This PDF file contains the front matter associated with SPIE Proceedings Volume 12706, including the Title Page, Copyright information, Table of Contents and Conference Committee lists.

A comprehensive site testing campaign was carried on in the northwestern area of China from July to November 2022. We conduct the study focusing on the daytime optical turbulence and precipitable water vapor long-term variation in this area, which are essential for time-domain astronomy and site scheduling. A relatively quiet and dry atmosphere situation that benefits observation can be more easily found in September and October. The so-called ’conversion time’, an excellent condition for observation at dawn and dusk, behaved differently in different months. Meanwhile, better observation conditions can be found at dawn in July, August and September but at dusk in October and November in the daytime.

A methane leakage monitoring system based on light-induced thermoelastic spectroscopy (LITES) is proposed in this manuscript. We use our methane leakage monitoring system for methane detection at the wavelength of 1650.961 nm. This system has a minimum detection limit of 62.8 ppm·m and a good linear response (R-square = 0.997). We also simulated methane leakage, and the results show that our system has the ability to monitor methane leakage.

Optical system with zooming ability is essential for space exploration. In this paper, we proposed a new varifocal lens design based on the fifth-order X-Y polynomial free-form surface. It can change its focal power by the vertical deflection of the two free-form surfaces. We described the proposed lens’s modulation phase function and aberration based on the first-order optical analysis. Simulation experiments compared the proposed lens with the Alvarez lens regarding surface depth and zoom capability. We further investigate the correspondence between vertical deflection and optical power. The results show that the focal power of the varifocal lens based on the fifth-order X-Y polynomial free-form surface is proportional to the cube of the lateral shift distance, which has a stronger zoom ability than the Alvarez lens. It can achieve a wide range of power changes with a smaller lateral displacement, contributing to the zoom system’s further miniaturization.

The phase transition of water vapour is typically accompanied by a change in the water vapour isotopes. The dynamics, transpiration, and condensation of water vapour in the atmosphere can also be revealed by measuring water vapour isotopes in the atmosphere. This information is crucial for understanding the water cycle in the atmosphere. Fourier Transform Infrared (FTIR) spectroscopy is widely used to monitor atmospheric trace gases. This study is based on near-infrared solar absorption spectra collected by portable Fourier Transform Infrared spectrometer (FTS) to observe the column concentration results of H2O and HDO. And the column isotope ratio δD is calculated by H2O and HDO results. The fitted root-mean-square errors (RMSE) of the spectral retrieval window of H2O and HDO were 0.107% and 0.175%, respectively. And the mean retrieval error for H2O and HDO was (0.59 ± 0.21) % and (0.94 ± 0.20) %, respectively. The calculated error of δD was 0.0035‰, which shows a high level of observational accuracy. The time series of δD obtained from September 2016 to December 2017 with a varied in the range of -5.69‰ to -369.19‰. And the lowest δD observed in January with a mean value of (-249.63 ± 32.35) ‰ and the highest δD observed in July with a mean value of (-38.61 ± 2.43) ‰, the time series show a clear seasonal variation. The observations demonstrate the capability of the FTIR spectrometer to observe the stable isotope and isotope ratio δD of atmospheric water vapour with accuracy and precision.

In recent years, studies on fine particulate matter have shown that high concentrations of particulate matter seriously affect the quality of weather, creating a series of severe weather such as haze and posing a great risk to human health. The results of epidemiological studies suggest that particulate matter is associated with a higher risk of cardiopulmonary mortality and morbidity. Therefore, there is an urgent need to conduct research on particulate matter to solve the human health problems caused by particulate matter pollution. The identification of the compositional characteristics of particulate matter presupposes the separation of particulate matter with different aerodynamic diameters and provides scientific guidance for solving the problem of atmospheric particulate matter pollution. To address this problem, a virtual impactor with a cutting particle size of 1.2 μm is designed in this paper. The influence of key parameters on the performance of the virtual impactor is also discussed. The results show that the proposed virtual impactor has a cutting particle size of 1.2um and a good steepness of the collection efficiency curve. It shows that it can effectively separate atmospheric particulate matter according to particle size and provides a design basis for realizing a low-cost atmospheric particulate matter mass concentration detection instrument. Meanwhile, we design a microfluidic chip for particulate matter detection based on this virtual impactor. The hardware circuit of this microfluidic chip is also designed.

The imaging equipment working in the atmosphere will not only be limited by the performance of the imaging system, but also be affected by turbulence. In the fields of astronomical observation, ground-based remote sensing and remote monitoring, there is an urgent need for corresponding methods and technologies to eliminate the impact of atmospheric turbulence and obtain clear images. With the development of computer technology, atmospheric optics theory and image processing technology, more and more researchers hope to combine deep learning technology with atmospheric turbulence theory to reduce the impact of turbulence on imaging and obtain clear and stable images. In this paper, a turbulence image restoration technique based on Generative Adversarial Networks (GAN) is proposed, which is divided into generator network and discriminator network. The generator network is used to convert blurred images affected by turbulence into clear images. The discriminator network is used to compare the converted image with the real clear image to determine whether the image is real or generated. After the whole GAN is optimized and trained, the image transformed by the generator and the real and clear image cannot be distinguished from each other. Because the training of the GAN requires a large number of corresponding samples, it is difficult to obtain the images affected and unaffected by turbulence at the same time in real life, so this paper uses the statistical characteristics of turbulence to simulate a large number of images affected by turbulence. We used the trained GAN model to simulate turbulence image restoration and got some achievements.

