At present, no automatic observation instrument for atmospheric visibility is available according to visibility definition. To solve this problem, on the basis of the principle of artificial observation visibility and the effective use of CCD digital photography, this paper builds a digital photographic automatic observation system for visibility (DPVS) and develops a new type of automatic observation instrument for atmospheric visibility completely in accordance with visibility definition, which provides an effective solution for the observation of atmospheric visibility. The experimental results show that the system can precisely observe the atmospheric visibility, and the observation error of the proposed system compared to the transmission instrument is about 10% when the visibility is low and about 20% and the visibility is high. All the indices of the new automatic observation instrument meet the requirements of the World Meteorological Organization for the development standard of visibility meters.

The effect of the surface albedo on the sky polarization mode is studied. At present, there is a lack of research on quantitative tests with a single influencing factor at different time and locations in the actual environment. In view of this, the re-developed libRadtran software is used to simulate and analyze the sky polarization mode at different surface albedos. Then, synchronous remote tests are conducted in group on meadow and asphalt surfaces, ocean and asphalt surfaces with the imaging test system and the influence of surface albedo on the polarization azimuth and polarization degree is analyzed quantitatively. The results show that the surface albedo has little effect on the polarization azimuth distribution, which is always stable. However, it has a strong attenuating effect on the polarization degree. At the same time on the same day, a greater surface albedo entails a smaller maximum polarization degree; a bigger difference of surface albedo means a sharper average decrease and a larger decreasing extent in maximum polarization degree.

Single photon avalanche diode (SPAD) now plays an indispensable role in extremely low light detection. However, SPADs are often required possessing two response peaks under different lighting conditions, which cannot be realized in a single-wave-peak SPAD (SWP-SPAD). Moreover, the multiple SWP-SPADs responding to different wavelengths will reduce the integration of the detection system. In this work, we propose a double-wave-peak SPAD (DWP-SPAD) to detect both the visible light and the near infrared light. We conduct the device-level simulation by means of the technology of the computer-aided design, and build an external quenching circuit to measure key parameters. The test results show that the breakdown voltage of the SPAD is 12.75 V. Under experimental conditions of 22 ℃ and the excess bias voltage of 0.5 V, there are two peaks of the SPAD’s photon detection probability, 32% at 520 nm and 12% at 840 nm, respectively. When the over-bias voltage is 1 V, the dark count rate (DCR) is 1 kHz. Therefore, the proposed SPAD can achieve double-wave-peak detection at a low DCR.

In this paper, the signal processing method based on the total variation (TV) algorithm is used to eliminate time domain noise and improve the signal-to-noise ratio (SNR) in the phase-sensitive optical time domain reflection (φ-OTDR) system. Intensity and position information of the Rayleigh backscattering traces can be processed by converting the traces into a two-dimensional gray image. The TV algorithm can smooth the time domain noise and extract the useful information efficiently via the gradient descent method. Experimental results verify that on the sensing fiber with the length of 3.5 km, the TV algorithm can effectively realize the distributed measurement of 300 Hz vibration signal, and the SNR of the vibration position can realize 10.13 dB. In addition, we further verify the ability of the TV algorithm to detect wideband vibration signals, and successfully realize the wideband disturbance signal recognition in the frequency range of 300 Hz~1 kHz. It is shown that the TV algorithm can extract vibration information effectively in φ-OTDR system.

Polar codes belong to a coding scheme that is proved to reach the limit of channel capacity by strict mathematical methods. To apply polar codes to high-speed real-time optical communication systems, we adopt a fully-unrolled pipeline architecture in this paper. Based on Xilinx xcvu13p-flga2577-1-e field programmable gate array (FPGA) chips, we develop a successive cancellation list (CRC-SCL) decoder based on cyclic redundancy check codes with a code length of 256 for the first time in hardware, and this decoder can be adapted to various code rates. The total throughput of the decoder reaches 40 Gbit/s at the maximum clock frequency of 156.25 MHz. In addition, we carry out 56-Gbit/s (28-Gbaud) QPSK back-to-back experiments based on polar codes. Experimental results show that the CRC-SCL decoder implemented in this paper can obtain a coding gain of 7.5 dB when the bit error rate is equal to 10 -3. Furthermore, to balance the error correction performance and resource consumption, we also analyze the influence of quantization bits on the decoder performance.

