This PDF file contains the front matter associated with SPIE Proceedings Volume 13398, including the Title Page, Copyright information, Table of Contents, and Conference Committee information.

Photo-responsive materials have attracted widespread attention for their potential advantages in resource conservation and sustainable use. Among the various photo-responsive molecules, azobenzene groups exhibit unique photoconductive cis-trans isomerization responsiveness and find extensive applications in the field of photo-controlled smart materials. This paper presents the preparation of a photo-responsive polyurethane material (denoted as PBHC6AB-U) incorporating azobenzene groups into its main chain. PBHC6AB-U exhibits outstanding photo-response performance, boasting a photo isomerization efficiency of 71.7%, and can achieve 20 cycles of the write-erase process under alternating UV and visible light irradiation. Moreover, by incorporating this material into A4 paper, one can prepare a photo-responsive erasable paper with a hydrophobic water contact angle of 110°, capable of multiple cycles of use. It possesses excellent photochromic and waterproof properties, showcasing a promising application prospect in the field of optical information storage.

With the rapid advancement of new-generation information technologies such as 5G, cloud computing, and artificial intelligence (AI), data centers, serving as the operational platforms for information systems, have seen a continuous rise in energy consumption, currently reaching 30kW per rack. The necessity to reduce power consumption in data centers cannot be overstated. Optical modules in data centers, serving as the bridge for information exchange, account for over 40% of the total power consumption of switches. Low-power optical modules have become a hot topic in the industry. To reduce the energy consumption of optical modules, various low-power solutions have been proposed, such as Co-Packaged optics, linear drive pluggable optics (LPO) without digital signal processing (DSP), and linear receive optics (LRO) with half-DSP, but their performance ultimately depends on high-speed, low-power driver chips. This paper uses simulations and experiments to develop a 4×13Gbps multi-channel ultra-low-power linear drive optical transmitter based on the current bias circuit, which can achieve an extinction ratio ranging from 2.3 to 7.3 dB, an eye height of 196 μW, and an eye width of 43.1 ps when operated at a modulation voltage of 500 to 1100 mV. The power consumption is reduced to 1.08 mW/Gbps. Compared to traditional optical modules, this solution reduces energy consumption by about 80% and costs by 30%. Additionally, experimental results have demonstrated that the key elements in the design of a multi-channel linear direct-drive optical transmitter based on the bias circuit also include: 1) the use of a sink current source to supply power in a manner that effectively prevents signal reflection; 2) traditional multi-channel current source chips cannot achieve effective channel isolation, and passive filters need to be added for channel isolation to reduce high frequency signal interference between channels; 3) Since the re-timer has been eliminated, it's necessary to rigorously optimize the link impedance and minimize signal reflection. This solution integrates the advantages of both low cost and low power, making it applicable in short-distance interconnection scenarios such as those between data center internal racks and backplanes.

In this article, we propose a polymer tilted fiber grating (POTFBG) based on polymethyl methacrylate (PMMA) and study its temperature and strain sensing characteristics. Compared to traditional tilted fiber Bragg gratings, this grating exhibits superior temperature and strain sensitivity, along with excellent linearity, significantly enhancing the sensing performance of fiber Bragg gratings. Due to the material properties of PMMA, the observed peak shifts towards shorter wavelengths as the temperature increases. The data indicate that within the temperature range of 10-60°C, its sensitivity can reach -155.8 pm/°C, which is over ten times that of traditional silica single-mode tilted fiber Bragg gratings. The grating is simple to fabricate, highly sensitive, and holds great potential for development as a sensor.

Differential Absorption Lidar (DIAL) serves as a pivotal technique for profiling atmospheric CO2 concentrations, yet its efficacy is hampered by the presence of noise. Traditional denoising methods, such as Empirical Mode Decomposition (EMD) and its variant (EEMD), have been employed to mitigate this issue. However, these methods are not underpinned by a robust mathematical framework and are prone to the phenomenon of mode mixing, which can compromise the quality of signal decomposition. In this research, we present a novel denoising method for Differential Absorption Lidar (DIAL) signals, employing Successive Variational Mode Decomposition (SVMD) integrated with Pearson correlation coefficients. The algorithm initiates by decomposing the echo signal into a multitude of intrinsic mode functions (IMFs) through the SVMD process. Subsequently, Pearson correlation coefficients are utilized to quantitatively assess the degree of similarity between each IMF and the original signal. Only those IMFs that meet a pre-defined threshold of similarity are integrated back into the reconstruction process, yielding a refined, denoised signal. The efficacy of our proposed denoising methodology is substantiated through a comparative analysis with simulated DIAL echo signals. The results highlight the algorithm's ability to effectively reduce noise in echo signals, thereby improving the precision and effective range of CO2 concentration profile retrievals.

In this paper, we studied the transmission characteristics of a Bessel Gaussian beam (BG) carrying a rotational asymmetric power-index phase vortex (PEPV-BG), and explored its propagation characteristics in free space through theoretical analysis and numerical simulation. The numerical simulation results show that by modulating the topological charge(TCs) and power index(PIs) of the PEPV-BG beam, the intensity and phase of the beam are redistributed. This type of intensity distribution based on changes in the topological charge and PIs has applicable in particle capture, light capture, and biopharmaceutical sectors.

Pound-Drever-Hall (PDH) locking is a magnificent technique in modern optics, particularly in optics and precision measurements. In laser frequency stabilization experimental realization, PDH locking parameters are to be carefully chosen for optimal locking performance. This presented work provides a simulation result of the effects of two key parameters in PDH stabilization: modulation frequency and modulation depth. In the simulation, by varying the value of modulation frequency and modulation depth, their impact on the error signal is visualized. This study shows that in the low modulation frequency regime, the higher the modulation frequency, the greater the value of the error signal and the wider the free spectral range it occupies. In the high modulation frequency regime, with a higher modulation frequency, the error signal spans a wider free spectral range. By incrementally increasing the modulation frequency, a periodic pattern emerges with a period of roughly 500 linewidths. This periodicity corresponds to the cavity's free spectral range. Additionally, the error signal's magnitude varies with modulation depth, peaking when the depth reaches approximately 1.08198 radians before declining. These observations illuminate the intricate relationships between modulation parameters and system response in PDH locking. Understanding these dependencies is crucial for optimizing PDH systems across research and industrial applications, enabling enhanced performance in areas such as precision spectroscopy, interferometry, and laser frequency stabilization.

