The working principle of four-quadrant detector for laser guidance was introduced. According to the technical requirements of laser guidance and the working characteristics of four-quadrant detector, an improved method of lens design of four-quadrant detector for laser seeker was proposed. Aiming at the problem that nonlinear relationship was not easy to solve, the four-quadrant detector lens was designed by using Zemax in sequential mode, and the energy distribution of the light spot was controlled by setting operand, so that the angle deviation of the target was linearly related to the output signal of the four-quadrant detector, which could improve the real-time detection accuracy. The feasibility of this method was verified by simulation analysis combined with application background. The simulation results show that the full field of the system is ±10°, the linear field of view is ±0.8°, the focal length is 21 mm, the spot radius is about 0.4 mm, the pupil diameter is 36 mm, and the optical length is 35 mm. This method does not require uniform energy of light spots on the detector, nor does it require uniform size of light spots in each field of view, which greatly simplifies the design.

For the angle sensitivity of snapshot imaging chips and imaging optical components, a snapshot spectral imaging system based on field compression was designed. The system consisted of a front field compression system, an aperture, a rear imaging lens group and a spectral imaging chip. Through Zemax optical design of the front optical system, the field of view of ±10° could be compressed to ±3° in the range of 450 nm~800 nm, and the maximum wave difference was less than a quarter wavelength. The rear lens group was designed to correct chromatic aberration and spherical aberration of the optical system. The RMS radius of each field of view of the whole optical system was close to the pixel size of the array detector, and the relative distortion was less than 2.138%. Finally, the feasibility of the field compression optical system was verified by experiments, and the imaging system was used to image targets with different color letters and location targets. The results show that the central wavelength of red R is 610 nm, the central wavelength of green G is 500 nm, the central wavelength of blue B is 460 nm, and the central wavelength of red ground and green ground is 613 nm and 517 nm, respectively, which further verifies the accuracy of the system.

With the development of the loitering missile weapon system, the requirements of miniaturization, multi-function and high integration of the optoelectronic load on the loitering missile are getting higher and higher, and the accompanying heat dissipation problem is becoming increasingly prominent. In order to solve the problem of poor heat dissipation performance of the optoelectronic system on loitering missile, an optimization design method of air-cooling system based on parametric modeling was established. The designable parameters of the air-cooling system were firstly determined, then the several groups of sample points based on the Latin hypercube sampling method were selected, and the output response of each sample point corresponding to the input parameters through ICEPAK simulation calculation was obtained, thereby establishing the air-cooling radiator Kriging proxy model. Then, based on the proxy model, the adaptive simulation annealing (ASA) algorithm was used to optimize the air-cooling system. Finally, the optimization results were substituted into the thermal simulation model to verify its accuracy. Taking a small missile-borne optoelectronic system as an example, the thermal simulation analysis of the air-cooling radiator under empirical design was carried out to optimize the temperature minimization of heat source chip. The results show that compared with the empirical design, the optimized air-cooling radiator can reduce the temperature rise of the heat source by 28.5%, which effectively improves the heat dissipation level of the missile-borne optoelectronic system, and meets the requirements of system design.

An asymmetric spatial aberration wind measurement interferometer was designed to simultaneously detect 557.7 nm oxygen-atom green-line airglow and 630.0 nm oxygen-atom red-line airglow in the detection range of 90 km~300 km according to the needs of wind field detection in the middle and upper atmosphere, and the optical range difference compatible with the two bands was selected according to the relationship between the interferometric fringe modulation regime and the optimal optical range difference for the detection of the two bands. The field of view of the interferometer was improved by designing and selecting the top angle and material of the expanded field of view prism. In order to reduce the influence of thermal deviation on the accuracy of wind measurement, the relationship equations between thermal deviation and shim material, shim thickness, and interferometer bias were derived, and the corresponding parameters were calculated by this equation. In addition, a middle-step grating was adopted as the reflection grating to realize the simultaneous detection of dual-band. According to the needs of the foundation detection, the required front lens group and rear lens group were designed. Finally, the overall system was simulated and the simulated streak map was obtained to verify whether it met the needs of dual-band detection. The simulation results show that the thermal deviation of the optical range difference of the final interferometer in the 557.7 nm airglow band is 3.22×10?6 mm/°C, and the phase thermal drift is 0.03 rad/°C. The thermal deviation of the optical range difference in the 630 nm airglow band is 9.45×10?7 mm/°C, and the phase thermal drift is 0.009 42 rad/°C. The design results show that the system is suitable for dual-band detection. The design results show that the system meets the need for 90 km~300 km wind measurement and reduces the influence of thermal deviation on the measurement accuracy compared with the earlier design.