A scheme for master-slave carrier recovery upon the blind phase search algorithm is proposed in this paper, and the scheme is suitable for coherent wavelength division multiplexing systems based on optical frequency comb with frequency offset. Firstly, the blind phase search algorithm is used to obtain the phase noise of the master channel, which is in turn used to initialize the phase noise of the slave channel. Then, the initialized results are corrected with phase trackers that can test phases automatically. By adaptively adjusting the number and central position of the test phases, this scheme achieves low-complexity tolerant carrier phase recovery of frequency offset. The simulation results show that when a five-line optical frequency comb with an 80 GHz interval is used as the transmitter and the local oscillating light source, the calculation complexity of the slave channel can be reduced by 80% without sacrificing phase noise tolerance compared with carrier recovery schemes that have channels independent from each other.

Subcarrier signal-to-noise ratio (SNR) expressions are derived in this paper for the precoded direct current-biased optical orthogonal frequency division multiplexing (DCO-OFDM) system and the precoded asymmetrically clipped O-OFDM (ACO-OFDM) system. Simulation results show that in the line-of-sight channel, precoding does not affect the bit error rate (BER) performance of the systems. In the multipath channel, however, it can equalize the frequency-selective fading of the optical wireless channel, thereby uniformizing the subcarrier SNR at the receiving terminal of the O-OFDM system and ultimately improving the system BER performance. The Monte Carlo method is then used to simulate and analyze the peak-to-average power ratio (PAPR) and the BER of O-OFDM systems applying discrete Fourier transform precoding, discrete cosine transform precoding, and discrete Hartley transform precoding, which verifies the correctness of the theoretical analysis. The simulation also verifies the PAPR suppression function of precoding under bilateral clipping of O-OFDM signals.

For the photon counting integral imaging system in a low-light environment, this paper proposes an element image enhancement algorithm based on the composite photon counting model and the Lucy-Richardson algorithm. First, in compliance with the integral imaging principle, 3DSMAX software is used to simulate the target element image collected by the synthetic aperture integral imaging system. After normalization of the target element image, the photon counting element image is obtained via the photon counting model. Then, it is processed in light of the composite photon counting model and its quality is enhanced in view of the additivity of the Poisson distribution. Finally, the Lucy-Richardson algorithm is iterated to enhance the element image and the reconstruction formula is employed to generate the reconstructed image. Experimental results show that the peak signal-to-noise ratio of the enhanced element image increases with the algorithm iteration number and gradually stabilizes. In addition, enhancing the element image delivers a better reconstruction result than the conventional maximum likelihood estimation method.

Multi-view structured light measurement is a process of utilizing structured light measurement system to achieve the complete expression of the measured object from multiple angles. Thus, the splicing of the measurement data from multiple perspectives affects the integrity of the measured object. In this paper, a new method is proposed to estimate the measurement pose using the deep learning and to directly align the multi-view data. The structure light measurement model is a four-step phase-shifting method combined with multi-frequency heterodyne method to realize the single high-precision three-dimensional reconstruction. In pose estimation, You only look once (YOLO) network is used to identify the 3D bounding box corner of the measured object, and perspective n point (PnP) algorithm is used to estimate the target pose. Since the coordinate systems of the measurement system and pose estimation are unified to the monocular camera, the data from multiple perspectives are directly spliced using the estimated pose. The feature descriptors of adjacent point clouds are established, and iterative closest point (ICP) algorithm is used to realize the high-precision stitching. The results show that the proposed measurement can effectively realize the multi-view structured light data splicing. The translation accuracy of pose estimation is better than 3 mm, the rotation accuracy is better than 1°, and the average deviation of stitching point cloud is 0.02 mm, which has a comparable accuracy level with that of using the method of the marker points. The proposed method is suitable for the multi-view structured light measurement with single pose estimation, which can improve the registration efficiency for multi-view measured data.