Tunable Diode Laser Absorption Spectroscopy (TDLAS) has revolutionized the field of trace gas detection. Its excellent sensitivity, high resolution, and fast response capability make it applicable to multi-component and multi-parameter measurements. Moreover, it has broad prospects in the field of gas detection. Because of the close relationship between CH4 and CO2 concentrations and seismic activities, accurate monitoring of these two gases' spatial and temporal distribution is of far-reaching significance for earthquake early warning. In this paper, we design a digital modulation and demodulation TDLAS-based dual-gas concentration measurement system to measure CH4 and CO2 gas concentrations simultaneously. Through the design of a single detector with dual light sources, we not only enhance the integration of the system but also eliminate the noise interference caused by the traditional digital phase-locked amplification circuit at the software level, which further improves the accuracy of the TDLAS technology in gas detection and reduces the size and power consumption of the system, which makes it easier for subsequent maintenance and operation. It further improves the accuracy of TDLAS technology in gas detection, reduces the system size and power consumption, and provides a lot of convenience for the subsequent maintenance and optimization work.

The topological charge of the vortex beam is directly related to beam size, transmission robustness, and influence degree of turbulence. Moreover, it plays an important role in measuring the target’s rotation speed of the rotational Doppler effect. To effectively address this issue, in this work, coherent synthesized vortex beams with different topological charges were produced by using a laser array. A systematic experimental study on the coherent synthesized vortex beam under different rotation speeds in the context of off-axis incidence was carried out. From the acquired research results, important experimental verification to the measurement of the target’s rotation speed due to the rotational Doppler effect can be provided. This outcome further confirms the impact of the topological charge on the measurement accuracy.

Tunable optical filters show excellent performance in integrated optics. Present schemes for tunable filter either have a large footprint or suffer from mediocre performance, hindering the development of integrated optics systems. Here, a tunable guided-mode resonant grating filter is elaborately designed through a precise, modified coupling mode theory. This structure consists of a silver metallic grating and a multilayer waveguide. The grating period of the grating layer is arranged in a gradient descent configuration. The diffraction effects produced by the grating structure, when coupled with the guided modes in the underlying multilayer waveguide, result in guided-mode resonance, thereby achieving band-pass filtering. We employ Sb2Se3, a phase-change material, as the dielectric layer in the multilayer waveguide structure. By controlling the temperature, Sb2Se3 can transition between amorphous and crystalline states, enabling switching between two operational bands. Simulation results demonstrate that the transition between the amorphous and crystalline states of Sb2Se3 allows for switching of the filtering range from 1262.5-1269.5 nm to 1544-1552 nm. We analyzed the electric field energy distribution and the quality factor (Q) of the resonance peaks to verify and understand the device's performance. Our design offers a novel approach to achieving tunable filtering in the near-infrared band, with potential applications in signal processing, wireless communication, and the medical field.

The laser beam-expanding lens can improve the beam collimation by reducing the spatial divergence angles of the laser beam, and is widely used in the laser range finder of spaceborne. An aspheric laser beam-expanding lens of spaceborne is designed as a transmission-type lens, and the wavefront error RMS and magnification of the optical system is be requested high-precision in vacuum environment. The assembly and adjustment precision of traditional centering methods cannot achieve the exacting requirements of design. This paper proposes an innovative high-precision assembly and adjustment method for laser beam-expanding lenses. The sensitivity factors of assembly and adjustment are controlled step by step. Base on decentration measurement technology and the interference detection technology corrects system aberration in atmospheric environment, and interferometer power technology ensures system magnification in vacuum environment. The results of test confirm that wavefront error RMS of the lens is 0.015λ@1064nm, and the magnification is 9.98 in vacuum environment, satisfying the stringent design specifications. This approach offers a novel and effective solution for high-precision assembly and adjustment of transmission-type optical systems.

An on-line correction method for dynamic ampacity parameters of submarine cables based on optical fiber temperature measurement is proposed. First, through sensitivity analysis, find the material parameters that have a greater impact on the calculation of the current carrying capacity of IEC60853. Then, in the submarine cable real-time monitoring system, current data that meets certain characteristics and corresponding fiber temperature measurement data are extracted, and the conductor temperature is calculated by the thermal circuit method. Compared with the conductor temperature calculated by IEC60853, particle swarm optimization algorithm is used to modify the material parameters online, so as to reduce the error of IEC60853 in calculating the dynamic current carrying capacity. Finally, a 220KV three-core photovoltaic composite submarine cable from an offshore wind farm in Yancheng is taken as an example to verify the effectiveness of the method.

Multi component gas detection in goaf can be used to determine the oxidation and spontaneous combustion status of residual coal in goaf, and to determine the development trend of spontaneous combustion of residual coal in goaf. TDLAS gas detection technology is becoming increasingly widely used due to its narrow spectral lines, which can effectively avoid cross interference. The study adopts a structure where multiple lasers share an absorption cell to construct a laser multicomponent gas detection device, which greatly reduces the overall cost of the detection device, improves integration, and reduces the size of the detection device. Through the research of multi-component gas TDLAS detection technology, the structure and hardware circuit of the detection device were designed. The developed multi-component gas detection device was used to test the detection range, detection error, and response time of six indicator gases including methane, oxygen, carbon dioxide, carbon monoxide, ethylene, and acetylene. The testing verified that the multi-component gas detection device can accurately detect each indicator gas, and the detection range, detection error, and response time meet the standard requirements.

The market for house robots is booming, fueled by advancements in visual sensing, particularly LiDAR technology. Solidstate LiDAR excels in precise, low-cost imaging, suitable for integration. This article aims to review the principles, strengths and weaknesses of three types of solid-state LiDAR – flash LiDAR, MEMS LiDAR and PA LiDAR. As technology evolves, solid-state LiDAR finds wider use in service and industry. Service robots emphasize safety and flexibility, while industrial robots prioritize robustness and power. Recent innovations focus on enhancing FOV, reducing power and errors, pointing to a future of compact, hybrid, innovative, and cost-effective solid-state LiDAR systems.

