A method and device for detecting and predicting atmospheric refraction and waveguide environmental parameters

Abstract

The present invention relates to the interdisciplinary field of atmospheric science and communication technology, specifically a method and apparatus for detecting and predicting atmospheric refraction and waveguide environmental parameters, comprising the following steps: based on broadband light source emission, using a spectroscopic element to distribute the power of the broadband light source beam to form a probe beam and a reference beam, guiding the probe beam through a preset open atmospheric optical path, and simultaneously guiding the reference beam through a stable medium or vacuum pipeline with a known refractive index. The present invention forms a probe beam and a reference beam by splitting the broadband light source, and causes the probe beam to pass through an open atmospheric path while the reference beam passes through a stable medium. The interference signals of the two beams are then Fourier transformed to extract wavelength phase difference mapping data, which can capture subtle optical path changes caused by atmospheric refractive index disturbances. Compared with traditional single-point or single-path measurements, the present invention utilizes broadband spectral information to improve the perception sensitivity and measurement dimensionality of spatial inhomogeneity of atmospheric refractive index.

Description

Technical Field

[0001] The present invention relates to the interdisciplinary field of atmospheric science and communication technology, and in particular to a method and device for detecting and predicting atmospheric refraction and waveguide environmental parameters. Background Art

[0002] In existing technologies, although spectral analysis can be used to obtain material composition, in open atmospheric paths, the rapid spatiotemporal fluctuations of the refractive index caused by factors such as changes in trace gas concentrations, temperature gradients, and turbulence make it difficult for traditional single-point sampling or slow-scanning spectral techniques to capture the instantaneous three-dimensional distribution and high-frequency perturbation characteristics of the atmospheric refractive index. As a result, the analysis results are often time-averaged or spatially limited, which cannot meet the needs of refining the atmospheric optical environment. For example, traditional refractive index measurement methods, such as the Abbe refractometer, are mainly used for single-point refractive index determination of liquid or solid samples and are difficult to directly apply to tomographic imaging of the atmospheric refractive index field in a wide space. Therefore, improvements are needed. Summary of the Invention

[0003] The purpose of the present invention is to solve the shortcomings of the prior art and to propose a method and device for detecting and predicting atmospheric refraction and waveguide environmental parameters.

[0004] To achieve the above objectives, the present invention adopts the following technical solution: a method for detecting and predicting atmospheric refraction and waveguide environmental parameters, comprising the following steps:

[0005] Based on the emission of a broadband light source, a spectrometer is used to distribute the power of the broadband light source beam to form a detection beam and a reference beam. The detection beam is guided through a preset open atmospheric optical path, while the reference beam is guided through a stable medium with a known refractive index or a vacuum pipeline to obtain the interference signal of the two beams. The interference signal is then Fourier transformed to extract the phase difference value that varies with wavelength and obtain wavelength-phase difference mapping data.

[0006] Based on the wavelength-phase difference mapping data, the phase difference values ​​at different wavelengths are extracted. According to the differences in the refractive properties of dry air and water vapor for light of different wavelengths, a set of linear equations is established to solve the contribution of each component. Multiple groups of broadband light source transmitters and receivers are set up in a specified area to form a cross-optical path network covering the monitoring area. The integrated phase difference of each optical path is recorded, and the monitoring area is gridded. The refractive index of each grid is adjusted through iterative calculation, and the minimum constraint of the total variable component is applied at the same time until the residual of the reconstructed object edge meets the preset threshold, and the atmospheric refractive index disturbance field is established.

[0007] Preferably, the method further comprises:

[0008] Based on the emission of a tunable semiconductor laser, the first absorption line that responds to water vapor concentration and the second absorption line that responds to temperature are selected. The laser is driven to scan the preselected laser wavelength range. The laser absorption signal passing through the atmosphere is captured by a photodetector. The signal is digitally phase-locked and amplified to extract the second harmonic amplitude. The path-integrated water vapor concentration and path-integrated temperature are converted according to the calibration data to obtain the path-integrated temperature and humidity data.

[0009] Based on the path-integrated temperature and path-integrated water vapor concentration in the form of time series in the path-integrated temperature and humidity data, a digital filter is applied to filter out slowly changing background trends to obtain temperature and water vapor concentration pulsation sequences, and the autocorrelation function and cross-correlation function of the pulsation sequences are calculated. Based on the path length information, the temperature structure parameters, humidity structure parameters and temperature and humidity covariance structure parameters are inferred. Combined with the spatial refractive index distribution information provided by the atmospheric refractive index disturbance field, the evolution of the atmospheric optical environment parameters is inferred to generate an atmospheric environment parameter prediction set.

[0010] Preferably, the step of acquiring the wavelength phase difference mapping data is:

[0011] Based on the emission of a broadband light source, the spectrometer is controlled to adjust the power distribution ratio of the probe beam and the reference beam. The probe beam is calibrated to propagate along an open atmospheric optical path defined by predetermined coordinate points. The reference beam is coupled into a vacuum tube with controlled internal pressure and temperature. The beam collimation parameters and path geometric parameters are recorded to obtain a set of optical path configuration parameters.

[0012] Based on the optical path configuration parameter set, the emission of the probe beam and the reference beam is synchronously triggered, and the two beams are configured to generate spatial interference fringes at the beam-combining point through a Michelson interferometer, and the change of the interference fringes intensity over time or optical path difference scanning is captured, and the analog voltage signal is converted into a digital sequence through an analog-to-digital converter to obtain an interference signal sequence;

[0013] Based on the interference signal sequence, the collected digital sequence is Fourier transformed to obtain the spectrum representation of the signal. The peak position and phase value corresponding to each wavelength component are identified from the spectrum. By comparing with the reference arm calibration data, the variation of the phase difference between the detection light and the reference light caused by the atmospheric refractive index disturbance as a function of wavelength is calculated and extracted to obtain the wavelength-phase difference mapping data.

[0014] Preferably, the steps of acquiring the atmospheric refractive index disturbance field are:

[0015] Based on the wavelength phase difference mapping data, phase difference measurement values ​​of multiple target wavelength points are uniformly selected therefrom, and an overdetermined linear equation system is constructed using the refractive index dispersion coefficients of dry air and water vapor at each wavelength, where the unknowns are the dry air density contribution and the water vapor density contribution of the path integral, to establish a refractive component equation;

[0016] Based on the refractive component equation, pairs of broadband light source transmitting units and spectrum acquisition units are deployed at multiple points around the area to be measured. The connections between the transmitting and receiving units are planned to form a cross-optical path network. The spectral phase difference is measured independently for each optical path, and the integrated phase difference data of all optical paths is summarized to obtain a cross-path integrated phase set.