After configuration size and combing type of aerial electro-optical equipment have been confirmed, thickness dimension is critical to its imaging performance. The window designing subject was described and analyzed from three aspects: design variables, combing types and applied loads, and the design goal of plane window thickness based on structural rigidity and root mean square (RMS) wavefront error was determined. Based on the first order structural resonance frequency and the RMS wavefront errors under temperature and pressure loads effects, the window thickness dimension range of 11.9 mm to 18.4 mm was quantified and solved. Integrated analyzing process was proposed aiming at window assembly performance in synthetic conditions. The first order structural resonance frequency of optical window assembly is 151 Hz, the RMS wavefront error is less than 1/10 reference wavelength with effects on composite load, such as flow field, gravity and vibration in operation. The test results show that the RMS wavefront error of optical window is less than 0.07 reference wavelength, and the images of vibration and flying test are stable and clear, which verifies that the design and analysis method of window thickness dimension is right and effective.

Aiming at the detection of SO2 concentration in SF6 decomposition products in electrical equipment, the design of ultraviolet absorption spectrum analysis module and data processing method were studied. Low power consumption pulsed xenon lamp light source was used to shorten preheating time. A long optical path gas absorption cell with multiple reflections was designed to effectively shorten the response time. The gas consumption was reduced, and the light source and micro spectrometer were directly coupled with the gas chamber, so that the stability was better. The SO2 concentration was inversed in the 280 nm~320 nm spectral band. The partial least squares regression multiple correction method was used to establish a regression model for the differential absorbance of SO2 spectral band and the SO2 concentration, and the errors of the model was less than 0.5 μL/L. The principle prototype was designed, and the feasibility of the design scheme was verified by experiments.

Optical splitter is an important optical element in spectral imaging system. Among them, filter light splitting is a common and effective means of light splitting. A spectral imaging system based on angle-tuned narrowband filter splitting was proposed. By adjusting the angle between the filter and the incident light, the central wavelength of the transmission spectrum was shifted, so as to realize spectral imaging in a specific wavelength range. The system mainly consisted of an optical lens with an adjustable filter, an angle tuning device, a CMOS camera and an upper stage mechanism. The field of view angle of the system is 17.5°, F/# is 8, focal length is 26 mm, and total length is 200 mm. The MTF curve of each band is greater than 0.3 at 96 lp/mm, the distortion is controlled within 2%, and the spectral resolution is about 3 nm. After experimental testing and verification, the system can perform angle tuning in the incidence angle range of 0~46 degrees, which realizes the continuous light splitting function, and can capture the spectral image corresponding to any central wavelength in a certain spectral range.