High precision laboratory geometric calibration is the basis for the validity of on-orbit data of the Directional Polarimetric Camera. However, the difference in refractive index between the laboratory geometric calibration environment and the on-orbit vacuum environment can lead to changes in instrument geometric performance. The geometric performance difference of the instrument in the standard atmospheric environment and vacuum environment was analyzed by Zemax. The image point position deviation of the instrument in the two environments increases monotonically with the FOV. The image point position in the standard atmospheric environment is further away from the optical axis. When the FOV of the incident beam is 60o , the image points position deviation in all bands is greater than 1.42 pixels. Then, the laboratory carried out the environmental difference verification experiment based on the geometric performance verification light source. The experimental results are in good agreement with the Zemax analysis results, and the average deviation in the 670 nm band is less than 0.01 pixel. Finally, the laboratory geometric model parameters of the Directional Polarimetric Camera are corrected according to the Zemax analysis results. The corrected geometric model parameters will effectively improve the on-orbit geolocation and image registration accuracy of the Directional Polarimetric Camera.

To estimate spatial distribution of thermal characteristics of stratospheric airships, this paper considers the complex thermodynamic environment in which the airships operate, and establishes a computational model for the thermal characteristics of the airships, including thermal equilibrium equations, direct solar radiation, scattered solar radiation, Earth-reflected radiation, atmospheric infrared radiation, Earth infrared radiation, radiation heat transfer and convective heat transfer between skin units. With this model, theoretical simulations of temperature fields were performed for the airships. The simulation results show that the skin temperature of stratospheric airships are mainly affected by the intensity of solar radiation, which is lower at night and higher during the day. Under floating conditions, the skin temperature field exhibits high non-uniformity and significant temporal variations. The skin solar absorptivity of the stratospheric airship has a significant effect on the skin temperature, as reducing the solar absorptivity from 0.5 to 0.2 decreases the maximum skin temperature from 322.94K to 263.98K, with a decrease of 58.96K. The skin surface infrared emissivity is another factor which has a significant effect on the skin temperature, as increasing the surface infrared emissivity from 0.5 to 0.8 reduces the maximum skin temperature from 297.35K to 274.74K, with a decrease of 22.61K. Different seasons have a certain influence on the skin surface temperature of stratospheric airships, with a temperature difference of about 15K between the summer and the winter solstices, mainly due to the difference in solar radiation intensity received by the skin of the airship, which affects the temperature variation of the skin. The theoretical model established in this paper provide a useful tool for multi-physics simulations and analyses of stratospheric airships.

Models related to long and short-term memory networks have demonstrated superior performance in short-term prediction, but their prediction ability becomes limited in long sequence time series forecasting (LSTF), and prediction time increases. To address these issues, this paper optimizes the Transformer and Informer models in the following ways: (1) input representation optimization, by adding a time embedding layer representing global timestamps and a positional embedding layer to improve the model's prediction ability for aerosol extinction coefficient (AEC); (2) self-attention mechanism optimization, by using probabilistic self-attention mechanism and self-attention distillation mechanism to reduce memory usage and enhance the model's local modeling ability through convolutional aggregation operations; (3) generative decoding, using dynamic decoding to enhance the model's long sequence prediction ability. Based on these optimizations, a new LSTF model for AEC is proposed in this paper. Experimental results on the atmosphere parameters of the Maoming (APM) dataset and weather dataset show that the proposed model has significant improvements in accuracy, memory usage, and runtime speed compared to other similar Transformer models. In the accuracy experiment, compared to the Transformer model, the MAE of this model on APM dataset decreased from 0.237 to 0.103, and the MSE decreased from 0.345 to 241. In the memory usage experiment, the model can effectively alleviate memory overflow problems when the input length is greater than 720. In the runtime speed experiment, when the input length is 672, the training time per round decreased from 15.32 seconds to 12.39 seconds. These experiments demonstrate the effectiveness and reliability of the proposed model, providing a new approach and method for long sequence prediction of AEC.

Sun glint is a serious obstacle to passive optical remote sensing images. As is the specular reflection of sunlight from the facets of the water surface, sun glint has great linear polarization characteristics, and it is usually suppressed by adding polarizers. Therefore, a spaceborne sun glint polarization parameter measurement system is developed to calculate the on-orbit sun glint parameters in real time. Firstly, we analyzed the polarizing radiation distribution model of sun glint and developed a real time detection system for polarization angle of sun glint according to the principle of spaceborne polarization imager. The system is using Xilinx V5 FPGA as the on-the-satellite processing platform, and we use high-level synthesis (HLS) tools for algorithm hardware description development. By using dataflow, pipeline and other optimization methods in HLS, we greatly reducing computing time and reducing the FPGA resource use. Finally, we use it to calculate the sun glint polarization angle through a three-channel data with a granularity of 25×25 in 670nm, the simulation results show that under the 100M clock, 54% of the slice and DSP48 FPGA resources are consumed, and the sun glint polarization angle can be calculated in 8ms time, which meets the design requirements of rapid sun glint detection.