The current smart grid technology is developing rapidly, the construction of extra high voltage grid is steadily advancing, and the level and complexity of modern grid automation is increasing. Optical fibre communication, as an emerging communication method, has a strong anti-interference ability, and the signal loss is very small in the process of long-distance data transmission. At the same time, optical fibre communication has the feature of large channel capacity, which can well achieve the instantaneous transmission of large amounts of data. This study for the distribution network of optical fiber resources are relatively tight, as well as fiber-optic sensors are based on the main network of large-scale equipment development, there is no small number of compact fiber-optic sensors for the distribution network, mainly to solve the degree of intelligence of the distribution network is not high, subject to cost and network constraints, the main network intelligent technology can not be copied and moved down the network, the need to study and build a sensing network adapted to the characteristics of the distribution network and the low-priced and efficient sensors, to achieve effective access to the distribution network intelligence. It is necessary to research and build a sensing network and low-cost and efficient sensors adapted to the characteristics of the distribution network, so as to realise the effective accessibility of distribution network intelligence. Therefore, this paper proposes the study of key technology of optical fibre integrated sensing for distribution grid, and the test results show that through the establishment of sensing network and low-cost and high-efficiency sensor system, it can realize the comprehensive monitoring and fault diagnosis of distribution network, find and repair the faults in time, and improve the reliability and safety of distribution network.

This research applies the IPCC energy consumption method to calculate the energy consumption carbon emissions in various cities in Shaanxi Province from 2013 to 2021. Regression models between NPP-VIIRS nighttime light data and energy consumption carbon emissions are constructed, and grid scale spatiotemporal distribution maps of energy consumption carbon emissions in Shaanxi Province are generated. Based on the Logarithmic Mean Divisia Index (LMDI) method, the driving effects of energy structure, energy intensity, economic development and population size on carbon emissions are studied. The research results of the article are as follows: (1) From 2013 to 2021, the energy consumption carbon emissions in Shaanxi Province showed an increasing trend, and there were significant differences in carbon emissions among different cities. (2) The main urban areas of most cities gradually expanded in size and their carbon emissions increased from 2013 to 2021. The Xixian New Area has been significantly expanding since 2017. Carbon emissions in some areas of Yulin and Yan'an have been decreasing since 2018. (3) Economic development and population size are positive factors driving the growth of carbon emissions in Shaanxi Province. The contribution of economic development to carbon emissions is much greater than that of population size. Overall, energy structure and intensity have a suppressive effect on carbon emissions. The research results can provide reference and inform policy decisions related to low-carbon development in Shaanxi Province.

In Dense Wavelength Division Multiplexing (DWDM) optical communication networks, the Optical Performance Monitor (OPM) can monitor key indicators for instance optical power, central wavelength, bandwidth, and optical signal-to-noise ratio in real-time. However, traditional OPM modules face the challenges like low accuracy, high cost, and unavoidable physical impacts. This paper proposes using the Back Propagation Neural Network (BPNN) algorithm to improve optical performance monitoring accuracy by reconstructing spectrum graphs to calculate optical power. Using simulated spectrum graphs as the dataset, the model is trained and validated with 0 dBm signals and evaluated with 5, 10, 15, and 20 dBm signals. Results show that the BPNN algorithm outperforms traditional OPM algorithm in reconstructing spectrum graph, improving optical power calculation accuracy and simplifying computational steps. With BPNN algorithm, the Mean Square Error (MSE) of the reconstructed spectrum is approximately 0.0011. This method not only enhances monitoring accuracy but also reduces errors in the OPM module. Although the training complexity increases, the prediction complexity has been decreased. Future research could optimize the structure and parameters of the BPNN model to improve its performance and explore its applicability in other optical communication systems.

With the trend of digital transformation of factories, industrial PON is applied more and more widely, in order to meet the more stringent delay requirements of PON network systems in industrial PON scenarios. Based on the analysis of the existing delay of the PON system, this paper finds that there is an optimization space and proposes an optimization scheme to reduce the delay in the PON system, and makes sufficient delay measurement experiments for the optimization scheme. The resulting average delay can be reduced to less than 30us, and the maximum delay can be reduced to 80us.

We researched and optimized the output characteristics of the pulse seed laser and the pre-amplifier. Based on acoustooptic external modulation technology, the effects of forward, backward, and bidirectional pumping modes on the output power and Amplified Spontaneous Emission(ASE) suppression of the pre-amplifier stage are studied. Using optimum fiber lengths of 3.0 m and 1.5 m in seed laser and pre-amplifier, the maximum laser output power of 1.41 W and the slope efficiency of ~16.3% operated at 1908.06 nm are achieved at a repetition rate of 1 MHz and a duty cycle of 80%, respectively. The ASE suppression ratio of 40.0 dB with the input pumping power of 10.88 W is achieved. In the pre-amplifier laser, no self-oscillation or nonlinear effects were observed, indicating that the incorporation of the pre-amplification structure can effectively suppress ASE. The dependence of the amplifier performances on optimum fiber length are also discussed in this paper.

The FBG have many advantages such as small size, light weight, simple structure, stable performance, and mature production technology, and has been widely used in fields such as construction, engineering, aerospace, etc. This article uses vacuum dispensing technology (VDT) to encapsulate different types of colloidal materials in the grid region of FBG. The thermal expansion coefficient and refractive index of different types of colloids are different, so the temperature sensitivity of the packaged FBG grating varies. Through experiments, it was found that when the grating region of FBG fiber grating is encapsulated with SD414, the sensitivity of FBG reaches 0.910nm/℃ in the temperature range of - 60 ℃~+60 ℃, which is 26.1% higher than before the grating region encapsulation.

The fabrication of subwavelength two-dimensional (2D) structures on the surface of bulk materials holds immense importance in the field of nanophotonics. We present a novel one-step technique for fabricating 2D-microbump structures on semiconductor 4H-SiC surface, utilizing three femtosecond laser beams with temporally delayed pulses. Various surface structures, including one-dimensional (1D) ripple structures, 2D composite ripple structures, and 2D square/rhombus-microbump structures, were uniformly distributed across the laser-irradiated areas, which were conspicuously characterized by their low spatial frequency. The fabrication of the 2D structure can be controlled by adjusting the delay time among the three laser beams, and a physical scenario utilizing surface plasmon polariton is proposed to elucidate the underlying mechanisms.