To monitor the micro-nano-scale deformation of optical fiber material during industrial production, this paper proposes a novel method based on the digital speckle correlation method (DSCM) to measure the out-of-plane displacement. The in-plane displacements between two consecutive images before and after material deformation are estimated by the DSCM. Then, the out-of-plane displacement field of optical fiber material under a microscope can be obtained by the wedge model. The principle of the DSCM is introduced and the measurement of out-of-plane displacement for the optical fiber material is simulated and tested based on the image spherizing algorithm. Simulation and experimental results show that the proposed method can directly extract the out-of-plane displacement from the in-plane displacement of two-dimensional images and measure the real-time deformation of optical fiber material. The experimental device used by the method is quite simple, and only an industrial camera is needed to capture two images under a microscope and thus complete the measurement. Furthermore, the out-of-plane displacement extraction process needs neither conversion of the images to the frequency domain nor phase envelope operation. The proposed method is appropriate for dynamic measurement.

Finite-difference time-domain and terahertz time-domain spectroscopy are used to study the internal delamination defects in glass-fiber-reinforced composite materials. First, the optical parameters of the glass-fiber-reinforced composite material in the terahertz frequency band are obtained using transmission terahertz time-domain spectroscopy; the finite-difference time-domain method is used to simulate the defects. Second, a terahertz time-domain spectroscopy system is used to inspect the prefabricated sample. Finally, the defects are imaged and analyzed for comparison to the time-domain waveform data determined theoretically and through actual detection. It is found that both methods can detect delamination defects with a thickness of 0.3 mm at a distance of 3 and 5 mm from the upper surface of the materials. These results show that the finite-difference time-domain method can provide theoretical support for detecting defects in composite materials by using terahertz time-domain spectroscopy while reducing the dependence on standard components; the terahertz time-domain spectroscopy system can effectively detect internal defects of materials and assess their overall performance through the detection results.

In view of the low coupling efficiency and long simulation time of vertical couplers, an inverse design simulation platform of multi-layer heterostructures is built. With the help of the function-oriented idea of the inverse design and the advantages of high-performance computing, micro/nano-photonic devices with complex multi-layer heterostructures can be generated automatically by convex optimization algorithms after the initial structures are built and the target functions are set. A high-performance vertical coupler based on this inverse design simulation platform is proposed in this paper. The coupling efficiency improves greatly after an Al mirror is integrated into the coupler. The simulation results show that the coupling efficiency of the coupler is 88.42% at 1550 nm wavelength (coupling efficiency is 32.45% without an Al mirror), and the coupler has a 3 dB bandwidth of 103 nm (1500--1603 nm) with good bandwidth and low loss characteristics.

By optimizing the parameter design, this paper prepared a 3×1 photonic lantern with excellent performance. It was fused with a multimode fiber with a core diameter of 30 μm. The stable and controllable quasi-single-mode output is achieved by spatial mode adaptive control and the traditional design principle of photonic lantern mode matching is broken through. Moreover, the optional range of the core diameter at the photonic lantern multimode fiber end is expanded. The stochastic parallel gradient descent (SPGD) algorithm is used to actively control the phase modulator at the input end. When the evaluation function is selected as the barrel power, the fundamental mode proportion of the output beams at the multi-mode fiber end is higher than 85%, and the quality factor M2 of the beams is stably below 1.18, which provides a possibility to solve the problem of mode instability in large-mode-field fiber laser. When the evaluation function is selected as the mode content of a single high-order mode, the corresponding high-order mode content at the output end exceeds 95%.