TC4 titanium alloy has a series of advantages such as excellent corrosion resistance, low density, high specific strength, good toughness and weldability, and plays an increasingly important role in the aerospace field. Based on the finite element analysis method, the temperature field of TC4 titanium alloy disc was numerically calculated by using the heat conduction equation. On the basis of analysis of the working characteristics of metal materials processed by pulsed laser, a thermal model that conformed to the actual processing characteristics was established, and the influence of the temperature field of TC4 titanium alloy with laser power, spot radius and laser pulse width was numerically analyzed. The results show that if the central laser wavelength is 1 064 nm, the laser power is 2 kW, the spot radius is 2 mm, the laser pulse width is 8 ms, the pulse repetition rate is 1 kHz, the diameter is 5.0 cm, and the thickness of 5 mm, the peak temperature rise of TC4 titanium alloy within 50 ms is 1 209.80 K. Under the same conditions, when spot radius is 1.5 mm, 2.0 mm, 2.5 mm and 5 mm, respectively, the highest thermal deformation of the end face of titanium alloy is 30.033 μm. The research results will provide a theoretical basis for laser processing of titanium alloys and accurate setting of laser processing parameters.

Semantic segmentation of remote sensing images is a task of great theoretical importance and practical values. Remote sensing images contain rich feature information, and the pixel information at the boundary is also more difficult to determine, making segmentation more difficult. Based on the structure of Mask2Former, an improved multi-scale feature interaction structure Mask2Former-MS and a boundary optimization structure Mask2Former-BR were proposed, the former utilized bilinear interpolation for up-sampling and down-sampling to achieve the effect of feature fusion, and a channel attention mechanism was introduced to reduce the effect of redundant information. The latter utilized the atrous spatial pyramid pooling (ASPP) module for feature extraction, the different atrous rates was used to capture feature information at different scales by each parallel atrous convolution branch of ASPP, and the ReLU layer and batch normalization (BN) layer for activation and normalization were used to suppress gradient vanishing and made the pixels at the boundary more accurate. The experimental results show that by comparing the U-Net network and the Mask2Former structure on the Gaofen image dataset (GID), the optimal precision and optimal accuracy of the improved Mask2Former-MS structure and the Mask2Former-BR structure are 88.82%, 85.90% and 89.56%, 87.46%, respectively, and the segmentation effect of the improved structures is better.

In order to improve the positioning accuracy of the reference position in the grating diffraction laser warning system, a spot center approximation method based on the minimum grayscale difference of indexed ring was proposed. According to the given initial coordinates of the spot center, a 3×3 center coordinate matrix was generated. The Lagrange interpolation was used to calculate the grayscale values of points on the indexed ring centered at the center coordinate matrix. The center coordinate with the minimum grayscale difference on the indexed ring, which represented the true coordinates of the spot center, was approximated using a binary search method. In the accuracy comparative experiment, the proposed algorithm showed average errors of 0.001 3 pixels in the x-direction and 0.001 1 pixels in the y-direction across three sets of ideal spot model samples. In the stability comparative experiment, the proposed algorithm exhibited average standard deviations of 0.165 3 pixels in the x-direction and 0.186 0 pixels in the y-direction across three sets of actual spot image samples. The spot center approximation method based on the minimum grayscale difference of indexed ring has obtained the lowest average error or standard deviation in two comparative experiments, respectively, which demonstrates higher accuracy and better stability, thereby improving the positioning accuracy of the reference position in the laser warning system, and provides a new solution for spot center positioning algorithms.

Image colorization is one of the core problems of great interest in computer vision and has attracted more and more researchers in recent years. The colorization technique improves the recognition rate and scene comprehension of targets of human eyes in grayscale images, especially in low-light-level (LLL) images. However, the current colorization methods still have problems such as color bleeding, color deviation and boundary blurring. To solve the above problems, a colorization method for grayscale images combined with semantic segmentation was proposed. A colorization network composed of a classification sub-network and a semantic segmentation sub-network was designed to fuse the features extracted from the semantic segmentation sub-network and the classification sub-network into the colorization network, and guide the colorization network to assign an accurate color to each object and background in the image. Then the attention mechanism combining with the space and channel was introduced into the semantic segmentation sub-network to obtain a more accurate semantic segmentation results, thereby improving the perception ability of image boundaries and the processing ability of details of the colorization network. To verify the effectiveness of the proposed method, several sets of LLL images of different scenes were captured under LLL environment and colorized by multi-pixel photon counter (MPPC) experimental platform. The experimental results show that the peak signal-to-noise ratio (PSNR), structural similarity index measure (SSIM), and learned perceptual image patch similarity (LPIPS) of the proposed method is improved by 6.12%, 11.65%, and 4.99%, respectively.