Based on the Pancharatnam-Berry phase principle, metalens permits precise phase manipulation through spatial-variant micro/nano-structures. In this study, a bifocal metalens incorporating spatial-variant subwavelength silicon(Si) gratings is introduced for an incident wavelength of 1550 nm with orthogonally circular polarization. The metalens is segmented into two interleaved sub-apertures for right-handed circularly polarized(RCP) and left-handed circularly polarized(LCP) lights, respectively. For incident RCP light, the proposed bifocal metalens attains a focal length of 100 μm, which can be adjusted to 200 μm through polarization state switching to LCP. Furthermore, with inverse designed diaphragms and holographic optical element, a Fourier transform optical interference lithography system is utilized to generate multiple interference light beams simultaneously and fabricate targeted spatial-variant micro/nano-gratings in the photoresist film, which is promising for the production of the Pancharatnam-Berry phase metalens based on spatial-variant nanogratings.

The core objective of dual-energy CT is to accurately reconstruct the effective atomic number and electron density of materials, enabling precise material identification. This paper analyzes the impact of X-ray energy spectrum deviation on the precision of dual-energy decomposition, utilizing a dual-energy decomposition algorithm and numerical simulation experiments. Experimental data were collected using security inspection CT equipment. An energy spectrum correction method, based on CT image reprojection technology, was applied to correct the energy spectrum deviation. This approach facilitates accurate dual-energy reconstruction and material identification.

In recent years, colloidal semiconductor nanocrystals and quantum nanostructures of various sizes and shapes have emerged as excellent solution-processable luminescent materials for display applications. Using multi-dimensional nanostructures instead of spherical nanocrystals can produce linearly or circularly polarized light with superior color purity and brightness. This substitution greatly enhances the performance and efficiency of future display technologies. Perovskite nanorods, as novel display materials, have garnered significant attention, especially in polarized optics, showing great potential. This study proposes a simple post-treatment method to fabricate long CsPbBr₃ perovskite nanorods by post-treating CsPbBr₃ nanocrystals with a PbBr₂ solution. This treatment significantly improved the aspect ratio of the nanorods (NRs), increasing the anisotropy value from 0.04 to 0.18. Additionally, the surface defects of the treated nanorods were reduced, and the PLQY increased from 37.6% to a maximum of 49.3%, with a marked improvement in stability.

A reflective frequency selective absorber (RFSA) using computational pixelated structure is proposed. The RFSA consists of a high-impedance ITO conductive film covered with a polyethylene terephthalate (PET) dielectric layer and a resonant cavity. The resonant cavity is a three-layer structure with a metal pattern and a fully reflective metal film on and at the back of a PET dielectric layer, respectively, which produces an in-phase total reflection. The metal pattern is formed by pixelated and binary square with a value of 1 or 0 to indicate whether it is metallized. Coherent perfect absorption (CPA) can thus be achieved by the in-phase total reflection from the resonant cavity combined with the high-impedance ITO film. A reflection coefficient lower than -10 dB from 11 to 13 GHz and greater than -1 dB from 14.6 to 16.3 GHz with a minimum insertion loss of -0.45 dB at 15.5 GHz is achieved based on computational pixelated metasurface and CPA. Moreover, based on the same thickness of the layered structure, tunability of the absorption bands and reflective notch is achieved by changing only the dimension and arrangement of the pixels based on simulated annealing algorithm and CST Microwave Studio for fully automated inverse topology optimization. The proposed method provides a flexible and convenient way to realize frequency selective absorbers which is of great significance in manipulation of electromagnetic radiation, microwave detection and shielding.

With the continuous development of the semiconductor industry, advanced chip manufacturing technology has reached the node of 5 nm and below, and wafer defects will inevitably occur in the manufacturing process. These tiny defects will lead to chip failure and significantly affect product yield. Semiconductor wafer manufacturing involves multiple stages, each of which introduces surface defects that affect the quality of lithography and cause device characteristics to fail. Therefore, it is very important to detect the surface defects of bare wafers. In this paper, a high-precision detection method based on quadriwave lateral shear interferometry (QLSI) is proposed, which can detect nanoscale height changes with high sensitivity and provide wafer surface topology measurement. The non-contact technology avoids the damage caused by probe contact, realizes efficient and real-time detection, reduces production costs and improves product quality.

As a widely used display terminal, the uniformity of Light-emitting Diode(LED) display screen brightness has a significant impact on its display effect. To improve the brightness uniformity of LED display screens, the Charge-coupled Device(CCD) image method is often used. This method uses a CCD camera to obtain the display image of the LED display screen, obtains the LED brightness through the image, and obtains the correction coefficient from it. In practice, it is necessary to determine the coordinates of the light points in the image. To address this issue, the relationship between the position of the light points in the LED display and the coordinates in the image was analyzed, and a formula for calculating the brightness of the light points was derived. And an internal circuit of Field Programmable Gate Array(FPGA)for brightness correction was designed. Through experiments, the non-uniformity of LED display screens has been reduced from 6.506 to 2.923. The results show that this method is efficient, time-saving, and can significantly improve the brightness uniformity of LED display screens.

This study introduces a novel photonic crystal fiber (PCF) refractive index-temperature (RI-T) sensor. It has an innovative three-core structure that forms three channels to achieve high sensitivity and accurate measurement of three parameters simultaneously. The independence of the three-channel sensing is experimentally verified.Simulation outcomes indicate that the dual-channel RI sensing achieves maximum detection ranges of 1.32-1.41 and 1.35-1.44, with a maximum wavelength sensitivity (WS) is 28300 RIU^-1. The maximum amplitude sensitivity (AS) is 15500 RIU^-1. Regarding temperature sensing, the sensor can detect 0°C- 90°C, the max WS is 7.8 nm/°C. In conclusion, the proposed PCF-SPR sensor can achieve precise measurements of solution concentration and environmental temperature.

This paper proposes a self-reference SPR sensor with high performance based on metallic rectangular nano-hole array and a four-layer stacked LID - HID (Low Index Dielectrics and High Index Dielectrics) dielectric structure, which is useful to improve the stability of the sensor against the environmental factors. The surface plasmon (SP) mode arising from the metallic rectangular nano-hole array is served as sensing mode and is sensitive to the RI of the analyte. The guided mode resonance (GMR) excited in the stacked dielectric structure is served as a self-reference mode and is not sensitive to the analyte. After optimization with FDTD method, the results of the experiment showed that the proposed sensor can achieve a FOM of 320 RIU^-1 and the sensitivity of 800 nm/ RIU for the sensing mode, and a quality factor of 7368 for the self-reference mode. The stability of the sensor has reached 1600, which has better performance than the previous self-reference SPR sensors, and has potential applications in high-precision biochemical sensing, high-Q filtering, and advanced photonic devices.