The laser induced breakdown spectroscopy (LIBS) technology coupled with a principal component analysis and relevance vector machine (PCA-RVM) was used for rapidly detect the concentration of heavy metal Cr in soil. The PCA-RVM was obtained by optimizing the relevance vector machine (RVM) with PCA.LIBS spectrum of 14 soil samples with different concentration of elements were collected and used for the model training and prediction. 10 of those were selected as training sample sets to build the PCA-RVM model, and the others as test sample sets for model evaluation. Comparing with the prediction results of PCA-RVM model with that obtained using RVM and support vector machines (SVM) model, the analytical accuracy improved by 84.17% to RVM and 92.62% to SVM at the maximum, respectively. Indicating that the PCA-RVM model can effectively improve the detection accuracy and repeatability of LIBS analysis of elemental concentration in soil.

We develop an optical wireless communication-based 2K real-time video surveillance system prototype with field- programmable gate arrays. Using a 3-W blue light-emitting diode and an avalanche photo-diode, 20-m and 1.5-m real-time picture/video transmission with a high resolution of 1920 × 1080 pixels is implemented in free space and pure water channel, respectively. It indicates the good performance of the prototype, which is the first step to realize underwater visual monitoring in future human-robot interaction applications.

In this paper, the effects of turbulence intensity and transmit-receive matching angle residuals on detection performance of spaceborne coherent wind lidar were studied and analyzed. The antenna efficiency equation was derived and simulated in the target plane by Monte Carlo and Backpropagated local oscillator (BPLO) methods. Normalized CNR was defined as a measure. The antenna aperture corresponding to the maximum normalized CNR was considered optimal. We simulated the optimal aperture with different mismatch angles of 0 µrad, 2 µrad, 4 µrad, and 6 µrad under weak, intermediate, and strong turbulence intensities respectively. From the simulation results, it is concluded that:as the turbulence intensity and angular residual increase, the coherence length and the optimal antenna aperture decreases. Besides, under strong turbulence, the effect of mismatch angle on the normalized CNR is weakened and the appropriate range of antenna aperture is narrow. The optimal antenna aperture is about 400 mm under the condition of weak or intermediate turbulence.

During the propagation of array laser in the atmosphere, due to the influence of atmospheric coherence length, average wind velocity and laser duration, the beam quality in the far field will be reduced. In this paper, an array laser propagation model and a dynamic atmospheric turbulence phase screen are constructed. The peak intensity and the circumferential intensity are used as the criteria to evaluate the beam quality degradation of coherent and incoherent lasers in the far field. The results show that the beam quality of coherent combining is better than that of incoherent combining in a short laser duration; However, the beam quality of incoherent and coherent combination decreases and approaches gradually with the increase of laser duration. The researches can provide basic support for selecting the best beam combining mode when the high-power laser system is used in different environments.

At present, governments around the world and the organization are demonstrating how to deploy LEO communication constellations, such as Starlink, space-based information network and other mega constellations. With the satellite increasing quantity，it greatly increases the risk of satellite in orbit collision. In case of satellite collision early warning, the satellite depends on ground system early warning information, and then guides the satellite to avoid maneuver, the whole chain takes a long time and involves the coordination of multiple departments, multiple personnel and different links. The management cost is very high and the efficiency is low, which cannot meet the needs of orbit collision management of mega constellations .Autonomous avoiding of satellites on orbit is an inevitable trend. In this paper, we devise a scheme for satellite autonomic avoiding on low orbit mega constellations. By analyzing the orbit debris environment of spacecraft, its collision early warning theory is established, the strategies and methods for orbit avoidance are formulated, spacecraft warning software is based on continually update cata- -log database，what is also used for Orbit early warning and avoidance. It will provide technical support for the healthy on orbit operation of mega constellation in the future.

The spatial and temporal distribution of atmospheric aerosols closely affects climate change, air quality, environmental pollution and human health. Exploring and predicting the spatial and temporal characteristics of regional atmospheric aerosols is beneficial to the monitoring and assessment of regional atmospheric environmental quality. Taking the Qinghai-Tibet Plateau and its surrounding areas as an example, this study considers the spatial and temporal non- stationarity of aerosol optical thickness (AOD) and its multiple driving factors, and proposes a geographically and temporally weighted regression method based on kernel principal component analysis (KPCA-GTWR) is proposed. The method eliminates the multicollinearity among the driving factors after the multicollinearity test, extracts the principal components with a cumulative contribution rate greater than 95% as the input of GTWR, and improves the prediction accuracy of GTWR. Finally, the method compared with the prediction results of the conventional VIF-GTWR method and PCA-GTWR method. The results found that (1) there are correlations between AOD and its multiple drivers, as well as linear and nonlinear correlations between the drivers. (2) In comparison, the KPCA-GTWR method has the highest prediction accuracy. Compared with the conventional VIF-GTWR and PCA-GTWR methods, the predicted AOD with MERRA-2 AOD 10-fold cross validated R 2 improved from 0.764, 0.861 to 0.914 , RMSE decreased from 0.059, 0.05 to 0.044 , and MAE decreased from 0.043, 0.037 to 0.033, respectively. (3) Comparing the results in June, July, August in 2020, the spatial distribution of AOD and MERRA-2 AOD predicted using this method in and around the Tibetan Plateau is consistent and shows large spatial differences. The low values of both predicted AOD and MERRA-2 AOD are located in the main part of the Tibetan Plateau, around 0.25 or less, while the high values are found in the Tarim Basin, the Ganges Basin of India and the Sichuan Basin, up to 0.75 or more.