To address the issue of traditional algorithms being limited in type and having substantial debugging difficulties in metal surface defect detection, a distributed aperture detection imaging system was designed to achieve super-resolution reconstruction. On this basis, an improved template-difference detection algorithm was proposed. Firstly, adaptive non-local mean filtering and large-scale median filtering were applied for preprocessing, followed by difference operation. Then, adaptive binarization was realized based on the structure similarity index measure. Finally, the scratches, void defects, and rivets were classified by utilizing the prior feature information of defect area, shape, and color. Experimental results indicate that the improved template-difference method achieves the best performance in both recall and precision. The average recall of scratch defects reaches 98% and average precision is 62.57%, significantly superior to traditional algorithms such as Sobel, Prewitt, and Laplacian (with records of 53.74%, 47.78%, and 25.72%, respectively). This system scheme enhances the efficiency and accuracy of metal plate defect detection, possessing significant practical application values.

Road damage detection is of vital importance in the process of road maintenance. In order to solve the problem that the current road damage detection relies on large vehicle-mounted detection equipment, resulting in high cost and poor universality, an ultra-lightweight surface crack detection model applied to edge equipment was proposed. Firstly, a lightweight road damage detection network was constructed, and on this basis, redundant parameters in the network were deleted based on the feature mapping contribution pruning strategy, so as to ensure real-time monitoring in edge devices without reducing the detection accuracy. Finally, the experimental results show that the size of the proposed model is only 2.06 M, and the accuracy rate reaches 68.6% at the frame rate of 40. Compared with the original YOLOv5s model, when the accuracy is only reduced by 3.4%, the number of parameters is reduced by 70.8%, and the inference delay on the edge platform is reduced by 175 ms. In summary, the proposed model can detect road characteristics more effectively while maintaining a high level of accuracy, and has good robustness for road damage detection.

In view of the test requirements, test conditions and the deficiencies of existing projectile motion parameters measurement methods of airborne weapons projection test in flight test, an accurate measurement method of projectile motion parameters based on three-dimensional model was proposed. Firstly, the method, principle and system composition of accurate measurement of projectile motion parameters based on three-dimensional model were briefly discussed. Then, the methods of high precision geometry and texture modeling, automatic registration of three-dimensional model and dynamic sequence image, automatic point finding, turning point tracking and high precision pose and attitude solving were discussed in detail. Finally, a ground test verification system was constructed, and the verification tests for the accuracy of static measurement data and the effective reliability of dynamic measurement data were carried out. The test results show that the proposed method effectively improves the measurement accuracy and reliability, and realizes the three-dimensional reproduction of the motion process based on the projectile body model.

The study of solar spectrum is of profound significance to science and human society. The satellite-borne solar imaging spectrometer designed in accordance with this requirement has a low signal-to-noise ratio and a large uncertainty after calibration of the radiance response directly on the ground, so it is difficult to achieve accurate measurement of the radiance response. Therefore, the solar radiance hyperspectral responsivity calibration system was constructed to test the whole system radiance responsivity. The calibration accuracy of the solar imaging spectrometer calibration test was improved, the dynamic range was improved by 2.8 times, and the extended uncertainty could reach 4.60%. Compared with the results of direct calibration, the signal-to-noise ratio of solar imaging spectrometer calibration test was significantly improved, which met the requirements of radiance response calibration of solar imaging spectrometer.