A Fourier transform spectrometer (FTS) chip based on silicon-polymer hybrid waveguide is proposed. The silicon-polymer hybrid waveguide consists of a silicon slot waveguide filled with an electro-optic (EO) polymer. The EO coefficient of employed EO polymer can be as large as 359 pm/V, resulting in a π-voltage-length product of less than 0.1 V·mm for our designed FTS chip which features a high resolution of 2.2 nm with a compact size of less than 0.5 mm².

Smart lighting fixtures using Pulse Width Modulation (PWM) control can emit different colors of light by adjusting the duty cycles of different LED channels. The traditional Grassmann theorem is limited to calculating the duty cycles for up to three LED channels and fails to account for the nonlinear variations in the photometric and electrical parameters of LEDs, leading to high Standard Deviation of Color Matching (SDCM) in mixed color output. This work develops a comprehensive method for calculating the duty cycles for color mixing, which, given the basic photometric and electrical parameters of LEDs, can directly calculate the duty cycles for achieving target colors with three or more LED channels. The results of color mixing for Red-Green-Blue (RGB) LEDs and Red-Green-Blue-White (RGBW) LEDs with SDCM < 6 demonstrate the feasibility of this method. This approach is effective for mass production of low color tolerance lighting fixtures.

A machine vision detection method based on YOLO algorithm is provided in this paper for automatic defect identification of titanium alloys. Firstly, an optical detection system was designed, which mainly consists of an industrial camera with experimental bracket and PC. High-resolution images of the surface information of titanium alloy samples were obtained by the system above. Then, a high-quality data set of titanium alloy surface defects was constructed to ensure the training effect and generalization ability of the detection system. Finally, the YOLOv5 object detection algorithm was used for automatic defect identification of titanium alloy.

In orthogonal time-frequency-space (OTFS) systems, when peak average power ratio (PAPR) is suppressed through companding operation, errors in the signal probability density function design cause noise in the companding processes, increasing the loss power in both processes. The signal amplitude is reconstructed in this study by converting the probability density function of the original signal into a probability distribution function with a finite distribution. The algorithm uses the rotating factor to preprocess the signal, completes the reconstruction of the signal distribution through the global search method, and uses the average power conservation before and after companding operation as the criterion to determine the companding demarcation point. This is based on the principle of minimising the companding loss power, according to the difference of correlation of different grouping methods, and completes the signal compression and expansion processing. The analysis results show that the proposed algorithm can effectively suppress PAPR while ensuring the BER performance of the system.

Optical gas imaging technology is crucial for gas detection and environmental monitoring. However, traditional background update algorithms, such as the Gaussian Mixture Model (GMM), often fail in dynamic scenes due to their reliance on image gray values and inability to handle moving objects like people and vehicles. This paper proposes an innovative approach that integrates semantic recognition models, such as YOLO-World, with traditional GMM methods to enhance background update processes. By employing infrared gas-detecting optical devices, the system mitigates background temperature variations and enhances gas image contrast. The YOLO-World model identifies and isolates moving objects, while optical flow techniques track their movement, allowing for rapid background replacement and reducing false alarms. Two outdoor experiments demonstrate the effectiveness of this approach: one involving methane release with human movement and another with both vehicles and humans in motion. The results show significant improvements in detection accuracy and reliability, paving the way for more efficient and robust gas leak detection systems in dynamic environments. This method not only reduces false alarm rates but also enhances the adaptability of gas detection systems to various real-world scenarios.

After completing the parameter calibration of the projector, the projector can be regarded as another camera and integrated with the binocular cameras to form a trinocular stereovision system. Unlike the traditional calibration method that relies on high-precision planar targets, this paper only requires a simple, unmarked white paper target to obtain the world coordinates of feature points provided by the binocular system. An improved bundle adjustment method is used for the global optimal estimation of the parameters of the projector and dual cameras. The calibration verification experimental results show that the proposed improved bundle adjustment method can optimize the parameters. Comparative experiments measuring standard planes demonstrate that the proposed method can improve measurement accuracy.

To monitor key parameters in agricultural ecosystems, laser speckle contrast imaging technology is utilized to analyze plant growth dynamics and soil moisture changes. Through quantitative speckle images, the micro-movements of plant leaves and their physiological activities, as well as changes in soil speckle intensity under different humidity levels, are revealed. The results show that this technology can accurately reflect micro-changes within the ecosystem, providing scientific support for ecological management and optimization decisions.

Aiming at the problem of high image noise in infrared heat wave detection, an image denoising method with improved partial differential equations (PDE) is proposed. Aiming at the limitations of the current partial differential equation model in removing image noise, the study analyzes its theoretical basis, and combined with the characteristics of the heat wave image, the existing partial differential equation mathematical model is targeted to improve. The improved PDE denoising method is compared with the classical P-M model and commonly used filtering methods, and the denoised thermograms are quantitatively evaluated using image quality evaluation indexes. The experimental results show that the proposed improved PDE algorithm can effectively enhance the denoising effect of the thermogram while retaining more damage edge feature information, and the image quality is better than the classical P-M model and commonly used filtering methods.

Spectral modulation polarization technology is a snapshot spectral polarization measurement technique without moving parts, offering high accuracy. Anhui Institute of Optics and Fine Mechanics has developed a prototype Ultraviolet-visible Imaging Spectropolarimeter. Prototype consists of a spectral modulation module, a telescope, and an Offner spectrometer, enabling dual-channel polarization imaging. The spectral modulation module uses Wollaston prisms for beam splitting, which has the disadvantage of asymmetric splitting angles, reducing the matching accuracy of the dual-channel polarized images. Therefore, it is necessary to analyze the imaging asymmetry caused by the prism wedge angle and determine the range for the wedge angle. To converge the dual-channel polarized beams after Wollaston prisms at the spectrometer slit, a telescope with F-number of 5 was designed. To verify the dual-channel imaging performance of the system, an overall analysis was conducted with the spectrometer, ensuring a modulation transfer function greater than 0.4 for each spectral and the specifications met the design requirements.