Improving the performance of blue light-emitting devices is an urgent requirement for the practical application of perovskite light-emitting devices. In this study, we investigated the effects of the hypophosphorous acid (HPA) additive on the morphology, crystallinity, and photophysical characteristics of quasi-two-dimensional perovskites containing mixed-halide anions and binary long-chain ammonium cations. The results show that the HPA additive can improve the crystallinity of perovskite films, boost the formation of the light emission phase, effectively passivate the defects, and enhance charge transport. The maximum external quantum efficiency and maximum luminance of the quasi-two-dimensional sky-blue perovskite light-emitting devices are 7.9% and 7300 cd/m 2, respectively, which are about 4.2 and 2.9 times that of the devices without HPA. The operational stability of the devices is also improved.

Endocytoscopy (EC), as a kind of endoscope with ultra-high magnification, enables the in vivo observation of stained nuclei directly, which is of great significance for the diagnosis of early-stage cancer. Only Olympus of Japan has the technology so far. The core component of EC is the optical imaging system at the tip, and the current endocytoscopic imaging system has a small field of view (FOV) during imaging at high magnification, which leads to low efficiency. In this study, an endocytoscopic imaging system with high magnification and a large FOV has been proposed. We use six-piece spherical system to realize a zoom endoscopic objective lens with a large FOV, which has merits of high performance and low cost. Then, we construct the endocytoscopic imaging system based on this lens. The experimental results show that the object resolution of our system arrives at 181.0 lp/mm, and the magnification is about 500×. In addition, the FOV of microscopic imaging is significantly increased to 1200 μm×670 μm, which is more than double that of the current endocytoscopic imaging system. On this basis, the nuclear segmentation function is added to the system by deep learning, and the segmentation accuracy reaches 96.58%, which verifies the imaging ability of our system for the details of nuclear morphology.

Based on the optical phase change material Ge2Sb2Se4Te1 and the optical waveguide structure, a reconfigurable 2×4 mode multiplexing optical switch device is proposed to improve the optical communication capacity. The device is composed of two 1×2 multiplexing switch units with a slanted waveguide structure and a 2×2 multiplexing switch unit with symmetrical structure. First, the mode transmission characteristics in the waveguide are analyzed by the mode coupling theory. Second, the optical switching device is modeled by the three-dimensional finite difference time domain method. Finally, the model is used for experimental research. The research results show that when the working wavelength is 1550 nm, the insertion loss of the 1×2 switch unit when the phase change material is in the crystalline state and the amorphous state is as low as 0.60 dB and 0.06 dB, and the extinction ratio is as high as 19.55 dB and 27.58 dB, respectively. The minimum insertion loss of the 2×4 mode multiplex switch in the entire C-band (1530--1565 nm) is 0.23 dB, and the maximum extinction ratio is 19.12 dB.

Wavelength-modulated surface plasmon resonance (SPR) sensors based on prism coupling can obtain high detection sensitivity only in the long-wavelength band but cannot take both detection range and detection sensitivity into account. In this work, we proposed a wavelength and angle co-modulated SPR sensor using the surface plasmons excited by objective-coupling. Through angle adjustment via objective coupling, the detection sensitivity of the SPR sensor in the short-wavelength band is improved, and the refractive index is measured with high sensitivity in a large detection range. Through simulations and experiments, the refractive indices of glucose solutions with different concentration were measured with the proposed method. The dynamic detection range is 4.4×10 -2 RIU, and the detection sensitivity is 5066.97 nm/RIU. In comparison with the wavelength-modulated SPR sensing method, the detection sensitivity of the wavelength and angle co-modulated SPR sensing method is increased by 2.5 times in the same detection range. This method achieves the real-time and rapid detection of refractive indices with high sensitivity in a large dynamic detection range, and it can be widely applied to biomedicine, food safety, and other fields.