[0017] Based on the cross-path integral phase set, the monitoring space is discretized into a three-dimensional voxel grid, and an initial refractive index estimate is assigned to each voxel. The voxel refractive index is adjusted according to the difference between the measured values ​​of each optical path and the calculated value of the current model. At the same time, a total variation regularization term is introduced to constrain the smoothness of the iterative solution until the residual reaches the preset accuracy, and the atmospheric refractive index disturbance field is established.

[0018] Preferably, the steps for obtaining the path integrated temperature and humidity data are:

[0019] Control the operating temperature and injection current of the laser, select and stably output a first near-infrared absorption line that is sensitive to changes in water vapor concentration, and a second absorption line that is sensitive to changes in atmospheric temperature, set the parameters for periodic scanning of the laser wavelength at the center of the spectrum line, and obtain a laser scanning parameter set;

[0020] Based on the laser scanning parameter set, the modulated laser beam output by the driving laser passes through the target atmospheric path, is received by the photodetector after filtering out the background light, the absorption signal output by the detector is amplified, and the amplitude data points of the second harmonic signal are demodulated and extracted to obtain the harmonic amplitude of the absorption signal.

[0021] Preferably, the step of acquiring the path-integrated temperature and humidity data further includes: based on the harmonic amplitude of the absorption signal, using a quantitative relationship model between the second harmonic amplitude obtained in advance through standard gas calibration and the gas concentration and temperature, converting the second harmonic amplitudes of the two measured spectral lines into path-integrated water vapor concentration values ​​and path-integrated temperature values ​​respectively, forming a time-synchronized measurement data sequence, and acquiring path-integrated temperature and humidity data.

[0022] Preferably, the steps of obtaining the atmospheric environment parameter prediction set are:

[0023] Based on the multi-point time sampling data of path-integrated temperature and path-integrated water vapor concentration in the path-integrated temperature and humidity data, each time series is subjected to Butterworth high-pass filtering to separate the fluctuation components caused by atmospheric turbulence and obtain a temperature and humidity pulse value series;

[0024] Based on the temperature and humidity pulsation value sequence, the autocovariance function of the temperature pulsation time series, the autocovariance function of the water vapor concentration pulsation time series, and the cross-covariance function between the two are calculated, and the temperature structure parameters, humidity structure parameters and temperature and humidity covariance structure parameters are inferred from the zero-point delay value of the covariance function to establish the atmospheric turbulence characteristic parameters.

[0025] Preferably, the step of acquiring the atmospheric environment parameter prediction set also includes: based on the atmospheric turbulence characteristic parameters and in combination with the three-dimensional refractive index mean distribution provided by the atmospheric refractive index disturbance field, simulating and calculating the beam path bending, intensity fluctuations and arrival angle fluctuations to generate the atmospheric environment parameter prediction set.

[0026] The present invention also provides an atmospheric refraction and waveguide environmental parameter detection and prediction system, comprising:

[0027] The spectral interferometry module uses a spectrometer to distribute the power of a broadband light source, forming a probe beam and a reference beam. The probe beam is guided through a preset open-atmosphere optical path, while the reference beam is guided through a stable medium with a known refractive index or a vacuum pipeline. The interference signal between the two beams is obtained and Fourier transform is performed on the interference signal to extract the phase difference value that varies with wavelength and obtain wavelength-phase difference mapping data.

[0028] The refractive index disturbance field reconstruction module extracts the phase difference values ​​at different wavelengths based on the wavelength-phase difference mapping data, establishes a linear equation system to solve the contribution of each component based on the differences in the refractive properties of dry air and water vapor for light of different wavelengths, sets up multiple sets of broadband light source transmitters and receivers in a specified area to form a cross-optical path network covering the monitoring area, records the integrated phase difference of each optical path, grids the monitoring area, adjusts the refractive index of each grid through iterative calculation, and simultaneously applies a minimum constraint on the total variable component until the residual error of the reconstructed object edge meets the preset threshold, thereby establishing the atmospheric refractive index disturbance field;

[0029] The absorption spectrum measurement module, based on tunable semiconductor laser emission, selects a first absorption line that responds to water vapor concentration and a second absorption line that responds to temperature, drives the laser to scan a preselected laser wavelength range, captures the laser absorption signal that passes through the atmosphere through a photodetector, performs digital phase-locked amplification on the signal to extract the second harmonic amplitude, and converts the path-integrated water vapor concentration and path-integrated temperature based on calibration data to obtain path-integrated temperature and humidity data;

[0030] The atmospheric environment prediction module applies a digital filter to filter out slowly changing background trends based on the path-integrated temperature and path-integrated water vapor concentration in the time series form in the path-integrated temperature and humidity data, obtains temperature and water vapor concentration pulsation sequences, calculates the autocorrelation function and cross-correlation function of the pulsation sequence, infers temperature structure parameters, humidity structure parameters and temperature and humidity covariance structure parameters based on path length information, and infers the evolution of atmospheric optical environment parameters in combination with the spatial refractive index distribution information provided by the atmospheric refractive index disturbance field to generate an atmospheric environment parameter prediction set.

[0031] Compared with the prior art, the advantages and positive effects of the present invention are:

[0032] The present invention uses a broadband light source to split the light into a probe beam and a reference beam. The probe beam is then directed through an open atmospheric path, while the reference beam is passed through a stable medium. The interference signal between the two beams is then Fourier transformed to extract wavelength phase difference mapping data. This method can capture subtle optical path variations caused by atmospheric refractive index disturbances. Compared to traditional single-point or single-path measurements, the use of broadband spectral information improves the sensitivity and measurement dimensionality of spatial inhomogeneities in the atmospheric refractive index. Furthermore, by utilizing the phase differences at different wavelengths in the wavelength phase difference mapping data and combining them with the known dispersion properties of dry air and water vapor, a linear equation system is established to solve their respective contributions. This effectively separates the main factors affecting the atmospheric refractive index, breaking away from the limitations of previous analyses that obfuscate the contributions of each component. Multiple sets of transmitter-receiver pairs are deployed within a region to form a cross-optical network, and the integrated phase difference of each path is recorded. The monitoring area is then gridded, and iterative calculations are used to adjust the grid refractive index, while applying a total variation minimum constraint. This allows for rapid and stable reconstruction of the atmospheric refractive index disturbance field, overcoming the problems of low reconstruction quality and blurred edges in traditional tomography under sparse sampling conditions, and obtaining information on the spatial distribution of the atmospheric refractive index. By combining a tunable semiconductor laser to select specific absorption lines for high-frequency scanning, and using digital lock-in amplification to extract the second harmonic amplitude and convert it into path-integrated temperature and humidity information, the method achieves simultaneous measurement of atmospheric temperature and water vapor concentration, providing a data foundation for capturing high-frequency dynamic processes such as atmospheric turbulence. The acquired path-integrated temperature and humidity data time series is digitally filtered to produce a pulsating sequence. Its autocorrelation and cross-correlation functions are then calculated and combined with path length to infer turbulent structure parameters. This enables quantitative assessment of atmospheric optical turbulence intensity, addressing the limitations of traditional methods in directly measuring turbulence parameters. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] Figure 1 Schematic diagram of the steps of the present invention. DETAILED DESCRIPTION