By capturing both the two-dimensional intensity and orientation information, the light-field camera is capable of generating depth information during the refocusing process. This technology holds great potential for applications in computational photography and computer vision. According to the imaging principle of microlens array light-field camera, this paper presents a design method for an light-field camera imaging system based on a metalens array. The method encompasses the overall design of the light-field camera imaging system as well as specific design considerations for the lens unit. Simulation and design results indicate that the optical system has the capability to achieve near-diffraction-limited imaging. The metalens units, which utilize the concentric nanorings structure, not only significantly reduce computational costs but also provide excellent achromatic imaging performance across the visible spectrum.

In this paper, ellipsometer combined with scanning electron microscope for solving the complex refractive index of nano film is proposed. Firstly, the interface of the nano film was measured using scanning electron microscope to obtain its thickness. Next, measure the parameters of the ellipsometer to establish the corresponding mathematical model and obtain the characteristic parameters of the thin film. Then, optimize the ellipsoidal mathematical model by comparing the film thickness obtained by scanning electron microscopy with that obtained by ellipsometry. Ultimately obtaining accurate film thickness and optical constants. The results show that the relative error of the calculation result of the optical properties is less than 1.0 nm and the measured values of optical constants are also consistent with the theoretical values. At the same time, the results derived from our method are in better agreement with the standard value, which shows that the measurement results are true and effective. Therefore, this method reveals the possibility of high-precision measurement of nano film through ellipsometer and scanning electron microscope, and makes it be a much better option to be employed for further micro-nano structures analysis applications.

The CARPE3D model significantly enhances the capability of three-dimensional parabolic equation propagation models to simulate complex marine environments, serving as a high-precision tool for three-dimensional ocean acoustic propagation. Despite its advanced performance, the model still has certain limitations. To address these issues, this paper proposes improvements to the classic CARPE3D model by utilizing higher-order three-dimensional parabolic equations and the split-step Fourier method for acoustic field calculations. The accuracy and precision of the improved model are validated through simulation and error analysis.

Laser-induced sound (LGS) technology is an effective method for achieving node-free communication from air to underwater environments. This paper introduces a frequency-shift keying (FSK) modulation method to enhance the stability of LGS communication. By controlling the time intervals between laser pulses to generate laser pulses with different repetition frequencies, sound signals are produced underwater based on the thermal expansion mechanism. At the receiving end, decoding is achieved by leveraging the energy differences in laser-induced sound signals of varying repetition frequencies. Experimental results demonstrate that the FSK modulation method provides superior communication performance. Compared to the traditional on-off keying (OOK) modulation method, FSK modulation effectively prevents decoding errors caused by interference between pulses, thereby enhancing the stability and reliability of communication.

The space-terrestrial integration network is undoubtedly the most significant engineering project today, while the space-terrestrial link is the bottleneck that constrain the network performance. The conventional methods of radio resource allocation of space-terrestrial link still play a dominant role, but improved approaches are needed to discover opportunities for enhancing the spectrum efficiency. Based on the analysis of future needs, a reinforcement learning assistance algorithm is proposed as an effective way to optimize the radio resource allocation of space-earth link. First, Markov decision process is constructed based on the characteristic of downlink resource allocation, then the resource allocation model is trained by using Q-learning. Simulation results show that the model could effectively enhance the spectrum efficiency.

Double-selective fading in multipath environments seriously affects the spectral efficiency and stability of communication systems. In high-speed mobile scenarios, traditional communication technology is difficult to cope with rapidly changing channel conditions, resulting in performance degradation. Orthogonal time-frequency space modulation (OTFS) is proposed to solve these challenges, but in ZP-MIMO-OTFS systems, the artificial setting of damping factors brings uncertainty, affecting system performance. Although the existing maximum ratio combined signal detection algorithm (MRC) has improved the performance, its effect is greatly affected by the selection of damping factor. Therefore, a GAMRC detection algorithm based on multi-objective genetic optimization algorithm is proposed in this paper. By optimizing the population evolution and elimination mechanism of the algorithm, the contingency and uncertainty of damping factor selection are reduced. The simulation results show that GA-MRC detection algorithm can provide better performance under different damping factors, which provides a reference for realizing the lowest bit error rate.

In cross-water-air medium communication using laser detection for signal reception, the detection signal is susceptible to external noise interference, leading to a degradation in communication quality. This paper proposes an anti-interference acoustic detection scheme for laser detection equipment. The scheme first transforms the traditional underwater MFSK (Multi Frequency Shift Keying) modulation method into M-LFM (Multi-Linear Frequency Modulated) modulation, encoding information into the slope information of the LFM signal. Subsequently, at the laser detection equipment signal reception end in the air, the received signal is preprocessed using optimal fractional Fourier transform to eliminate abnormal impulse noise and then inverse transformed into the time domain. Finally, the preprocessed signal is matched with the modulated baseband M-LFM signal to complete information demodulation. The simulation results show that the communication scheme in this paper can ensure the correct decoding of the signal under the external high-intensity and wide-band ambient noise interference, and at the same time, the effectiveness of the scheme is verified through the pool test, which confirms that it is able to enhance the quality of trans-water-air medium communication.

In the realm of wireless communications, where the escalating number of users and soaring data demands are prevalent, interference management (IA) has become increasingly crucial. Among the numerous challenges impeding the realization of IA techniques, the rapid time-variation of channels stands out as a predominant obstacle. Consequently, two IA algorithms tailored for non-ideal beamforming spatial channels are investigated in this article, under the framework of an IA system model incorporating lens antenna arrays, thus reflecting more realistic scenarios. In prior - literature, the rudimentary Least Squares (LS) method has been utilized for channel estimation, followed by the application of IA schemes to compute users' signal-to-interference-plus-noise ratio (SINR), outage probability, and throughput. Compared to ideal beamforming spatial channels, IA algorithms post channel estimation exhibits superior performance. Building upon preceding work, we employ both the Minimum Mean Square Error (MMSE) and linear MMSE (LMMSE) algorithms for channel estimation prior to interference cancellation. Through simulation comparisons, our proposed methodologies demonstrate enhanced performance in terms of outage probability and throughput.