The gas sensing based on graphene plasmons enhanced infrared absorption has the advantages of label-free identification of gas molecules, low loss and tunability. However, the optical field confinement of graphene plasmons is much smaller than distribution range of gas molecules, resulting in weak interaction between graphene plasmons and gas molecules. It is difficult to significantly improve the sensitivity of gas sensing. A gas sensor based on double-layer graphene nanoribbons with enhanced plasmons is proposed to improve the near-field coupling between highly confined field and gas molecules. Meanwhile, the influence mechanism of trapping free-gas molecules via surface adsorption is explored on increasing the sensitivity of gas sensing. The results show that the vibrational absorption enhancement of gas molecules based on double-layer graphene nanoribbons is improved by at least an order of magnitude than the single-layer graphene. The surface adsorption by graphene which tunes the gas concentration close to graphene can change the mode weight of vibrational mode to improve the sensitivity further. This study provides an important theoretical basis for designing and preparing gas sensor based on two-dimensional materials plasmons enhanced infrared absorption, and promotes the development of highly sensitive and integrated gas

We incorporate neural networks into the optical design of off-axis three-mirror reflective system, enabling us to achieve design outcomes without relying on iteration or ray tracing methods. Our approach involves combining analytical relations with neural networks during the design process, which yields results covering the entire parameter space with a single user input, and each design is scored simultaneously. Our results demonstrate that neural networks can simulate the complex relationship between performance requirements and structural parameters of an optical system. As such, the structural parameters can be directly obtained from the performance requirements, replacing the iterative optimization process traditionally used. This approach leads to relatively efficient and straightforward optical design. We anticipate that this method can be extended to various optical systems, reducing the experience threshold and difficulty of optical design.

By constructing an external circulating cavity to provide sufficient delay that equals a multiple of pulse repetition time, a method with a fixed experimental configuration is proposed to measure the coherence length of both single-frequency and microwave-modulated optical pulses. This method can accurately determine the number of coherent pulses as well as distinguish the coherence states: complete coherence, partial coherence and complete incoherence. In addition, all desired coherence phenomena are obtained by one-time measurement, avoiding other operations like frequent fiber-cutting or devices-reconnection in previous methods. Simulation results show that the coherence length of the dual-frequency laser is periodically extended by the reciprocal of the frequency difference, and the random jitter of pulse propagation time would result in obvious measurement errors via perturbing coherence status.

Turbulence effect is one of the key factors limiting underwater optical transmission communication. Eddy light underwater transmission can provide a new way to realize ultra-wideband and high speed underwater optical information transmission. This paper studies the scintillation index of the modified Bessel Gaussian beam propagating in ocean turbulence, analyzes the influence of wave source parameters and ocean turbulence parameters on the propagation quality of the modified Bessel Gaussian beam, and studies the transmission characteristics of the modified Bessel Gaussian beam propagating in underwater turbulence by designing experiments. The influence of turbulent flow induced by water diffusion with different temperature and salinity differences on beam propagation is considered. The theoretical and experimental results show that smaller width parameters will reduce the scintillation index of the beam under the same ocean turbulence environment. In the selection of ocean turbulence parameters, the larger turbulent kinetic energy dissipation rates and the smaller temperature salinity fluctuation equilibrium parameters can also effectively improve the beam transmission performance, and the scintillation index increases with the increase of turbulence intensity. The research results of this paper have important reference value for the research of vortex light transmission and communication

The temperature structure of the global mesosphere and lower atmosphere (MLT) is significant for the study of atmospheric physical, chemical and kinetic processes. Oxygen (O2) A-band airglow (762 nm) can be used as an important tracer to detect the atmospheric temperature structure. The advantage of spatial heterodyne spectrometer (SHS) is high stability, high throughput and high spectral resolution. The fine spectral structure of A-band night glow is detected by limb observation combined with simultaneous split field imaging of atmospheric vertical profile, and the temperature information is retrieved by recovering spectra. Building an accurate forward model is the premise and foundation to obtain the global spaceborne high-resolution atmospheric temperature structure. Based on the A-band night glow radiation mechanism, molecular spectroscopy theory, atmospheric radiation transfer theory and the detection principle of SHS, this paper constructs the forward model of target airglow observation. Furthermore, the sensitivity and analysis of the influencing parameters of the forward model is carried out, which provides a theoretical basis fort the forward modes modification and instrument design. The results show that the forward model described in the paper can satisfy the simulation of A-band night glow spectral radiance observed by SHS at any location through limb observation combined with simultaneous split field of atmospheric vertical profile. That is, the atmospheric tangent range covers 80-120 km and the vertical resolution is better than 2 km. It lays a foundation for the space-borne SHS to detect and accurately retrieve the global temperature structure in MLT region.