[0034] In order to make the purpose, technical solutions and advantages of the present invention more clearly understood, the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0035] See also Figure 1 The present invention provides a technical solution, a method for detecting and predicting atmospheric refraction and waveguide environmental parameters, comprising the following steps:

[0036] Based on the emission of a broadband light source, a spectrometer is used to distribute the power of the broadband light source beam to form a detection beam and a reference beam. The detection beam is guided through a preset open atmospheric optical path. The preset open atmospheric optical path is a spatial path that is planned before the start of the experiment or monitoring, connecting the broadband light source transmitter and the receiver. It has a straight geometric shape and is not less than 1 km long. The detection beam propagates in an open, uncontrolled real atmospheric environment. At the same time, the reference beam is guided through a stable medium with a known refractive index or a vacuum pipeline to obtain the interference signal of the two beams. The interference signal is Fourier transformed to extract the phase difference value that varies with wavelength to obtain wavelength-phase difference mapping data.

[0037] Based on the wavelength phase difference mapping data, the phase difference values ​​at different wavelengths are extracted. According to the differences in the refractive properties of dry air and water vapor for light of different wavelengths, a linear equation system is established to solve the contribution of each component. Multiple groups of broadband light source transmitters and receivers are set up in the specified area to form a cross-optical path network covering the monitoring area. The integrated phase difference of each optical path is recorded, and the monitoring area is gridded. The refractive index of each grid is adjusted through iterative calculation, and the minimum constraint of the total variable component is applied at the same time until the residual of the reconstructed object edge meets the preset threshold. The threshold is automatically determined by minimizing the reconstruction residual to establish the atmospheric refractive index disturbance field.

[0038] Based on the emission of a tunable semiconductor laser, the first absorption line that responds to water vapor concentration and the second absorption line that responds to temperature are selected. The laser is driven to scan the preselected laser wavelength range. The laser absorption signal passing through the atmosphere is captured by a photodetector. The signal is digitally phase-locked and amplified to extract the second harmonic amplitude. The path-integrated water vapor concentration and path-integrated temperature are converted according to the calibration data to obtain the path-integrated temperature and humidity data.

[0039] Based on the path-integrated temperature and path-integrated water vapor concentration in the form of time series in the path-integrated temperature and humidity data, a digital filter is applied to filter out the slowly changing background trend, and the temperature and water vapor concentration pulsation series are obtained. The autocorrelation function and cross-correlation function of the pulsation series are calculated. According to the path length information, the temperature structure parameters, humidity structure parameters and temperature and humidity covariance structure parameters are inferred. Combined with the spatial refractive index distribution information provided by the atmospheric refractive index disturbance field, the evolution of the atmospheric optical environment parameters is inferred to generate a prediction set of atmospheric environment parameters.

[0040] The steps for obtaining wavelength phase difference mapping data are as follows:

[0041] Based on the emission of a broadband light source, the spectrometer is controlled to adjust the power distribution ratio of the probe beam and the reference beam. The probe beam is calibrated to propagate along an open atmospheric optical path defined by predetermined coordinate points. The reference beam is coupled into a vacuum tube with controlled internal pressure and temperature. The beam collimation parameters and path geometric parameters are recorded to obtain a set of optical path configuration parameters.

[0042] Based on the optical path configuration parameter set, the emission of the probe beam and the reference beam are synchronously triggered. The two beams are configured to produce spatial interference fringes at the beam-combining point through the Michelson interferometer. The change of the interference fringes intensity over time or optical path difference scanning is captured, and the analog voltage signal is converted into a digital sequence through an analog-to-digital converter to obtain the interference signal sequence.

[0043] Based on the interference signal sequence, the collected digital sequence is Fourier transformed to obtain the spectrum representation of the signal. The peak position and phase value corresponding to each wavelength component are identified from the spectrum. By comparing with the reference arm calibration data, the variation of the phase difference between the detection light and the reference light caused by the atmospheric refractive index disturbance with the wavelength is calculated and extracted to obtain the wavelength phase difference mapping data.

[0044] Specifically, based on the emission of a broadband light source, the power distribution ratio of the detection beam and the reference beam is first adjusted by controlling a tunable neutral density filter or a polarization beam splitter or other spectroscopic elements. The initial setting can be 50:50, and then fine-tuned according to the signal-to-noise ratio of the interference signal. For example, if the detection beam is greatly attenuated in the atmosphere, the initial power ratio of the detection beam is appropriately increased. The goal is to make the light intensity of the two beams at the beam-combining point close to obtain high-contrast interference fringes. Subsequently, a four-quadrant detector or a CCD camera is used as feedback, and the detection beam is calibrated by controlling the precision two-dimensional electric translation stage and pitch rotation stage on which the detection light emission collimating lens is installed to ensure that it is accurately along a plurality of pre-measured ground control points (for example, points accurately calibrated by GPS or total station). ,…, ) is propagated along an open atmospheric optical path defined by the optical fiber. The sign of completion of calibration is that the offset of the center of the detection spot at the target point (such as the center of the farthest receiver target) is less than a preset value, which is determined according to the path length and the divergence angle of the light source. For example, for a 1 km path, the offset is controlled within 1 cm. At the same time, the reference beam is efficiently coupled into a vacuum pipeline with precisely controlled internal pressure and temperature through an optical fiber coupler. The pressure of the vacuum pipeline is maintained below 1000 by the connected vacuum pump and pressure sensor. Pascal level to ensure that its refractive index is close to vacuum (i.e. 1), and the temperature is stabilized at e.g. During this process, the collimation parameters of the light beam are recorded in detail, including the beam divergence angle (for example, the measured divergence angle is 0.5 milliradians), pointing stability (for example, the root mean square value of the light spot center shake within 10 minutes is recorded, which is required to be less than 5 microradians), and the geometric parameters of the path, including the precise three-dimensional coordinates of each predetermined coordinate point, the total length of the optical path (for example, the length measured by the laser rangefinder is 1052.34 meters), etc., to obtain the optical path configuration parameter set.