With the development of technologies such as aerodynamics and wireless communication, UAVs(unmanned aerial vehicles) have continuously achieved breakthroughs in flight speed, and it has become feasible for UAVs to complete complex tasks through network collaboration. Reliable and high-precision relative distance measurement and positioning between nodes is an urgent need to achieve collaborative networking and high-precision strikes. In real battlefield environments, satellite navigation is prone to enemy interference. The ranging method based on satellite navigation cannot effectively solve the problems of high-speed and clock drift in the case of satellite navigation rejection. This article proposes a HSTSS(high-speed time-space synchronization) method based on data links, which utilizes the radio frequency Doppler effect in communication to estimate the motion speed, acceleration, and clock drift of nodes, and corrects and compensates the ranging results, solving the application problems of High-speed, high maneuverability, and relative ranging with clock drift. The simulation comparison results show that the HSTSS method proposed in this paper has significant advantages over traditional DOWR(dual one-way ranging) in terms of ranging accuracy, stability, and maximum error. In scenarios where the motion states of node machines are constantly changing, CHSTSS(complex highspeed time-space synchronization) methods perform better than SHSTSS(simple high-speed time-space synchronization) methods.

In communication networks, in order to obtain better bit error rate performance, it is necessary to use a suitable modulation format according to the link characteristics. Therefore, coherent receivers are faced with the need to receive signals in multiple modulation formats. Coherent optical communication systems can make full use of the amplitude, phase, polarization state, time and frequency of optical carriers for signal modulation. Digital signal processing is an important part of coherent receivers and the key to improving receiving sensitivity. In order to achieve multi-modulation reception, it is necessary to study digital signal processing solutions for multi-modulation signals. This article conducts theoretical and experimental research on the modulation, demodulation methods and digital signal processing algorithms of highspeed coherent optical communication systems. A parallelization scheme for multi-modulation format digital signal processing is proposed. The offline experimental verification results of the parallelized multi-modulation digital signal processing algorithm show that at the forward error correction (FEC) bit error rate threshold, the signal reception sensitivity is 2dB higher than that of the QPSK modulation format.

This paper proposes a dual-frequency miniaturized antenna for implantable medical devices. The proposed antenna has two frequency bands: the mid-field frequency band (1.4-1.6 GHz), and the industrial, scientific, and medical frequency band (ISM), respectively, for wireless power transmission (WPT) and data transmission or wireless monitoring. A compact dual-frequency transmission antenna based on optimal current distribution has been proposed as a transmitter to achieve wireless power and data transmission establishment. The simulation results show that within a distance of 50mm, the transmission coefficient can reach -27.8dB. Finally, human radiation safety has a lower specific absorption rate, indicating the potential of implants.

Timing synchronisation (TS) in ultra-long-range ocean communication scenarios is critical for orthogonal frequency division multiplexing (OFDM) systems, but multipath uncertainty in this scenario reduces the correctness of timing synchronisation. To mitigate the effect of multipath, this paper proposes a learning method based on extreme learning machine (ELM) for TS improvement algorithm. Aiming at the uncertainty of multipath, the improved algorithm improves the TS classical inter-correlation algorithm by taking M OFDM symbols without ISI region sampling point data block correlation operation to get the timing offset estimation; ELM further reduces the timing offset metric based on the correlation of the improved algorithm. Compared with the synchronisation algorithm and the ELM-based TS method, the ELM-based TS improved algorithm learning method has higher synchronisation accuracy.

In order to understand the positioning and anti-interference technology of high-frequency partial discharge in transformers, a multi terminal coupled sensing technology for high-frequency partial discharge positioning and anti-interference in transformers has been proposed. This paper compares and analyzes the on-site application effects of different detection technologies, discusses the principles, influencing factors, and development trends of partial discharge joint detection and positioning technology, analyzes the shortcomings of traditional "electrical acoustic" joint positioning methods, and proposes the detection principles, steps, effects, and application scope of "ultra-high frequency ultrasonic" and "ultra-high frequency optical" joint positioning methods. It points out new research directions for faster and more accurate positioning of partial discharge live detection in on-site power equipment in the future.

Wireless sensor networks have extensive applications in various domains, including environmental monitoring, military reconnaissance, intelligent transportation, and healthcare. To address the shortcomings of routing protocols, particularly those related to energy consumption, we propose an Energy-efficient Routing Protocol called SDBERP (Shared Neighbor Degree and Probability Assignment Based Density Peaks Clustering Algorithm). This protocol enhances clustering efficiency by streamlining some unnecessary steps through an improved SP-DPC algorithm. For selecting cluster centers, our protocol integrates decision-making factors such as the remaining energy of the nodes and their distance from the base station. Additionally, a two-step allocation method is employed for nodes that are not chosen as cluster centers. During the cluster head selection phase, the node's energy level, its distance from the base station, and its proximity to other nodes within the cluster are considered to identify the most suitable cluster head. Our proposed protocol uses proportional clustering, which helps maintain a stable number of clusters. The routing protocol was simulated using Python, and the experimental results demonstrate its effectiveness in significantly extending the network's lifespan and minimizing energy usage.

5G technology has been widely used in power systems due to its high speed, low latency, and wide connectivity. At the same time, the power wireless private network designed specifically for the power system provides solid support for the stable operation of the power grid with its high reliability, safety, and scalability. With the development of new power systems, the demand for power communication is growing rapidly. By combining the advantages of 5G and power grid, a public dedicated integrated communication terminal is designed to improve the efficiency and intelligence level of power grid communication, while ensuring business security and efficient operation. The application testing of the intelligent distribution station building scheme has verified the terminal's ability to handle massive data, high bandwidth communication, and data security. The electrical performance of the terminal fully meets the standards of the power industry and has broad application prospects in the field of power business adaptation.

Emergency Position Service (EPS) has important application value in the fields of public security and disaster relief in China. To promote the scale application of Emergency Position Service, this paper mainly reviewed the system architecture and security requirements of the location platform based on EPS, and studied the functional and performance test methods of the EPS platform. Based on the specific test results and practical application cases, the efficiency and reliability of the Emergency Position Service platform were analyzed, and suggestions for future optimization and improvement of EPS platform were put forward.