Aiming at the demand of small delay measurement of photoelastic modulator (PEM) in high-precision optical rotation detection, a high frequency and small delay PEM scheme for optical rotation detection was proposed. COMSOL (COMSOL multiphysics) finite element simulation was used to simulate the vibration mode analysis and size determination of a 120 kHz PEM in standing wave mode, and to design and process high-frequency small-delay PEM samples. It was verified by experiments, and the amplitudes of one to four octave signals were extracted by field programmable gate array (FPGA) as the main research object, which realized the automatic calculation of small-delay PEM phase delay amplitude and the measurement of rotation angle. The experimental results show that the PEM frequency of the measuring system is 120.32 kHz, the average phase delay amplitude is 0.11 rad, and the repeatability is 0.000 7. The amplitude of phase delay is 2.9 times smaller than that of traditional single PEM, which has great practical significance for weak and high-precision optical rotation detection.

The photoresponse non-uniformity of electron bombardment active pixel sensor (EBAPS) refers to the phenomenon that when the photocathode in the EBAPS device is illuminated by a uniform light source, the output grayscale of different pixels is inconsistent. Especially in low-light environments, the image non-uniformity makes it difficult to identify details, affecting the accuracy of subsequent image processing and analysis. Its generation mechanism is mainly caused by the difference in light response of different regions of the photocathode, the difference in electron multiplication characteristics of different regions of the electron-sensitive complementary metal-oxide-semiconductor (CMOS), the difference in response of each pixel to the same stimulus, and the difference in transmission channels in the readout circuit. Aiming at the non-uniformity problem in EBAPS, a test method based on the coordinated adaptation of EBAPS photocathode response, electron multiplication and pixel response non-uniformity was proposed. Experimental results show that this method can effectively evaluate the non-uniformity effect of EBAPS devices and can play a guiding role in device test screening and algorithm correction.

In complementary metal-oxide-semiconductor (CMOS) image sensors, forming a barrier with a Delta structure (delta-doping) on the surface can effectively resolve the issues of performance changes in traditional CMOS image sensors under irradiation environment. The width and height parameters of the barrier directly affect the dark current on the surface of the CMOS image sensor as well as the efficiency of surface signal detection. It was assumed that the total energy of electrons and the cross-sectional direction of tunneling satisfied the Schrodinger equation, calculating the probability of tunneling and the relationship between the tunneling height and width, and resulting in the conclusion that the minimum width of the Delta-doped barrier should be above 1 nm, thereby designing the doping structure and doping concentration. It was discussed that CMOS with Delta doping had the feature of high-efficient, stable, and uniform quantum efficiency, which enhanced low-energy electron detection and contributed to low-light imaging and space exploration.

Existing image super-resolution networks are mostly designed for visible light images, with relatively fewer studies focusing on infrared image super-resolution, and most of them simply adopt methods from visible light image super-resolution. In response to the low resolution and blurred edges of infrared images, a gradient-guided infrared image super-resolution reconstruction network was proposed. The gradient information in low-resolution infrared images was fully utilized by the network, fusing the gradient map with the extracted features, thereby resulting in a high-resolution image with clearer edges and higher contrast. The experimental results of the comparative and ablation studies demonstrate that the proposed method outperforms other comparative methods in infrared image super-resolution reconstruction, generating high-resolution images of higher quality.

Luminous remote sensing images have been widely used in social and economic estimation, urban monitoring, ecological environment assessment and public health. Using luminous remote sensing to detect ground objects in low illumination conditions such as nighttime and twilight, it is complementary to traditional daytime remote sensing to form all-day earth observation capability. However, in low illumination environment, the image quality of remote sensing camera will decline sharply with the attenuation of camera light input, so how to improve the signal-to-noise ratio (SNR) of remote sensing image is the focus of luminous remote sensing. The SNR of a remote sensing camera developed in the early stage was analyzed and modeled in detail. The functional relationship between SNR, integration time and ground radiation brightness was given in the face array staring mode. When the integration time is greater than 2 ms, the SNR is better than 10 dB, and when the integration time is greater than 15 ms, the SNR is better than 20 dB. In strip imaging mode, the relation between SNR and line frequency and TDI series was given. The results show that when the TDI series is constant, the SNR decreases with the increase of line frequency, and when the line frequency is constant, the SNR increases with the increase of TDI series, but the speed of SNR increase gradually slows down with the increase of TDI series.