[0045] Based on the optical path configuration parameter set, a pulse signal generator or a digital delay generator is used to synchronously trigger the light sources of the detection beam and the reference beam (for example, the shutter or modulation signal of the light source is opened at the same time), ensuring that the time jitter of the emission of the two beams is controlled at the nanosecond level. For example, the synchronization error of the trigger signal is less than 1 nanosecond. Then, a standard Michelson interferometer configuration is used, which includes a 50:50 broadband beam splitter, a fixed reflector (for the reference optical arm), and a precisely movable reflector (for the detection optical arm. However, in this application, the detection optical arm is an open atmospheric path, and the reference optical arm usually has a built-in movable reflector). The optical path difference scanning device) and a beam combining element are used to make the detection beam passing through the atmospheric path and the reference beam passing through the vacuum pipe interfere at the beam combining point (usually another beam splitter or directly on the detector surface), thereby generating spatial interference fringes. If a spectrometer is used for detection, false-color interference fringes may be formed. If an optical path difference scan is performed, the change of the intensity of the central interference fringe with time or optical path difference scanning is captured. The optical path difference scan is achieved by controlling the position of the reference arm reflector through a precision piezoelectric ceramic driver (PZT). The scanning range covers at least the coherence length of several center wavelengths. For example, the scanning range is The scanning frequency is 100 Hz, and the generated interference light signal is received by a high-speed photodetector (for example, a silicon-based or indium gallium arsenide detector with a bandwidth greater than 1 MHz). The analog voltage signal output by the detector is converted into a digital sequence in real time through an analog-to-digital converter (ADC). The sampling rate of the ADC is set according to the scanning speed and the required resolution. For example, for a scanning frequency of 100 Hz and the desired phase resolution, the sampling rate is set to 10 MHz. The number of bits of the ADC (for example, 16 bits) ensures sufficient dynamic range and quantization accuracy to obtain the interference signal sequence.

[0046] Based on the interference signal sequence, digital signal processing technology is first applied to the collected digital sequence representing the intensity changes of the interference fringes. For example, baseline correction and noise filtering are first performed, such as using a high-pass filter to remove DC components or low-frequency drift, and then a window function (such as a Hanning window or a Blackman window) is applied to reduce spectral leakage. The fast Fourier transform (FFT) algorithm is then performed on the processed digital sequence to obtain the complex spectrum representation of the signal, namely the amplitude spectrum and phase spectrum. From the amplitude spectrum of the spectrum, the peaks corresponding to the wavelength components of the light source are identified. The position (frequency) of the peak is related to the wavelength (or wave number). The center wavelength corresponding to each peak is determined by the calibration spectrum of the light source, and the phase values ​​at these peak frequencies are extracted. , then, by comparing it with the previously obtained reference arm calibration data, the reference arm calibration data is obtained by placing the detection arm in a vacuum or a known stable medium, or replacing the detection arm with an optical element with known transfer characteristics, and performing the same interferometric measurement and Fourier transform processing to obtain the phase information , this calibration data reflects the fixed phase delay and dispersion characteristics introduced by the instrument itself and the reference optical path. Then, the phase difference between the detection light and the reference light caused by the atmospheric refractive index disturbance is calculated and extracted as a function of wavelength. The calculation formula is: ,in is a global phase constant, which can be determined by selecting the phase difference at a certain wavelength as the zero point or by other methods. This is the wavelength phase difference mapping data.

[0047] The steps to obtain the atmospheric refractive index disturbance field are:

[0048] Based on the wavelength phase difference mapping data, the phase difference measurement values ​​of multiple target wavelength points are uniformly selected from them. The refractive index dispersion coefficients of dry air and water vapor at each wavelength are used to construct an overdetermined linear equation system, where the unknowns are the dry air density contribution and water vapor density contribution of the path integral, and the refractive component equation is established.

[0049] Based on the refractive component equation, pairs of broadband light source transmitting units and spectrum acquisition units are deployed at multiple points around the area to be measured. The connections between the transmitting and receiving units are planned to form a cross-optical path network. The spectral phase difference is measured independently for each optical path, and the integrated phase difference data of all optical paths is summarized to obtain the cross-path integrated phase set.

[0050] Based on the cross-path integral phase set, the monitoring space is discretized into a three-dimensional voxel grid, and an initial refractive index estimate is assigned to each voxel. The voxel refractive index is adjusted according to the difference between the measured values ​​of each optical path and the current model calculated value. At the same time, a total variation regularization term is introduced to constrain the smoothness of the iterative solution until the residual reaches the preset accuracy, and the atmospheric refractive index disturbance field is established.

[0051] Specifically, based on the wavelength phase difference mapping data , and evenly select multiple target wavelength points at equal wavelength intervals or equal wavenumber intervals. For example, if the spectrum range of the broadband light source is 600 nm to 1000 nm, a point can be selected every 20 nm, and the phase difference measurement values ​​of 21 wavelength points in total can be selected. (in , ), then, using the known dry air and water vapor at each selected wavelength The refractive index dispersion coefficient calculated using the empirical formula for refractive index dispersion (e.g., Ciddor formula or Owens formula) is denoted as and , these coefficients describe the refractive index contribution of unit density of dry air and water vapor at different wavelengths. Then, an overdetermined linear equation system is constructed. The basic principle is that the path integral phase difference is related to the path integral refractive index, and the refractive index is a linear superposition of the contributions of dry air and water vapor. For each optical path, its path integral phase difference is ,in is the wavelength at point s on the path The atmospheric refractive index minus 1 can be expressed as ,in and are the densities of dry air and water vapor, respectively. Therefore, for the jth wavelength, we have the equation: , where the unknown is the path-integrated dry air density contribution along the entire optical path and path-integrated water vapor density contribution Since there are M wavelength points of measurement data (M>2, that is, the number of equations is greater than the number of unknowns), an overdetermined linear equation system is formed. The least squares method is used to solve the equation system and we get and The optimal estimate of , this set of equations is the established refractive component equation.

