-wave voltage characteristics of Y-waveguide in the full temperature range in RFOG system based on broad spectrum light source was tested by experiment. The test results show that the half-wave voltage of Y-waveguide modulator is linearly and negatively correlated with temperature. The temperature-induced half-wave voltage characteristics of the Y-waveguide modulator result in a maximum relative variation error of 1 266.01 ×10?6 in the scale factor of the RFOG system based on the broad spectrum light source.

In order to solve the problem of frequent disconnection of carbon fiber conductors for large-capacity and long-distance transmission due to undetectable hidden defects, a detection method for hidden defects in multi-strand carbon fiber composite core conductors based on optical fiber sensing technology was proposed. The operating environment of the wire was established and the operating conditions were simulated. The time-domain reflection technology based on distributed fiber Brillouin scattering was adopted to detect the temperature and strain distribution of carbon fiber wires, and the optical time-domain reflection technology was combined to detect the loss of optical fibers in carbon fiber wires. Comprehensive comparative analysis was conducted to obtain signal feature quantities such as fiber temperature, strain and loss that could characterize hidden defects in multi-strand carbon fibers, and a neural network model was constructed with each signal feature quantity as input to the model. Through model training, the various weight coefficients within the model were determined, enabling it to effectively detect hidden defects in multi-strand carbon fiber composite core wires. The experimental results show that this method can effectively obtain signal feature quantities of various types of fiber optic and can accurately detect various hidden defects in wires, which has important practical application values.

Indoor non-orthogonal multiple access (NOMA) visible light communications (VLC) systems have the potential to enable high-rate multi-user communication. Nonetheless, the multipath effect may lead to a substantial reduction in communication reliability and user fairness. Therefore, a virtual time reversal mirror (VTRM) technology for NOMA-VLC channel equalization to eliminate the influence of multipath effect on communication performance was proposed. Initially, the indoor NOMA-VLC system model and the characteristics of communication optical links in multi-user scenarios were analyzed. To leverage the sparsity characteristics of optical links gains, the sparsity adaptive matching pursuit (SAMP) algorithm was adopted to estimate the channel impulse response (CIR) of NOMA-VLC systems. On this basis, the VTRM method was introduced to equalize the channel of NOMA-VLC, reducing the impact of channel fading through the spatio-temporal focusing characteristics of VTRM, and the received signal was reconstructed to suppress the multipath effect. The theoretical analysis and simulation results show that the NOMA-VLC system equalized by the proposed algorithm improves the performance of user 1 by 4.4 dB, user 2 by 5.7 dB, improves the average signal-to-noise ratio (SNR) of the two users by 5.05 dB, and reduces the performance difference between users from 1.6 dB to 0.5 dB, when the forward error correction (FEC) bit error rate (BER) threshold is met. Overall, this method provides an effective approach for NOMA-VLC channel equalization.