The current development status of electro-optical information equipment for unmanned aerial vehicles (UAVs) was deeply analyzed domestically and internationally, and the development trend in the future of UAVs electro-optical information equipment under new circumstances was studied and proposed. Building on this foundation, the demands of transformation and development of UAVs electro-optical information equipment were emphasized and discussed from the aspects of confrontation among major power systems, insights from modern warfare, and domestic industry consensus. Additionally, several recommendations were put forward regarding the transformation and development, encompassing system construction, equipment development, civil-military integration, and foundational innovation. Finally, the transformation and development of UAVs electro-optical information equipment was summarized, emphasizing the necessity of pursuing a path of innovative development.

To enhance the environmental perception and target recognition capabilities of unmanned aerial vehicles (UAVs) in complex environments, the exploration of UAVs-mounted day-and-night single-channel natural-sensing color thermal imaging technology was undertaken. Based on deep learning technology, two image colorization techniques were constructed: the TIVNet, an infrared image colorization network based on a multi-discriminator generative adversarial network, and the infrared image colorization network based on the semantic-guided diffusion model with regional self-segmentation RSDM. A generative adversarial network architecture with multi-discriminator was employed by TIVNet to directly convert infrared thermal images into colorized visible-light-like images. However, there were instances where color inaccuracies were observed in the detailed aspects of certain scenes. The more real color images through a more sophisticated model were generated by RSDM, enhancing the visual effect and efficiency of information transmission in images, but the processing speed of the current model needed to be improved. Experimental results indicate that the two proposed methods each possesses distinct advantages in terms of the fidelity of image conversion and real-time processing rate. TIVNet has achieved real-time processing at a rate of not less than 40 Hz on platforms such as UAVs, demonstrating the technical feasibility. Moreover, it possesses the capability to facilitate equipment transformation applications based on the specific application requirements, thereby providing a novel technological means for the application of UAVs in both military and civilian domains.

An extrinsic Fabry-Perot interferometer (EFPI) acoustic sensor based on a graphene membrane was proposed, combined with a cascade model of convolutional neural networks (CNN) and long short-term memory networks (LSTM), for the detection and identification of various types of small rotorcraft drones. Furthermore, a detailed analysis was conducted on the feature extraction, data acquisition device, and the number of sound source categories involved in the experimental process. Through experimental comparison, it was found that when the Mel frequency cepstral coefficient (MFCC) was used for feature extraction, the recognition effect was significantly better than that of the short-time Fourier transform (STFT) and Mel spectrogram features. Moreover, the accuracy rate of using this sensor for small rotary-wing drones detection and recognition is approximately 2% higher than that of an electrical microphone. In addition, the recognition accuracy of the sound sources of various types of small rotary-wing drones is above 95.33%, which proves that it can effectively detect and identify multiple types of drones.

The frequent illegal use of civilian low-altitude small unmanned aerial vehicles (UAV) poses a serious threat to the harmonious development of the country and society. In response to the problems of missed detection, false detection, and low detection accuracy in small target detection of UAV based on visible light, a YOLO-SCConv ATT (YOLO-SCAT) algorithm model was proposed to reconstruct the ELAN (efficient layer aggregation networks) structure and reduce redundant spatial and channel features. At the same time, the attention mechanism CBAM (convolutional block attention module) was introduced to enhance feature extraction in spatial and channel dimensions during training, thereby improving the average detection accuracy of the model. The experimental results show that the accuracy, recall, F1 score, mAP@0.5 and mAP@0.5:0.95 can reach 94.4%, 94.4%, 94.4%, 94.7% and 52.9%, respectively, which proves that the YOLO-SCAT model improves the detection and recognition ability of small targets in complex visible light scenes, and can better meet the practical needs of anti-drone systems.