[0052] Based on the ability of the single path integral dry air and water vapor contribution obtained by solving the refractive component equation, a total of 8 stations are deployed around the area to be measured, such as the four corner points and the midpoints of the four sides of a square area with a side length of 1 km. Each station is equipped with a broadband light source transmitting unit and a spectrum acquisition unit, or is configured as a transmitting unit or a receiving unit only. By adjusting the orientation of each unit, multiple optical path connections between the transmitting unit and the receiving unit are planned and established to form a cross-optical path network covering the monitoring area. For example, if 4 transmitting units and 4 receiving units are deployed, up to 16 independent or partially overlapping optical paths can be formed to ensure that the optical paths form dense cross-coverage in the monitoring area to improve spatial resolution. For each independent optical path in this network (for example, from the transmitter To the receiver Path ), the aforementioned spectral phase difference measurement process is repeated independently, that is, the wavelength phase difference mapping data of the optical path is obtained, and the integral dry air density contribution and the integral water vapor density contribution of the path are calculated using the refractive component equation, or the integral phase difference value of each wavelength is directly used, and then all the The integrated phase difference data measured on the optical paths (or the integrated refractive index contribution data calculated therefrom) are used to form a data set containing each optical path and its corresponding measurement value, and a cross-path integrated phase set is obtained.

[0053] Based on the cross-path integral phase set, the three-dimensional monitoring space (for example, a space of 1 km*1 km*0.5 km) is first discretized into a regular three-dimensional voxel grid (voxels). The size of the voxel is determined according to the desired resolution and computing resources. For example, the size of each voxel is 20 meters*20 meters*10 meters. Assign an initial refractive index estimate , the initial value can be set to the refractive index calculated based on the standard atmospheric model, or the average refractive index obtained based on historical data of the same period. Then, the iterative calculation process begins. In the i-th iteration, for each light path p, according to the current refractive index distribution of each voxel , calculate the theoretical integral phase difference (or integral refractive index) of the optical path ,in is the optical path p in the voxel The calculated value is compared with the actual measured value of the optical path. Compare and get the residual Based on these residuals, the algebraic reconstruction technique (ART) or the simultaneous iterative reconstruction technique (SIRT) algorithm is used to adjust the refractive index value of each voxel. For example, the update rule of SIRT is ,in is the total length of the optical path p, is the relaxation factor, which is usually between 0.1 and 1.0, for example, 0.5. At the same time, in order to ensure the stability and physical rationality of the solution, the total variation regularization term is introduced as a constraint, which penalizes the refractive index gradient in the solution. norm, tends to produce smooth regions with clear boundaries, and its objective function is ,in is the regularization parameter, whose value is determined by cross-validation or L-curve method. For example, it can be initially set to 0.01, and the iterative process continues until the residual root mean square value of all light paths is Less than a preset accuracy threshold, which is set according to the measurement noise level and the desired reconstruction accuracy, for example, when the RMSE is less than one refractive index unit (corresponding to an N value of 0.1), or the change in the refractive index field between successive iterations is less than a certain minimum value (for example, the maximum absolute value of the change in the refractive index of all voxels is less than ), the iteration stops, and the refractive index distribution of each element obtained at this time is the established atmospheric refractive index disturbance field.

[0054] The steps for obtaining path integral temperature and humidity data are as follows:

[0055] Control the operating temperature and injection current of the laser, select and stably output a first near-infrared absorption line that is sensitive to changes in water vapor concentration, and a second absorption line that is sensitive to changes in atmospheric temperature, set the parameters for periodic scanning of the laser wavelength at the center of the spectrum line, and obtain a laser scanning parameter set;

[0056] Based on the laser scanning parameter set, the modulated laser beam output by the driving laser passes through the target atmospheric path, and after filtering out the background light, it is received by the photodetector. The absorption signal output by the detector is amplified, demodulated, and the amplitude data points of the second harmonic signal are extracted to obtain the harmonic amplitude of the absorption signal.

[0057] The step of acquiring the path-integrated temperature and humidity data also includes: based on the harmonic amplitude of the absorption signal, using the quantitative relationship model between the second harmonic amplitude obtained in advance through standard gas calibration and the gas concentration and temperature, the second harmonic amplitude of the two measured spectral lines is converted into path-integrated water vapor concentration values ​​and path-integrated temperature values ​​respectively, forming a time-synchronized measurement data sequence to obtain path-integrated temperature and humidity data.

[0058] Specifically, the operating temperature and injection current of the laser are controlled, and a first absorption line that is sensitive to changes in water vapor concentration and has a suitable absorption intensity in the near-infrared band is selected, such as the absorption line of water vapor near 1392.53 nanometers. At the same time, a second absorption line that is sensitive to changes in atmospheric temperature is selected, such as an absorption line in the oxygen A band near 760 nanometers that has a significant temperature response, or another water vapor absorption line with a different low-level transition energy is selected. The temperature of the laser chip is stabilized at a preset value through a temperature control unit. For example, for a distributed feedback (DFB) laser, the operating temperature is set to , the temperature stability target The upper limit of the allowable temperature drift is calculated based on the laser wavelength tuning coefficient (for example, 0.08nm / ℃) and the required wavelength stability (for example, less than 1 / 100 of the absorption line width. If the line width is 0.01nm, the wavelength stability is better than 0.0001nm). The laser drive power supply controls its injection current, for example, it is set to mA, its stability target The mA is determined based on the current tuning coefficient and the same wavelength stability requirements, and then the parameters of the laser output wavelength are set to perform periodic scanning around the center of the selected absorption spectrum, including the scanning center wavelength (i.e. the center wavelength of the spectrum line). ), the scanning amplitude can be set to 3 to 5 times the half-width of the spectrum line. If the half-width of the spectrum line is 0.02 nanometers, the scanning amplitude can be set to Nanometers, and scanning frequency, such as using a 1 kHz triangle wave or sawtooth wave for scanning. This frequency selection needs to be much higher than the frequency of atmospheric turbulence changes but lower than the higher frequency sine wave used for wavelength modulation. These selected spectral line wavelengths, operating temperature and current setting values, and scanning parameters (center, amplitude, frequency, waveform) together constitute the laser scanning parameter set.

