Method and device for detecting and predicting atmospheric refraction and waveguide environmental parameters

Abstract

The invention relates to the cross technical field of atmospheric science and communication technology, in particular to an atmospheric refraction and waveguide environmental parameter detection and prediction method and device, and the method comprises the following steps: carrying out the power distribution of a light beam of a broadband light source through employing a light splitting element based on the emission of the broadband light source, and forming a detection light beam and a reference light beam, and guiding the detection light beam to pass through a preset open atmosphere optical path, and guiding the reference light beam to pass through a known refractive index stabilizing medium or a vacuum pipeline. The detection light beam and the reference light beam are formed through light splitting of the broadband light source, the detection light beam penetrates through the open atmosphere path, the reference light beam passes through the stable medium, Fourier transform is carried out on interference signals of the two light beams to extract wavelength phase difference mapping data, and tiny optical path change caused by atmospheric refractive index disturbance can be captured. Compared with the traditional single-point or single-path measurement, the sensing sensitivity and the measurement dimension of the atmospheric refractive index spatial nonuniformity are improved by using the broadband spectral information.

Description

Technical Field

[0001] The present invention relates to the cross - technical 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 the prior art, although spectral analysis can obtain the composition of substances, in an open - air path, rapid spatio - temporal fluctuations of the refractive index caused by factors such as changes in trace gas concentration, temperature gradient, 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, and cannot meet the refined requirements for the atmospheric optical environment. For another example, traditional refractive index measurement methods, such as Abbe refractometers, are mainly used for single - point refractive index determination of liquid or solid samples and are difficult to be directly applied to tomographic imaging of the atmospheric refractive index field in a vast space. Therefore, improvements are needed. Summary of the Invention

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

[0004] To achieve the above object, the present invention adopts the following technical solution. A method for detecting and predicting atmospheric refraction and waveguide environmental parameters includes the following steps: Based on the emission of a broadband light source, a beam splitter 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 - air optical path, and at the same time, the reference beam is guided through a stable medium with a known refractive index or a vacuum pipeline. The interference signal of the two beams is obtained, and the interference signal is subjected to Fourier transform processing to extract the phase difference varying with wavelength, and wavelength - phase difference mapping data is obtained. Based on the wavelength - phase difference mapping data, the phase difference values at different wavelengths are extracted. According to the differences in the refractive characteristics of dry air and water vapor for light of different wavelengths, a linear equation system is established to solve the contribution amounts of each component. Multiple groups of broadband light source transmitters and receivers are set in a specified area to form a cross - optical - path network covering the monitoring area. The integral phase difference of each optical path is recorded, the monitoring area is gridded, and the refractive index of each grid is adjusted through iterative calculation while applying the minimum total variation component constraint until the residual of the reconstructed object edge meets the preset threshold, and an atmospheric refractive index perturbation field is established.

[0005] Preferably, the method further includes: Based on the emission of a tunable semiconductor laser, select the first absorption line that responds to water vapor concentration and the second absorption line that responds to temperature. Drive the laser to scan the preselected laser wavelength range, capture the laser absorption signal passing through the atmosphere by a photodetector, digitally lock-in amplify the signal to extract the second harmonic amplitude, and convert the path-integrated water vapor concentration and path-integrated temperature 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, apply a digital filter to filter out the slowly varying background trend, obtain the pulsation sequences of temperature and water vapor concentration, calculate the autocorrelation function and cross-correlation function of the pulsation sequences, and infer the temperature structure parameter, humidity structure parameter, and temperature-humidity covariance structure parameter according to the path length information. Combine the spatial refractive index distribution information provided by the atmospheric refractive index perturbation field to infer the evolution of atmospheric optical environment parameters and generate a set of predicted atmospheric environment parameters.

[0006] Preferably, the steps for obtaining the wavelength phase difference mapping data are as follows: Based on the emission of a broadband light source, control the beam splitting element to adjust the power distribution ratio of the probe beam and the reference beam, calibrate the probe beam so that it propagates along the open atmospheric optical path defined by the predetermined coordinate points, and couple the reference beam into a vacuum pipeline with controlled internal pressure and temperature. Record the beam collimation parameters and path geometry parameters to obtain a set of optical path configuration parameters; Based on the set of optical path configuration parameters, synchronously trigger the emission of the probe beam and the reference beam. Through the configuration of a Michelson interferometer, make the two beams generate spatial interference fringes at the beam combination point, capture the change of the interference fringe intensity with time or optical path difference scanning, and convert the analog voltage signal into a digital sequence through an analog-to-digital converter to obtain an interference signal sequence; Based on the interference signal sequence, perform a Fourier transform on the collected digital sequence to obtain the spectral representation of the signal. Identify the peak positions and phase values corresponding to each wavelength component from the spectrum, and calculate and extract the change amount of the phase difference between the probe light and the reference light caused by the atmospheric refractive index perturbation with respect to the wavelength by comparing with the calibration data of the reference arm to obtain the wavelength phase difference mapping data.

[0007] Preferably, the steps for obtaining the atmospheric refractive index perturbation field are as follows: Based on the wavelength phase difference mapping data, uniformly select the phase difference measurement values at multiple target wavelength points therefrom, and use the refractive index dispersion coefficients of dry air and water vapor at each wavelength to construct an overdetermined linear equation system, where the unknowns are the path-integrated dry air density contribution and water vapor density contribution, and establish a refractive component equation; Based on the refractive component equation, pairs of broadband light source transmitting units and spectrum collection units are deployed at multiple points around the area to be measured, and the connection between the transmitting and receiving units is planned to form a cross optical path network. The spectral phase difference of each optical path is measured independently, and the integral phase difference data of all optical paths are summarized to obtain the cross-path integral 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 a preset accuracy, and the atmospheric refractive index disturbance field is established.