As a new type of directed-energy weapon, high-energy laser (HEL) systems demonstrate significant advantages in counter-unmanned aerial vehicle (C-UAV) operations, including rapid response and high cost-effectiveness. Taking the small quadcopter as a typical research subject to conduct modeling, simulation, and quantitative analysis of HEL damage effects. Firstly, the research status of C-UAV technologies was systematically reviewed. Subsequently, a damage assessment model was established, incorporating key modules such as laser atmospheric transmission, irradiation response calculation, and damage degree evaluation. Through vulnerability analysis of UAV systems, critical damage components were identified, enabling the development of a thermo-mechanical coupled laser damage assessment model. Finally, numerical simulations were performed to evaluate damage effectiveness under various operational parameters. The simulation results demonstrate that the damage time exhibits strong correlations with both engagement distance and laser power density. Specifically, the damage time increases with reduced operational range and increased power density.

Single-photon lidar offers superior detection sensitivity, temporal resolution, and photon utilization compared to traditional linear lidar systems. It is increasingly important in fields such as remote sensing and mapping, military reconnaissance, and camouflage recognition. A domestically developed single-photon ranging system operating at the 1.5 μm wavelength was presented, in which a compact 1.5 μm fiber laser source with adaptive noise reduction and frequency modulation features was integrated to reduce system dark counts and eliminate range ambiguity. High-precision time-to-digital converters (TDC) were used to control system size, while the non-coaxial transceiver design ensured simple structure, easy adjustment and low noise. The single-photon ranging of 1.7 km was achieved with an optical power output of only 10 mW and a single pulse energy of 200 nJ. Experiments with multi-layer camouflage net-covered targets demonstrate the accurate target identification through the camouflage, with a detection precision better than 0.1 m. The results indicate that the domestically developed system performs well, showing significant advantages in power consumption, size, and weight, and is expected to paly an important role in many fields in the future.

The fiber Bragg grating sensor has a broad application prospect, and the main obstacle limiting its practical application is the high speed and high precision demodulation of the sensing signal. A matching grating filtering demodulation method and system were introduced. The reflectance matching filtering demodulation method was numerically simulated, and the strain transfer model was improved to establish a three-layer model of fiber-adhensive-piezoelectric stack. The specific parameters of fiber Bragg grating bonding on the piezoelectric stack were determined by simulation. Finally, the matching demodulation system was constructed. The method of expanding the demodulation range by bonding multiple fiber Bragg gratings on the piezoelectric stack was explored, and the center wavelength demodulation of fiber Bragg grating was realized by Hilbert transform peak-finding algorithm. The demodulation range of the system is 1 540.121 nm~1 541.474 nm, the maximum deviation is 8.6 pm, and the mean fluctuation is 5.4 pm, whose demodulation range, precision and stability are good, which can meet the wavelength demodulation requirements in specific applications. The demodulation system has certain reference significance and practical values.

Phase generated carrier (PGC) technology is the core technology of multi-wavelength fiber displacement sensor (MWFDS). A square-wave phase modulation and demodulation (SWPMD) method was proposed. The corresponding optical system was established for research purposes, which precisely controlled the phase modulation of multi-wavelength beams using square-wave signals. Digital processing was applied to the collected interference signals to achieve phase demodulation, thereby reconstructing the displacement information. The simulation experiment systematically analyzed the impact of modulation signals with different frequencies and changes in the initial phase of square-wave modulation signals on the accuracy of displacement reconstruction. The root-mean-square error (RMSE) of displacement reconstruction remained stable within the range of 0.15 μm to 0.3 μm regardless of the modulation parameters. By applying the SWPMD method to reproduce complex displacement trajectories, the universality and effectiveness of the SWPMD method in improving the performance of MWFDS were demonstrated. Finally, the reproduction of square wave displacement with different step sizes was calculated and analyzed, proving that the proposed method could theoretically achieve a resolution of 0.1 nm displacement measurement.