[0059] Based on the laser scanning parameter set, the scanning center wavelength, scanning amplitude and scanning frequency set therein are specifically used to drive the tunable semiconductor laser (such as DFB laser) to output laser light, and at the same time, a high-frequency sinusoidal modulation current (such as frequency 1) is superimposed on the slow scanning current (such as 1 kHz triangle wave). kHz, the modulation depth corresponds to a wavelength modulation amplitude of about 2.2 times the spectral line width), making the output wavelength of the laser After passing through the collimation system, the modulated laser beam passes through the predetermined target atmospheric path. At the receiving end, a narrowband interference filter with a central wavelength matching the laser operating wavelength and a bandwidth of, for example, 1 nanometer is used to preliminarily filter the incident light to reduce the influence of solar background light and other stray light. The filtered laser light is received by a photodetector (such as an indium gallium arsenide PIN photodiode for the near-infrared band) and converted into a photocurrent signal. The photocurrent signal is first converted into a voltage signal through a transimpedance amplifier (TIA) and preliminarily amplified. The gain of the amplifier is dynamically adjusted according to the signal strength and the input range of the subsequent analog-to-digital converter, for example, so that the absorption signal peak occupies 50% to 80% of the ADC dynamic range. Subsequently, the voltage signal containing the absorption information is input to a digital lock-in amplifier. The reference signal frequency of the lock-in amplifier is set to twice the high-frequency sinusoidal modulation, that is, kHz, by adjusting the reference phase of the lock-in amplifier until the in-phase component of the second harmonic signal reaches a maximum (or the orthogonal component reaches a minimum), extracting and recording the sequence of data points in which the amplitude of the second harmonic signal (2f signal) changes with time (i.e., with the scanning wavelength) during the slow wavelength scanning process, the harmonic amplitude of the absorption signal is obtained.

[0060] The step of obtaining the path integral temperature and humidity data also includes: based on the absorption signal harmonic amplitude, that is, the curve of the second harmonic signal amplitude versus scanning wavelength obtained for the water vapor absorption spectrum and the temperature sensitive absorption spectrum, first extracting its peak value from each curve , and then use the quantitative relationship model established in advance through the standard gas calibration experiment. The model is achieved by connecting the laser system to a gas chamber filled with a standard gas of known concentration, temperature and pressure, changing the gas concentration in the gas chamber (for example, for water vapor, by controlling the water source with different saturated vapor pressures, a gas with a relative humidity of 0% to 90% is generated, corresponding to a water vapor concentration range of, for example, from 0 to ppmv) and temperature (for example, the gas chamber temperature is controlled in the range of 5°C to 45°C by a temperature-controlled jacket, with a step of 5°C), and the second harmonic peak value under different conditions is recorded. , for water vapor concentration, establish The polynomial fitting relationship of , where the coefficient It is obtained by fitting the calibration data points using the least squares method, for example (For example, the unit of the second harmonic amplitude is volts), P is the average pressure of the measurement path, is the reference temperature during calibration. For the path integration temperature, if a single temperature sensitive spectrum is used, then The relationship between the two and the temperature T can be obtained by looking up the table or the inverse function method, or by using two spectral lines with different low energy levels (such as the spectral line pair of water vapor). ), then its second harmonic peak ratio Strongly correlated with temperature, establishing relationships, such as ,coefficient Also obtained by calibration, e.g. , substitute the second harmonic peak value (or ratio) of the water vapor spectrum line and the second harmonic peak value (or ratio) of the temperature sensitive spectrum line (or spectrum line pair) measured in real time on site into these calibration models, calculate the path-integrated water vapor concentration value and path-integrated temperature value at that moment respectively, and record these values ​​together with the corresponding timestamps to form a time-synchronized measurement data sequence to obtain path-integrated temperature and humidity data.

[0061] The steps for obtaining the atmospheric environment parameter prediction set are:

[0062] Based on the multi-point time sampling data of path-integrated temperature and path-integrated water vapor concentration in the path-integrated temperature and humidity data, each time series is subjected to Butterworth high-pass filtering to separate the fluctuation components caused by atmospheric turbulence and obtain the temperature and humidity pulse value series.

[0063] Based on the temperature and humidity pulsation value series, the autocovariance function of the temperature pulsation time series, the autocovariance function of the water vapor concentration pulsation time series, and the cross-covariance function between the two are calculated. The temperature structure parameters, humidity structure parameters and temperature and humidity covariance structure parameters are inferred from the zero-point delay value of the covariance function to establish the atmospheric turbulence characteristic parameters;

[0064] Based on the characteristic parameters of atmospheric turbulence and combined with the three-dimensional refractive index mean distribution provided by the atmospheric refractive index disturbance field, the beam path bending, intensity fluctuations and arrival angle fluctuations are simulated and calculated to generate a prediction set of atmospheric environment parameters.

[0065] Specifically, based on the path integral temperature in the path integral temperature and humidity data and path-integrated water vapor concentration Multi-point time sampling data, where Represents discrete sampling moments, such as sampling once per second. For each complete time series (for example, temperature data and water vapor concentration data for one hour), a digital Butterworth high-pass filter is independently applied for processing. The filter is designed as a fourth-order Butterworth filter. The Butterworth filter is selected because it has the most flat amplitude-frequency response in the passband and its cutoff frequency is The cutoff frequency is set based on the distinction between rapid fluctuations caused by atmospheric turbulence and slow background trends caused by the evolution of weather systems or diurnal variations. For example, if the focus is on turbulence with a time scale from a few seconds to more than ten minutes, the cutoff frequency It can be set to 0.001 Hz, which corresponds to a period of about 16.7 minutes. This means that slow changes with a period longer than 16.7 minutes will be filtered out, while fluctuations with a period shorter than this will be retained. The cutoff frequency Hertz is determined based on the typical average wind speed in the target monitoring area (e.g. 5 m / s) and the turbulence scale of interest (e.g. atmospheric structure trends greater than 5 km need to be filtered out), and is calculated as follows: , where U is the average wind speed, is the maximum scale to be filtered out, e.g. , the filtering operation transforms the original time series Convert to temperature pulsation sequence , and the original water vapor concentration time series Converted to water vapor concentration pulsation series ,in and The low-frequency components are removed by high-pass filtering, thereby separating the fast-fluctuating components dominated by atmospheric turbulence and obtaining a series of temperature and humidity pulsation values.