Cloud pollution problem in remote sensing data，Atmospheric scattering ,the presence and changes of chlorophyll fluorescence in vegetation, etc., all interfere with the inversion of CO₂, affecting the accuracy of CO₂ inversion.In this study, the Greenhouse Gases Monitoring Instrument (GMI) data collected from GaoFen-5 (GF-5) satellite was applied to the cloud detection study in O₂ A band. The detection results were compared with the cloud judgment product of the moderate resolution imaging spectroradiometer (MODIS), and the proposed algorithm can filterout 90% of the clear sky data. Based on this, a more in-depth study of atmospheric CO₂ retrieval was carried out. The CO₂ retrieval results were compared with those data collected from the Total Carbon Column Observing Network (TCCON) and Greenhouse Gases Observing Satellite, and the results showed that the average accuracy of CO₂ retrieval results was better than 1%. In addition, the correlation coefficient between the results of CO₂ retrieval method and the data collected from TCCON was 0.85. Due to the effect of vegetation chlorophyll fluorescence, the CO₂ retrieval results based on the GMI data were higher than TCCON collected data. After the corrections to reduce the effect of vegetation chlorophyll fluorescence, the correlation coefficient of the CO₂ retrieval results between GMI and TCCON

The space radiometric benchmark enables in-orbit traceable to SI system, calibrates in-orbit loads, improves data consistency across different space radiometric remote sensing missions, and facilitates long-term high-precision monitoring of global climate and environment. The transferring detector becomes an absolute power detector by quantum optical radiation measurement in the self-calibration mode, and is used to measure solar radiation in the observation mode. Si photodiode is used as transferring detector in the visible band, which requires high-precision radiometric detection at the photon level. Therefore, Si photodiode and its amplifying circuit need to have low noise. To expand the detection dynamic range of Si photodiode under low radiation condition, the noise sources of Si photodiode and its amplifier circuit are analyzed, and cooling of Si photodiode is proposed to reduce the noise. Vacuum cryogenic experiment was conducted to study the temperature characteristics of Si photodiode at 223K to 263K, and the temperature control design requirements were obtained. A sealed package Si photodiode based on two-stages TEC was developed, and a high-precision temperature control circuit with -40 °C ± 0.01 °C was designed. The shunt resistance of the cooled Si photodiode at -40°C was tested to be 8.5 TΩ, and the dark current was 1.2 fA. A wide dynamic range low-light-level irradiance source with adjustable radiation intensity is used to test the cooled Si photodiode with a low-noise transimpedance amplifier, the measurement signal-to-noise ratio was 1158 when the photocurrent was about 1pA.

In point target optical detection, the selection of the detection spectrum largely determines the upper limit of detection capability. In this paper, we analyze the main factors affecting point target detection and propose a spectral segment selection method for point target detection based on constant false alarm. The method uses the probability of detection as an evaluation index and considers the target and background radiation properties, atmospheric radiative transfer, background clutter and sensor noise levels. The method can calculate the optimal spectral band for its detection for different cases of target and background information. In this paper, we analyze the clutter levels of different surface types of background using MODIS data, and take typical airborne target detection as an example. We calculate the range of spectral bands whose detection probabilities meet the requirements under several conditions to verify its feasibility. The results show that the point target detection spectra satisfying the false alarm rate and detection probability requirements can be obtained by the method in this paper

Aerosol optical depth (AOD) is one of the basic parameters used to analyze physical properties of regional aerosols, but the in-situ observation or remote sensing AOD dataset could be scarce especially in ocean area. The Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2) reanalysis has the longest temporal span, and its accuracy in China sea area is to be evaluated. This study provides a validation of MERRA-2 AOD products’ applicability in the eastern and southern China sea based on Aerosol Robotic Network (AERONET). The results indicated that the MERRA-2 AOD with 1-hour temporal resolution agreed with the time averaged AERONET AOD well, for its correlation coefficient is 0.887, root mean square error (RMSE) is 0.096, and mean absolute error (MAE) is 0.056. Presented analysis also revealed a systematic underestimation of AOD that MERRA-2 made, and that deviation tended to increase in higher AOD which demonstrated a slope of -0.26 when utilized linear fitting technics, but the mean bias (MB) of test dataset was only -0.001 because the AOD concentrated on lower than 0.2. These results illustrated the suitability of using MERRA-2 AOD product in aerosol researches of the China sea area.

In this paper, based on the infrared channel brightness temperature from the advanced geosynchronous radiation imager (AGRI) of FengYun-4A satellite, the research on quantitative estimation of precipitation is carried out. The algorithm of precipitation estimation can be divided into three steps. Firstly, the dictionary of brightness temperature of FY-4A/AGRI infrared channel brightness temperature and the integrated multi-satellite retrievals for GPM (IMERG) precipitation is constructed as the historical training sample library. Secondly, the precipitation FOVs are identified. As prior information, the IMERG and ice cloud products are coupled to classification models of the K-nearest neighbor (KNN) and random forest to determine whether there is precipitation at the FOV to be estimated. Finally, the precipitation estimation is performed. Inverse problem regularization method and random forest regression model are used for precipitation estimation, respectively. On this basis, the preliminary experiments for precipitation estimation of and “Ampil (2018)” are carried out. The results show that the precipitation estimation accuracy with ice cloud products as prior information through the inverse problem regularization is better than that with the IMERG products as priori information, while the conclusion is the opposite for the random forest method. The accuracy of precipitation estimation based on the random forest method is better than that of the inverse problem regularization, especially in the “extreme” precipitation center.