The technology of general data recording equipment is the key technology to solve the problem of high speed recording and mass storage of UAV data, and it is the key research direction in the field of UAV in China. Fully learn from home and abroad universal record equipment new concept, idea and design, we carry out the research of UAV common data recorder technology and design a reliable recorder. It can fill the gap of our UAV in this field, can adapt for future all kinds of UAV, can achieve large-capacity and high-speed storage, can achieve formatting records from unformatted data, can achieve the whole process signal protection throughout the entire process. The universal data recording device can play a key role in UAV flight test, solve the technical problem that the mission system data interface cannot be universal in UAV flight test, and provide powerful data support for scientific research flight test.

In this paper, an adaptive grid DOA estimation algorithm based on sparse Bayesian learning (LMSBL) is proposed. Compared with the traditional off-grid EM-SBL algorithm, the proposed algorithm overcomes the problem of insufficient estimation caused by excessive grid spacing, improves the estimation accuracy and shorens the program running time under the condition of low SNR. In this algorithm, the grid position is regarded as variable, and the fast factor maximization method is combined to estimate the grid position coarse by dichotomous method, and then fine-estimated by root-updating grid algorithm. Experimental results show that the proposed algorithm is more accurate and faster than the off-grid EM-SBL algorithm under the condition of low SNR and large grid spacing.

Hybrid precoding combines the advantages of analogue and digital techniques and has become the preferred precoding method for achieving a balance between high performance and cost-effectiveness in large-scale MIMO systems by simplifying hardware requirements and reducing energy consumption.In this study, a novel hybrid precoding method based on Joint Space Division Multiplexing (JSDM) and Successive Interference Cancellation (SIC) techniques is proposed for multi-user 3D MIMO systems.User grouping and statistical information based analogue pre-coding using JSDM is firstly used to form a suppression of major interferences, whereas SIC further optimises the digital pre-coded joint combining matrix to finely tune the data stream for each user by sequentially detecting and removing interference from the decoded signals. The experimental results show that the hybrid precoding scheme based on JSDM and SIC can significantly improve the spectral efficiency and BER performance in multi-user scenarios.

The grape industry in Liangshan, China, has experienced significant growth over the past decade. However, most grape-growing plots in Liangshan are mountainous and scattered, posing challenges for real-time communication using traditional IoT models, as noted by Gamperl et al. (2021). In the coming years, the integration of cloud computing and artificial intelligence (AI) within IoT architecture is expected to become a key area of research in smart agriculture. However, most studies to date have focused on plains with concentrated plots and have not addressed the challenges of implementing peer-to-peer communication in mountainous areas. This study addresses these challenges by transmitting real-time data to a cloud platform via a 4G-cat1 network, enabling real-time communication and data processing in hilly, dispersed agricultural plots. The study outlines the content: developing a theoretical foundation for using 4G-cat1 as the main data transmission method and deploying the necessary infrastructure for reliable connectivity; installing Data Transmission Units (DTUs) at representative locations within the plots to collect and transmit environmental data in real-time to a centralized cloud platform; and utilizing cloud computing and AI technologies to monitor and analyze the stability of data transmission, ensuring the stable operation of each unit. The main finding is that an IoT system utilizing distributed networks is highly effective for smart agriculture in mountainous areas, addressing the challenges of dispersed and non-contiguous agricultural plots.

Sparse Code Multiple Access (SCMA) is an efficient multiple access method that can significantly enhance spectrum utilization and user capacity. In this paper, a SCMA system is employed for the uplink scenario of satellite Internet of Things (IoT) to improve the access capability of IoT devices and meet the access requirements of future large-scale satellite IoT terminal devices. However, due to its multi-carrier nature, SCMA inherits high peak-to-average power ratio (PAPR), which poses a challenge for power amplifiers in the uplink communication scenario of satellite IoT. Therefore, we propose a low PAPR SCMA system for satellite IoT uplink communication and introduce a Linear Frequency Modulation (LFM)- assisted approach to reduce PAPR. Specifically, we compress the amplitude of points with high peak values in the time domain signal before launching the SCMA system and transmit their sequence numbers in parallel through LFM signals. At the receiver end, we recover amplitudes according to received sequence numbers using matched filters. The proposed system achieves effective PAPR reduction without significantly increasing the algorithm complexity and maintaining the BER performance.

Visible light positioning (VLP) technology has recently been considered as a high-precision solution for indoor positioning. In a practical VLP system, since the receiver terminal is usually not placed horizontally, the receiver orientation needs to be considered during positioning to achieve high positioning accuracy. The VLP based on received signal strength (RSS) can be considered as a non-convex optimization problem regarding receiver location and orientation. Although various metaheuristic algorithms were extensively adopted in VLP systems to solve the optimization problems, most of them are based on the ideal assumption that the user device is placed horizontally. In this paper, a recently proposed metaheuristic algorithm called sparrow search algorithm (SSA) is considered for indoor VLP systems because of its good performance in solving the optimization problems. Moreover, the original SSA algorithm is improved to solve the optimization problems more effectively. In the improved SSA algorithm, both global and local optimal values are combined to enhance the capability of escaping local optima. In addition, nonlinear weights are used during position updating. Moreover, Levy flight strategy is introduced to achieve higher positioning accuracy. Simulation results show that compared to the popular metaheuristic algorithm called grey wolf optimization (GWO), both the original SSA and the improved SSA algorithms can achieve higher positioning accuracy, and the proposed NWL-SSA algorithm performs best.

To address the challenge of adaptive fusion of asynchronous data in GNSS-5G integrated positioning, we propose an adaptive method for GNSS-5G integrated positioning based on active noise prediction. First, a GNSS-5G fusion scheme based on sequential filtering is introduced, taking full advantage of the high update rate of 5G observations to achieve “multirate” fusion at the observation level. Next, a distance-dependent noise model is derived to quantitatively characterize the impact of the distance between the base station and the user on the covariance of the observation noise. Based on this model, an active noise prediction algorithm is proposed to adaptively adjust the observation noise covariance matrix to match the actual observation noise. This noise prediction algorithm requires no prior knowledge of the system configuration parameters, making it highly flexible. To efficiently handle mixed LOS and NLOS environments, a multirate switching strategy is designed to adaptively switch from the proposed method to the standard low-rate EKF, thus achieving “multi-rate” fusion at the positioning mode level.