In order to improve the spatial resolution of the imaging system, the influence mechanisms of the focal spot size and envelope shape in the focused refractive index microscopy imaging system on the spatial resolution are analyzed, and a method for improving the imaging spatial resolution through a numerical deconvolution algorithm is proposed. First, the spatial field distribution of the focused generalized cylindrical vector beam is analyzed, and then the difference between the influence of this beam and the ideal slim beam on the spatial resolution during the refractive index microscopic imaging process is compared. By measuring PS (Polystyrene) spheres with known refractive index and shape, the point spread function of the system under the experimental conditions is obtained. The deconvolution algorithm is used to reconstruct other sample images to obtain experimental results closer to the real situation. The results show that this method has a significant effect on improving the imaging quality and spatial resolution of the system.

The fluorescence method is a noninvasive measurement method that can rapidly measure the primary productivity of algae in aquatic systems. However, in the current analysis of fluorescence dynamics of primary productivity, when the photosynthetic size unit of algae is used with a fixed value, the measurement results of the primary productivity of algae in an aquatic system often exhibit deviations, particularly where cyanobacteria existing. The photosynthetic size unit is defined as the ratio of the photosynthetic reaction center concentration to the chlorophyll concentration. Herein, to obtain accurate algae photosynthetic size units and improve the accuracy of the primary productivity, excitation fluorescence spectroscopy was employed to analyze the proportion of cyanobacteria and other eukaryotic algae. As a result, the photosynthetic size unit of the mixed algae sample was corrected, and a fluorescence method based on the photosynthetic size unit correction is proposed to measure the primary productivity of algae. The results of a comparison test of the primary productivity of purebred and mixed samples demonstrate that using the proposed correction method, the measurement errors of the primary production of purebred cyanobacteria, chlorophyta, and pyrrophyta samples are reduced from 38.8%, 14.3%, and 13.2% to 3.9%, 4.1%, and 5.2%, respectively. In addition, the maximum and average measurement errors of the primary productivity of the mixed sample decrease from 20.4% and 15.2% to 4.5% and 5.2%, respectively, compared with those without correction. The proposed method can effectively resolve the measurement result deviation problem caused by the fixed value of the photosynthetic size unit. The proposed method provides an important reference to improve the measurement accuracy of primary productivity of algae in aquatic systems.

We study the eigenstates of Kramers-Henneberger (KH) hydrogen atom with σg and σu symmetries in a linearly polarized high-frequency strong laser field, within the framework of the nonperturbative theory. The theory predicts that within high-frequency limit, electric structure is determined by a time-independent Schr?dinger equation containing a “dressed” Coulomb potential. We use a new basis set to solve the structure equation and compare our calculation results with existing research results. Our results are accurate for low-level eigenstates especially the ground state (1s). But for excited states, our results are accurate only when the laser intensity is high. Furthermore, we also study the eigenstate structures of KH hydrogen atom. We find when the laser intensity is high, not only the low-level eigenstates exhibit the “dichotomy” structures, but also the high-level eigenstates display “muti-lobe” structures.

With a footprint camera for surface imaging of laser spot and at the same time, it will cause the laser spot image in the camera to overlap with the ground image, resulting in poor center positioning accuracy of the laser spot. In this paper, according to the characteristics of the images measured by GF-7 satellite footprint camera, the ground noise image classification method is proposed to optimize the Gaussian fitting spot at the same time, the classification method of the spot image and the extraction accuracy of the corresponding spot center under the background of different ground noise are analyzed. Experimental results show that the proposed method has a center positioning accuracy of 0.11, 0.13, 0.16 pixel, and a positioning variance of 0.020, 0.262, 0.341 pixel, respectively, under different noise conditions of low, medium, and high. At night when the signal-to-noise ratio is better, the spot positioning accuracy is 0.02 pixel, and the positioning variance is 0.0036 pixel, indicating that the noise is the most important factor affecting the spot center positioning accuracy.