Chlorophyll-a concentration, as a direct indicator of phytoplankton abundance, is important in the study of marine ecological environment and ecosystem's substance circulation and energy exchanges. This paper investigates the distribution of chlorophyll-a over time and space in the Changjiang Estuary through combining in-situ observation during scientific cruises and Geostationary Ocean Color Imager (GOCI) satellite images. The field measured spectral reflectance curves show significant differences from the near-estuarine region to the offshore region, including features such as peak and trough locations, slope variations, and spectral symmetry. Several popular inversion algorithms of chlorophyll-a concentration are optimized and compared using the training dataset, in which the generalized algal bloom index algorithm (GABI) gets a better accuracy and stability. Monthly average distribution maps derived from GOCI images show that chlorophyll-a concentration in the Changjiang Estuary and adjacent areas is always low (≤3 mg/m3 ) in winter, and slightly higher near the estuarine. In spring and summer, the chlorophyll-a concentration rises gradually due to the increasing water temperature, especially in areas east of the maximum turbidity zone. Moreover, chlorophyll-a concentration is relatively higher in the sea adjacent to the southeast of Zhoushan Islands in autumn.

Underwater wireless optical communication, which is an effective technical way to build a high-speed and flexible underwater wireless communication network due to its large bandwidth, good confidentiality and low time delay, is widely regarded as a complementary communication way to hydroacoustic communication. The newest research progress and main technical specification in the current technology of underwater wireless optical communication are introduced, the characteristics of the current underwater wireless optical communication technology are summarized in this paper. A series of improvement measures are proposed for the problems of short communication distance and low robustness in underwater wireless optical communication system, which can provide references for underwater wireless optical communication technology research and engineering project development.

Aerosol scattering and absorption coefficients are important parameters that characterize the optical properties of aerosols, which have significant impacts on the radiation balance, air quality, and climate change of the Earth. In order to further improve the understanding of the relationship between aerosol optical properties and meteorological parameters in the offshore areas of Guangdong Maoming, the scattering and absorption coefficients of aerosols as well as meteorological parameters such as temperature, humidity, pressure, wind speed, wind direction, and visibility were measured. In this study, a prediction model of aerosol scattering and absorption coefficients based on the CatBoost algorithm was proposed using the measured data. Firstly, the measured data was preprocessed, and then a CatBoost algorithm model based on ensemble learning was constructed and trained. The Optuna framework was used to optimize the hyperparameters of the model to obtain the final aerosol scattering and absorption coefficient prediction model. Finally, the machine learning model was used to predict the scattering and absorption coefficients of aerosols in the offshore areas of Maoming. The model was compared with XGBoost and LightGBM algorithm models, and the mean squared error (MSE) and mean absolute error (MAE) were used as evaluation metrics to assess the accuracy of the model predictions. Based on the evaluation metrics, the CatBoost algorithm model based on Optuna automatic hyperparameter optimization performed the best among several models. The experimental results showed that when the training and testing data came from the same region, the MAE of the CatBoost algorithm model based on Optuna hyperparameter optimization was about 5.33, and the MSE was about 48.764, achieving a prediction accuracy of 90.88% for aerosol scattering and absorption coefficients.

This paper presents the studies on the temperature compensation of birefringent filtersfor space-based solar exploration(Hα 656.28 nm). The four-element Lyot filter has a thickness ratio of 1:2:4:8. The technique of temperature compensation of the birefringent filter is based on the complementary characteristics of thermo-optic coefficients between the Iceland spar and ADP birefringence crystals. This paper describes a procedure of designing an independent of temperature filter. This technique of temperature compensation has the advantage that the system does not have a complicated mechanical structure by selecting the appropriate ratio of length of two different birefringence crystals.

Aiming at the detection of benzene concentration in the atmosphere, a power-modulation scheme with laser wavenumber tuning is proposed in mid-infrared integrated-path differential absorption (IPDA) lidar. Based on the differential absorption lidar (DIAL) theory, we design the configuration of power-modulation IPDA lidar. Its central measurement and reference wavenumber are selected as 3090.3cm^-1 and 3137.7cm-1, and the power-modulation scheme of IPDA lidar is proposed through interband cascade laser (ICL) current-driving characteristic. The simulation model of power-modulation mid-infrared IPDA lidar is constructed, and then its theoretical analysis is carried out. Furthermore, the retrieval algorithm for benzene concentration is presented, and then the concentration precision as 1/f noise with different frequencies is analyzed with FFT retrievals of 1000. The detection performance of lidar such as signal-to-noise ratio (SNR) and relative error for path length and visibility is compared between direct current (DC) driving and altering current (AC) driving, i.e. power-modulation scheme. The results show that the uncertainty of concentration is consistent with the effect of 1/f noise, that the SNR increases with the increase of visibility or the decrease of path length and the relative error decreases with the increase of visibility or the decrease of path length, and that the SNR will increase with the increase in frequency, and the relative error will decrease under the same path length and visibility. Therefore, the power-modulation mid-infrared IPDA lidar can be more effective for probing benzene concentration.