[0066] Based on the temperature and humidity pulsation value series, that is, the temperature pulsation time series and water vapor concentration pulsation time series First, calculate the statistical characteristics of these pulsation series, including the calculation of the autocovariance function of the temperature pulsation time series , the autocovariance function of the water vapor concentration pulsation time series , and the cross-covariance function between temperature fluctuations and water vapor concentration fluctuations ,in is the time delay, angle brackets represents the time average, and then, from the zero time lag values ​​of these covariance functions, i.e. (temperature fluctuation variance), (variance of water vapor concentration fluctuations), and (temperature and humidity pulsation covariance), the structural parameters of atmospheric turbulence are calculated, specifically, the temperature structural parameters , humidity structure parameters , and temperature and humidity covariance structure parameters (structural parameters, not functions) are estimated by the following relationship: ,as well as , where A is a constant related to the turbulence spectrum, ranging from 0.1 to 1.0. Here, based on the von Karman spectrum, for example, A can be taken as 0.5, is the outer scale of the turbulence of the corresponding physical quantity. Its value is set empirically or obtained from the product of the integration time scale of the covariance function and the average wind speed. For example, if the average wind speed is 5 m / s and the integration time scale is 20 seconds, the outer scale Estimated to be 100 meters, if measured ,but , establish the atmospheric turbulence characteristic parameters.

[0067] Based on the atmospheric turbulence characteristic parameters established in the previous steps, namely the temperature structure parameters , humidity structure parameters , and temperature and humidity covariance structure parameters , and combined with the three-dimensional refractive index mean distribution in the atmospheric refractive index disturbance field provided by broadband light source interferometry and tomographic inversion technology First, use these parameters to calculate the three-dimensional refractive index structure parameter field , and its calculation formula is , where P is the atmospheric pressure, T is the absolute temperature (the spatial distribution can be obtained from the path-integrated temperature and the standard atmospheric profile), is a known coefficient related to the wavelength of light, for example, for the visible light band, Then, a beam propagation numerical simulation method is used, such as the paraxial approximation (PWE) based on the Helmholtz equation combined with the split-step Fourier transform, to simulate the beam propagation in the three-dimensional refractive index distribution. and three-dimensional refractive index structure parameter field The process of propagation in the atmosphere, for the beam path bending, is calculated by solving the Eikonal equation or considering the refractive index gradient in ray tracing, for the intensity fluctuation (scintillation index ), which is obtained by calculating the normalized intensity variance in the PWE simulation, or by using the integral formula based on the Rytov approximation (for spherical waves under weak undulation conditions), where is the wave number, L is the path length, and for the arrival angle fluctuation , obtained by calculating the angular displacement variance of the beam centroid on the receiving plane, or using the formula (where D is the receiving aperture) by simulating and calculating multiple preset virtual optical paths or specific directions of interest, a set of parameters including the beam path bending amount, beam expansion, scintillation index, arrival angle fluctuation, etc. of each path is generated to form a prediction set of atmospheric environment parameters.

[0068] The above are merely preferred embodiments of the present invention and do not limit the present invention in any other form. Any technician familiar with the profession may use the technical content disclosed above to change or modify it into an equivalent embodiment with equivalent changes and apply it to other fields. However, any simple modification, equivalent change and modification made to the above embodiment based on the technical essence of the present invention without departing from the content of the technical solution of the present invention shall still fall within the scope of protection of the technical solution of the present invention.

Claims

1. A method for detecting and predicting atmospheric refraction and waveguide environmental parameters, characterized in that: The following steps are involved: Based on the emission of a broadband light source, a spectrometer is used to distribute the power of the broadband light source beam to form a detection beam and a reference beam. The detection beam is guided through a preset open atmospheric optical path, while the reference beam is guided through a stable medium with a known refractive index or a vacuum pipeline to obtain the interference signal of the two beams. The interference signal is then Fourier transformed to extract the phase difference value that varies with wavelength and obtain wavelength-phase difference mapping data. Based on the wavelength-phase difference mapping data, the phase difference values ​​at different wavelengths are extracted. Based on the differences in the refractive properties of dry air and water vapor for light of different wavelengths, a linear equation system is established to solve the contribution of each component. Multiple sets of broadband light source transmitters and receivers are set up in a specified area to form a cross-optical path network covering the monitoring area. The integrated phase difference of each optical path is recorded, and the monitoring area is gridded. The refractive index of each grid is adjusted through iterative calculation, and a minimum constraint on the total variable component is applied at the same time until the residual error of the reconstructed object edge meets the preset threshold, thereby establishing an atmospheric refractive index disturbance field. The steps for acquiring the wavelength phase difference mapping data are: Based on the emission of a broadband light source, the spectrometer is controlled to adjust the power distribution ratio of the probe beam and the reference beam. The probe beam is calibrated to propagate along an open atmospheric optical path defined by predetermined coordinate points. The reference beam is coupled into a vacuum tube with controlled internal pressure and temperature. The beam collimation parameters and path geometric parameters are recorded to obtain a set of optical path configuration parameters. Based on the optical path configuration parameter set, the emission of the probe beam and the reference beam is synchronously triggered, and the two beams are configured to generate spatial interference fringes at the beam-combining point through a Michelson interferometer, and the change of the interference fringes intensity over time or optical path difference scanning is captured, and the analog voltage signal is converted into a digital sequence through an analog-to-digital converter to obtain an interference signal sequence; Based on the interference signal sequence, the collected digital sequence is Fourier transformed to obtain a spectrum representation of the signal, the peak position and phase value corresponding to each wavelength component are identified from the spectrum, and the variation of the phase difference between the detection light and the reference light caused by the atmospheric refractive index disturbance as a function of wavelength is calculated and extracted by comparing with the reference arm calibration data to obtain wavelength phase difference mapping data; The steps for obtaining the atmospheric refractive index disturbance field are: Based on the wavelength phase difference mapping data, phase difference measurement values ​​of multiple target wavelength points are uniformly selected therefrom, and an overdetermined linear equation system is constructed using the refractive index dispersion coefficients of dry air and water vapor at each wavelength, where the unknowns are the dry air density contribution and the water vapor density contribution of the path integral, to establish a refractive component equation; Based on the refractive component equation, pairs of broadband light source transmitting units and spectrum acquisition units are deployed at multiple points around the area to be measured. The connections between the transmitting and receiving units are planned to form a cross-optical path network. The spectral phase difference is measured independently for each optical path, and the integrated phase difference data of all optical paths is summarized to obtain a cross-path integrated phase set. Based on the cross-path integral phase set, the monitoring space is discretized into a three-dimensional voxel grid, and an initial refractive index estimate is assigned to each voxel. The voxel refractive index is adjusted according to the difference between the measured values ​​of each optical path and the calculated value of the current model. At the same time, a total variation regularization term is introduced to constrain the smoothness of the iterative solution until the residual reaches the preset accuracy, and the atmospheric refractive index disturbance field is established.