The laser scattering and absorption of algal particles is the main reason for the attenuation of underwater blue-green laser communication performance in seawater. In this paper, based on the discrete dipole theory, five kinds of particle models of agglomerated core-shell cyanobacteria are established, including double ellipsoidal, four ellipsoidal, columnar filamentous, ring filamentous, and S filamentous ones. The extinction absorption and scattering coefficients of the core-shell algae particles at 532 nm of the blue-green laser are calculated as a function of the size of the core-shell cyanobacteria particles. Based on the uniform mixed layer theory, the scattering intensities of the core-shell cyanobacteria models versus scattering angle with and without an intermediate mixed layer are compared, and the influence of particle size on the scattering matrix elements is calculated for the five core-shell cyanobacteria models. The calculation results show that the absorption and scattering coefficients of the five kinds of algae at the band of a blue-green laser increase with the increase of particle size, and the forward scattering intensity is the largest. In contrast, the scattering intensities of the five models decrease with the increase of scattering angle, and the scattering matrix element ratios of several kinds of large size algae models fluctuate more. These research results lay a foundation for the study of blue-green laser scattering and absorption characteristics of underwater suspended algae particles as well as the modeling of underwater blue-green laser communication channels.

In our daily life, we often come into contact with various scattering media, such as ground glass, biological soft tissues, clouds and fog. Ground glass can generally be considered as a surface scattering medium without thickness, that is, a random phase mask. But biological soft tissues such as chicken breast are volume scattering media with a non-negligible thickness. The propagation process of light in a volume scattering medium such as chicken breast is complicated and is affected by factors such as thickness and anisotropy factor. In experiments, researchers often choose ground glass as the scattering medium, and tend to extend the relevant conclusions directly to the volume scattering medium such as chicken breast. We compare and analyze their differences in imaging and scattering energy distribution between ground glass and volume scattering media based on the energy distribution. In addition, we have proposed and used an integral divergence angle measurement method to explore the conditions under which the two speckle distributions are approximately equivalent.

When Fourier-transform infrared spectroscopy is used to on-line detection of high-temperature gas in an industrial furnace, the noise formed by turbulence will affect the spectral signal-to-noise ratio and the accuracy of concentration inversion. This paper introduces a new data processing method for infrared interference signal-spectrum conversion. Different from the traditional data processing method for Fourier transform spectra, this method takes the zero optical path difference as the reference to align the interference signals and averages multiple scanning interference signals. It adopts the complex window function and spectral data convolution to reduce the spectral aliasing caused by spectral sidelobes. This data processing algorithm can mitigate the effect of turbulent noise on the gas concentration inversion, improve the inversion accuracy, reduce the amount of system calculation, and increase the spectral data rate. Taking the passive measurement experiment of carbon monoxide with superimposed turbulence as an example, this paper analyzes the spectral signal-to-noise ratio, spectral correlation, and concentration inversion results using different data processing methods. The results show that the proposed signal data processing method is better than traditional data processing methods in the online detection of turbulent noise. The spectrum obtained by the new data processing method is more precise (with better spectral correlation), and the concentration of gas inversion is also more accurate. In addition, it can decrease the amount of system computation and shorten the time of the system’s online measurement. This is essential for the accuracy of online gas concentration monitoring.

We combined near-infrared spectroscopy with the deep learning theory to propose a method for rapidly detecting the content of each component in cotton-polyester blended fabric based on the Dropout deep belief network (DBN). Firstly, wavelet transform was used to compress the original spectral data. Then, a DBN model with a Gaussian restricted Boltzmann machine (GRBM) as the core was constructed, which could ensure the integrity of input data. Finally, Dropout was used to effectively prevent the model from overfitting and the interdependence between nodes was reduced by hiding some hidden layer nodes. As a result, network sparsification was achieved and the ability of nonlinear modeling and network model generalization was enhanced. The experimental results indicate that in the analytical model of the content of each component in cotton-polyester blended fabric built by the Dropout-DBN method, the correlation coefficients of prediction set for cotton and polyester contents are respectively 0.9927 and 0.9903, and the root mean square errors of prediction set are 0.0792 and 0.0869, respectively. The model proposed in this paper has much higher accuracy and adaptability than other modeling methods, which is conducive to model transfer and sharing and improves the intelligentization of the model.