A high-resolution simultaneous polarization imager based on off-axis three-mirror telescopic objective detects polarization information to enhance contrast and identify target. Stray light can increase system noise, reduce image contrast, and affect imaging quality. It is necessary to analyze and suppress stray light in order to ensure the polarization measurement accuracy of the instrument. The three-dimensional solid model and optical properties of the instrument were established by stray light analysis software Tracepro. The stray light of channel 1 was simulated and analyzed. The important surface of the system and the first-order stray light paths were found through forward trace and backward trace. The main baffle and vane, secondary mirror baffle and third mirror light barrier were designed by using CAD drawing software. Then the PST (Point Source Transmittance) curve of stray light is given under off-axis angle is within ± 50 °. When the off-axis angle is  30 °, PST is less than 10-10. The VGI (Veiling Glare Index) is 1.47%, which was obtained by fitting the PST curve and integrating. The influence of the VGI on the polarization accuracy was 0.020@p=0.3. The results show that the stray light suppression system have obvious effects, and the influence on the polarization accuracy is acceptable.

Rotating Fourier transform ultraviolet Raman spectrometer (RFTURS) is an ideal and valuable tool for atmospheric CO₂ detection. However, due to the short excitation wavelength and the nonlinear relationship between the optical path difference (OPD) and the rotating angle, it is difficult for RFTURS to produce linear interference signals. This paper proposes a time sequences trigger (TST) method to realize linear sampling of interference signals. Specifically, time sequences are designed at equidistant OPD intervals as external clocking signals to trigger the data acquisition (DAQ) card to sample interference signals. High angular resolution and precise time sequences are obtained by using a gearbox to work at low speed as well as detecting the OPD zero via a sensor, respectively. By a simulation spectrum and white light, the method was tested and ultimately obtained the expected restored spectrum, which addresses the current drawbacks such as large error of the non-uniform fast Fourier transform (NUFFT) method and the subsampling method, and unsuitable work conditions of the reference laser method performing at the UV. This work provides significant guidance for field measurement of atmospheric CO₂ by RFTURS.

Sensible heat flux (H) is an important physical quantity to characterize the turbulent energy transport in the near-surface atmosphere, which is benefit for understanding the spread and diffusion of urban atmospheric pollutants and weather changes. Referring to the principle of the large aperture scintillometer (LAS) to obtain H, we propose a method for detecting H by using laser speckle imaging (LSI) system based on a cooperative target. The experiment system used 3M microcrystalline reflective film to effectively reduce the requirement of laser power. Besides, it could overcome the limitation of the complex terrain of the test field, such as islands and hills where the transportation and electricity supply are not convenient. The refractive index structure parameter 2 Cn , which is required to calculate the H, inversion from image scintillation method and centroid drift method are compared to the 2 Cn inversion by coherence length meter. The comparison results show that 2 Cn obtained by the image scintillation method are not reasonable, while the results obtained by the centroid drift method are in good agreement with the coherence length meter, especially under the circumstances of laser beam near collimation.

Time of flight light detection and ranging (TOF LiDAR) is the main detection technology solution used in the mainstream LiDAR products at present. Smog has a certain interference effect on the laser, which affects the ranging accuracy of TOF LiDAR system. This paper focuses on the accuracy of TOF LiDAR ranging under smog conditions and the error analysis. A vertical cavity surface emitting laser is selected to emit a pulsed laser through a smog-filled smog chamber, a CMOS sensor is used to receive the reflected light, and the experimental data are collected using the host computer software. The collected data are then extracted from the effective area and processed with algorithms such as average filtering. Finally, the image of each pixel with the measured distance and the error situation are obtained. The effect of smog is simulated by increasing the system delay time to obtain the simulated image under smog conditions. The results obtained from the TOF LiDAR smog experiment are compared with the simulation results, and it can be seen that the smog has a significant attenuation effect on the laser transmission, with the attenuation ratio up to 63.99%, and the range error under the smog condition decreases by 53.55%, and the accuracy of the range measurement is improved.

Aerosol is the main component of air pollutants. Lidar is a powerful tool to detect atmospheric aerosols. 355 nm in ultraviolet, visible spectrum and 1064 nm in near infrared are commonly used in detection, while the ultraviolet spectrum with wavelength less than 320 nm is less used. The main reason is that ozone has a certain content in the atmosphere and is strongly absorbed in the ultraviolet spectrum. Retrieving aerosol extinction coefficient from ultraviolet lidar equation is more complex than from 355 nm, visible spectrum and 1064 nm lidar equation because of the interaction of aerosol absorption, ozone absorption and atmospheric molecular absorption.The method of detecting aerosol extinction coefficient is proposed by emitting two ultraviolet lasers into the atmosphere at the same time. An iterative inversion method is designed to retrieve the aerosol extinction coefficient profile from two ultraviolet lidar equations with the ozone concentration profile as the constraint condition. In order to verify the correctness of the inversion method, the test is arranged by simulation signal.Two simulation ultraviolet lidar signals are obtained from supposed aerosol extinction coefficient and ozone concentration profiles, then, the aerosol extinction coefficient profiles in the ultraviolet spectrum are retrieved from the simulated signals by the inversion method. The results indicate that the inversion method is feasible and reliable.