2. The method for detecting and predicting atmospheric refraction and waveguide environmental parameters according to claim 1, characterized in that: The method further comprises: Based on the emission of a tunable semiconductor laser, the first absorption line that responds to water vapor concentration and the second absorption line that responds to temperature are selected. The laser is driven to scan the preselected laser wavelength range. The laser absorption signal passing through the atmosphere is captured by a photodetector. The signal is digitally phase-locked and amplified to extract the second harmonic amplitude. The path-integrated water vapor concentration and path-integrated temperature are converted according to the calibration data to obtain the path-integrated temperature and humidity data. Based on the path-integrated temperature and path-integrated water vapor concentration in the form of time series in the path-integrated temperature and humidity data, a digital filter is applied to filter out slowly changing background trends to obtain temperature and water vapor concentration pulsation sequences, and the autocorrelation function and cross-correlation function of the pulsation sequences are calculated. Based on the path length information, the temperature structure parameters, humidity structure parameters and temperature and humidity covariance structure parameters are inferred. Combined with the spatial refractive index distribution information provided by the atmospheric refractive index disturbance field, the evolution of the atmospheric optical environment parameters is inferred to generate an atmospheric environment parameter prediction set.

3. The method for detecting and predicting atmospheric refraction and waveguide environmental parameters according to claim 1, characterized in that: The steps for obtaining the path integrated temperature and humidity data are as follows: Control the operating temperature and injection current of the laser, select and stably output a first near-infrared absorption line that is sensitive to changes in water vapor concentration, and a second absorption line that is sensitive to changes in atmospheric temperature, set the parameters for periodic scanning of the laser wavelength at the center of the spectrum line, and obtain a laser scanning parameter set; Based on the laser scanning parameter set, the modulated laser beam output by the driving laser passes through the target atmospheric path, is received by the photodetector after filtering out the background light, the absorption signal output by the detector is amplified, and the amplitude data points of the second harmonic signal are demodulated and extracted to obtain the harmonic amplitude of the absorption signal.

4. The method for detecting and predicting atmospheric refraction and waveguide environmental parameters according to claim 3, characterized in that: The step of acquiring the path-integrated temperature and humidity data further includes: based on the harmonic amplitude of the absorption signal, using a quantitative relationship model between the second harmonic amplitude, gas concentration, and temperature obtained in advance through standard gas calibration, converting the second harmonic amplitudes of the two measured spectral lines into path-integrated water vapor concentration values ​​and path-integrated temperature values, respectively, to form a time-synchronized measurement data sequence, and acquiring the path-integrated temperature and humidity data.

5. The method for detecting and predicting atmospheric refraction and waveguide environmental parameters according to claim 2, characterized in that: The steps for obtaining the atmospheric environment parameter prediction set are: Based on the multi-point time sampling data of path-integrated temperature and path-integrated water vapor concentration in the path-integrated temperature and humidity data, each time series is subjected to Butterworth high-pass filtering to separate the fluctuation components caused by atmospheric turbulence and obtain a temperature and humidity pulse value series; Based on the temperature and humidity pulsation value sequence, the autocovariance function of the temperature pulsation time series, the autocovariance function of the water vapor concentration pulsation time series, and the cross-covariance function between the two are calculated, and the temperature structure parameters, humidity structure parameters and temperature and humidity covariance structure parameters are inferred from the zero-point delay value of the covariance function to establish the atmospheric turbulence characteristic parameters.

6. The method for detecting and predicting atmospheric refraction and waveguide environmental parameters according to claim 5, characterized in that: The step of acquiring the atmospheric environment parameter prediction set also includes: based on the atmospheric turbulence characteristic parameters and in combination with the three-dimensional refractive index mean distribution provided by the atmospheric refractive index disturbance field, simulating and calculating the beam path bending, intensity fluctuations and arrival angle fluctuations to generate the atmospheric environment parameter prediction set.

7. The atmospheric refraction and waveguide environment parameter detection and prediction system according to the atmospheric refraction and waveguide environment parameter detection and prediction method according to any one of claims 1 to 6, characterized in that: include: The spectral interferometry module uses a spectrometer to distribute the power of a broadband light source, forming a probe beam and a reference beam. The probe beam is guided through a preset open-atmosphere optical path, while the reference beam is guided through a stable medium with a known refractive index or a vacuum pipeline. The interference signal between the two beams is obtained and Fourier transform is performed on the interference signal to extract the phase difference value that varies with wavelength and obtain wavelength-phase difference mapping data. The refractive index disturbance field reconstruction module extracts the phase difference values ​​at different wavelengths based on the wavelength-phase difference mapping data, establishes a linear equation system to solve the contribution of each component based on the differences in the refractive properties of dry air and water vapor for light of different wavelengths, sets up multiple sets of broadband light source transmitters and receivers in a specified area to form a cross-optical path network covering the monitoring area, records the integrated phase difference of each optical path, grids the monitoring area, adjusts the refractive index of each grid through iterative calculation, and simultaneously applies a minimum constraint on the total variable component until the residual error of the reconstructed object edge meets the preset threshold, thereby establishing the atmospheric refractive index disturbance field; The absorption spectrum measurement module, based on tunable semiconductor laser emission, selects a first absorption line that responds to water vapor concentration and a second absorption line that responds to temperature, drives the laser to scan a preselected laser wavelength range, captures the laser absorption signal that passes through the atmosphere through a photodetector, performs digital phase-locked amplification on the signal to extract the second harmonic amplitude, and converts the path-integrated water vapor concentration and path-integrated temperature based on calibration data to obtain path-integrated temperature and humidity data; The atmospheric environment prediction module applies a digital filter to filter out slowly changing background trends based on the path-integrated temperature and path-integrated water vapor concentration in the time series form in the path-integrated temperature and humidity data, obtains temperature and water vapor concentration pulsation sequences, calculates the autocorrelation function and cross-correlation function of the pulsation sequence, infers temperature structure parameters, humidity structure parameters and temperature and humidity covariance structure parameters based on path length information, and infers the evolution of atmospheric optical environment parameters in combination with the spatial refractive index distribution information provided by the atmospheric refractive index disturbance field to generate an atmospheric environment parameter prediction set.

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