Surface-enhanced Raman scattering (SERS) is a spectroscopic technique capable of accurately analyzing the compositions of materials at low concentration (volume fraction). In the case of metallic nanostructures, SERS enhancement is dependent on the electromagnetic field enhancement caused by the localized surface plasmon resonance (LSPR). In recent years, various LSPR metallic nanostructures are widely employed in SERS research, such as nanoantennas, nanoholes, and nanogrooves. However, once manufactured, these structures are immutable, which cannot meet the flexibility required by Raman detection. This problem can be solved by optical tweezers. In this paper, we develop a method of trapping gold nanocubes by optical force and facilitating gold nanocubes aggregation by photothermal convection. On this basis, the Raman signal at a low concentration (10 -12 mol/L) is significantly enhanced and detected, with the enhancement effect being better than that of gold nanospheres. Compared with traditional SERS, the proposed method has the advantages of real-time operation, dynamic operation and in-situ operation, thus showing potential application values in many important fields such as biological cell detection, analysis of substance composition and structure, and molecular sensing.

This article explores implementation and application of fluorescence auto-correlation spectroscopy (FACS) as a quantitative immunoassay method. Using the binding interaction between Alexa Fluor647 fluorophore/green fluorescent protein antigen and its monoclonal antibody as a model system, we used a benchtop fluorescence correlation spectrometer to collect fluorescence autocorrelation data of solution samples of the antigen mixed with various concentrations of its antibody. Combining the classic FACS technique with the maximum entropy method, we can respectively evaluate antigen-antibody binding quantitatively and qualitatively. By analyzing the collected FACS data, the self-developed data analysis software can determine the dissociation constant of the antigen-antibody binding reaction. Experimental results show that FACS is a simple, rapid, and sensitive method for quantitatively determining antigen-antibody binding affinity, suitable for measuring dissociation constant values in the pM to nM range. The modular software standardizes the data analysis procedure while improving accuracy and reproducibility of analysis results.

The existing distributed optical fiber Raman temperature measuring principle is to use the relationship between Stokes and anti-Stokes intensity ratio and temperature to obtain the temperature. However, it is difficult to process the light intensity signal, since the Raman scattering peak intensity is relatively weak. According to the bond relaxation theory and the relationship between Raman frequency shift and bond parameters, a linear relationship between Raman frequency shift and temperature is established. And a new method for measuring Raman frequency shift temperature is proposed. The Raman frequency shift high temperature effects of diamond, graphite, CdS, Bi2Se3 and Sb2Te3 are calculated. These calculation results match well with the experimental ones and the Raman reference frequency and the atomic cohesive energy are obtained. The proposed method effectively avoids the influence of Raman peak strength on temperature measurement and provides a new theoretical method for the rapid development of distributed optical fiber Raman temperature measuring techniques.

In light of the shortcomings of threshold increments in evaluating dynamic glare, starting from the visual characteristics of human eyes, this paper proposes a dynamic glare evaluation method based on the principle of brightness contrast analysis and builds a dynamic glare evaluation model. With the change in the field of view of human eyes as the starting point, the influence factor of the change in driving speed on the driver’s perception of the equivalent light curtain brightness in the lighting environment is studied. A variety of mathematical models are used to determine the relationship of driving speed with the ratio between dynamic and static equivalent light curtain brightness at the corresponding driving speed to explore the dynamic and static glare difference coefficient. The experimental results show that the difference coefficient is positively correlated with the driving speed of the drivers. From the analysis of goodness of fit and variance test, the relationship between the dynamic and static glare difference coefficient and the driving speed can be best described with an exponential function model. This evaluation method can lay a foundation for the establishment of a dynamic glare evaluation system and provide design basis and solutions for road lighting design in China.