Reducing carbon emissions is a global priority due to human impact on atmospheric pollution and the greenhouse effect. Achieving carbon peak and neutrality requires real-time monitoring of CO₂ concentrations. However, developing high-sensitivity, portable, and anti-jamming gas detection solutions is challenging. Among spectroscopic techniques, Tunable Diode Laser Absorption Spectroscopy (TDLAS) is highly sensitive for detecting CO₂ concentrations. This paper elaborates on the principles of TDLAS for detecting CO₂ concentrations and proposes a noise reduction algorithm to meet diverse environmental requirements. Simulations were performed using software to simulate CO₂ absorption spectra at approximately 1.57866535μm under high-intensity noise (0.1mW - 1mW). Based on this simulation, we applied the Wavelength Modulation Spectroscopy (WMS) technique to calculate the ratio of the output differential signal's second harmonic intensity to the first harmonic S_2f/1f(T) and output power to reduce light intensity influence and improve concentration inversion linearity. The weighted convolutional moving average filtering was utilized to optimize WMS denoising, utilizing weight transfer to make the process more precise and reliable. After analyzing various window functions, it was concluded that a window length of 9 would be the most optimal. The algorithm improved the signal-to-noise ratio (SNR) by 22.435% under these conditions. When the noise level increased fourfold from the original signal, the algorithm enhanced the SNR by 59.514%, enabling reliable CO₂ monitoring even under challenging conditions.

The light scattering method has the advantages of simple structure and good real-time performance in measuring the mass concentration of particulate matter. It is usually used to calibrate the laboratory standard particles to ensure the accuracy of measurement. However, the actual measured particle size of pollutant particles is complex and changeable, it is necessary to explore the scattering light intensity distribution law in multi-detection angles under different particle sizes. The numerical simulation results obtain scattering light intensity distribution of silica particles under different polarization state light sources, and get the appropriate range of detection angle. This paper mainly designs a set of device to measure the scattering light intensity and mass concentration of particulate matter. Meanwhile, the standard instrument TSI was used to measure the real-time change of the mass concentration of particulate matter. The results show that the scattering light intensity signal measured by photodetector is highly correlated with the mass concentration measured by the TSI standard instrument, and the mass concentration of the particles measured by the system is in good agreement with the standard instrument TSI. The scattering light intensity can effectively invert the real-time mass concentration of particulate matter. The experimental device is suitable for real-time measurement of particulate matter mass concentration.

With the development of photoelectric detection technology, blue-green laser underwater transmission and target detection have become a hot research field. At present, most of the underwater laser attenuation channel models regard seawater as a homogeneous medium, and a few layered models only consider the change of chlorophyll concentration with seawater depth, and the number of layers is small. This paper not only considers the influence of chlorophyll concentration, but also introduces the influence of temperature and salinity, increases the number of stratification intervals, and improves the seawater stratification model. Based on the measured data of temperature, salinity and chlorophyll concentration in the vertical direction of seawater provided by the Array for Real-time Geostrophic Oceanography data center website of China, the vertical distribution of seawater attenuation coefficient is given. Using this distribution, the seawater is stratified, and a more accurate vertical stratification model of seawater in the Pacific near Japan is established. Using the vertical stratification model of seawater established in this paper, the transmission process of blue-green laser underwater is simulated based on Monte Carlo method. The results show that with the increase of transmission distance, the number of photon packets on the receiving plane in layered seawater is always larger than that in uniform seawater. The photon packet energy on the receiving plane in the case of stratified seawater and the photon packet energy in the case of uniform seawater increase alternately, which provides a reference for the transmission characteristics of laser in actual seawater.

The polarization instrument of Fengyun-3 precipitation satellite is the first Polarization and Multi-Angle Imager (PMAI) with short-wave infrared channel in China, aiming to accurately measure the radiation characteristics of clouds and aerosols in the atmosphere. The accuracy of radiometric measurement is an important technical index of instrument performance, which is of great significance for the inversion of high-precision quantitative parameters of satellite remote sensing. For the non-polarization channel of a polarization imager, polarization is a kind of interference information, and the polarization sensitivity of the instrument needs to be inverted and quantitatively removed to improve the accuracy of radiation calibration. A method of least squares fitting response value of complete linear polarization incident light based on different polarization angles is proposed to measure the polarization sensitivity of the non-polarization channel full field of view. According to the measured polarization rate of each channel and the polarization characteristics of the incident light, the polarization sensitivity of each channel is calibrated based on the polarization calibration model. The results show that the polarization sensitivity of the non-polarization channel shows obvious edge effect, gradually increasing from the center of the focal plane to the edge, and has obvious spectral differences, the smaller the wavelength having the higher the polarization sensitivity. The maximum polarization sensitivity occurs in the edge field of view of the non-polarization channel in the 1030nm band, close to 1.6%, which has a great impact on the accuracy of radiometric calibration. After polarization sensitivity calibration, the polarization sensitivity of the edge field of view is within 0.5%. The results show that by calibrating the polarization sensitivity of the full field of view of the non-polarization channel, the radiometric calibration can be effectively improved, which provides strong support for high-precision quantitative remote sensing.

As a widely used wavefront sensor in adaptive optics, Hartmann-Shack wavefront sensor (HSWFS) has a simple structure and high accuracy. However, the dynamic range and field of view of HSWFS are limited, preventing it from usage under strong turbulence conditions. Plenoptic wavefront sensor (PWFS) has the advantages of large dynamic range and detection field of view, which effectively compensates for the shortcomings of HSWFS. In this paper, we analyzed the performance of the PWFS theoretically and then verified by simulation. Because of the fundamental error in wavefront slope measurement of PWFS, the open-loop wavefront correction accuracy is unsatisfied and closed-loop correction is highly preferred.