[0008] Preferably, the steps for acquiring the path integrated temperature and humidity data are: Control the operating temperature and injection current of the laser, select and stably output the first near-infrared absorption line that is sensitive to changes in water vapor concentration, and the 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 photoelectric detector 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.

[0009] Preferably, 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 amplitudes of the two measured spectral lines are converted 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.

[0010] Preferably, the steps of acquiring 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 pulsation 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.

[0011] Preferably, the step of obtaining the atmospheric environment parameter prediction set further 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 perturbation field, simulating and calculating the beam path bending, intensity fluctuation, and arrival angle fluctuation to generate the atmospheric environment parameter prediction set.

[0012] The present invention also provides an atmospheric refraction and waveguide environment parameter detection and prediction system, including: A spectral interference measurement module, based on the emission of a broadband light source, uses a beam splitting element to distribute the power of the broadband light source beam to form a detection beam and a reference beam, guides the detection beam through a preset open atmospheric optical path, and at the same time guides the reference beam through a stable medium with a known refractive index or a vacuum pipeline, obtains the interference signal of the two beams, and performs Fourier transform processing on the interference signal to extract the phase difference varying with the wavelength to obtain wavelength phase difference mapping data; A refractive index perturbation field reconstruction module, based on the wavelength phase difference mapping data, extracts the phase difference values at different wavelengths, establishes a linear equation system according to the refractive characteristics differences of dry air and water vapor for light rays of different wavelengths to solve the contribution amounts of each component, sets multiple groups of broadband light source transmitters and receivers in a specified area to form a cross optical path network covering the monitoring area, records the integral phase difference of each optical path, grids the monitoring area, adjusts the refractive index of each grid through iterative calculation, and at the same time applies the minimum total variation component constraint until the residual of the reconstructed object edge meets the preset threshold to establish the atmospheric refractive index perturbation field; An absorption spectrum measurement module, based on the emission of a tunable semiconductor laser, selects a first absorption line responsive to the water vapor concentration and a second absorption line responsive to the temperature, drives the laser to scan a preselected laser wavelength range, captures the laser absorption signal passing through the atmosphere through a photodetector, performs digital lock-in amplification on the signal to extract the second harmonic amplitude, and converts the path integral water vapor concentration and the path integral temperature according to the calibration data to obtain the path integral temperature and humidity data; An atmospheric environment prediction module, based on the path integral temperature and the path integral water vapor concentration in the form of a time series in the path integral temperature and humidity data, uses a digital filter to filter out the slow-changing background trend to obtain the temperature and water vapor concentration pulsation sequences, calculates the autocorrelation function and the cross-correlation function of the pulsation sequences, infers the temperature structure parameter, the humidity structure parameter, and the temperature-humidity covariance structure parameter according to the path length information, and in combination with the spatial refractive index distribution information provided by the atmospheric refractive index perturbation field, infers the evolution of the atmospheric optical environment parameters to generate the atmospheric environment parameter prediction set.

[0013] Compared with the prior art, the advantages and positive effects of the present invention are as follows: The present invention forms a detection beam and a reference beam by splitting the broadband light source, makes the detection beam pass through an open atmospheric path while the reference beam passes through a stable medium, and then performs Fourier transform on the interference signal of the two beams to extract the wavelength phase difference mapping data, which can capture the subtle optical path changes caused by the atmospheric refractive index perturbation. Compared with the traditional single-point or single-path measurement, by using the broadband spectral information, the sensitivity of perceiving the spatial inhomogeneity of the atmospheric refractive index and the measurement dimension are improved. Further, by using the phase value differences at different wavelengths in the wavelength phase difference mapping data and combining the known dispersion characteristics of dry air and water vapor to establish a system of linear equations to solve their respective contributions, the effective separation of the main influencing factors of the atmospheric refractive index is realized, getting rid of the limitation that the contributions of each component are confused in the previous analysis. Deploying multiple sets of transmitting and receiving pairs in the area to form an intersecting optical path network, recording the integral phase difference of each path, and then using iterative calculation to adjust the grid refractive index and applying the total variation minimum constraint after meshing the monitoring area, the rapid and stable reconstruction of the atmospheric refractive index perturbation field is realized, overcoming the problems of low reconstruction quality and blurred edges in traditional tomography under sparse sampling conditions, and obtaining the spatial distribution information of the atmospheric refractive index. Combining a tunable semiconductor laser to select specific absorption spectral lines for high-frequency scanning, and extracting the second harmonic amplitude through digital lock-in amplification to convert the integral path temperature and humidity information, the synchronous measurement of the atmospheric temperature and water vapor concentration is realized, providing a data basis for capturing high-frequency dynamic processes such as atmospheric turbulence. Performing digital filtering processing on the time series of the obtained integral path temperature and humidity data to obtain a pulsation sequence, then calculating its autocorrelation and cross-correlation functions and combining the path length to deduce the turbulence structure parameters, making it possible to quantitatively evaluate the atmospheric optical turbulence intensity and making up for the deficiency that traditional methods are difficult to directly measure turbulence parameters. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] Figure 1 It is a schematic diagram of the steps of the present invention. DETAILED DESCRIPTION OF THE INVENTION

[0015] In order to make the objectives, technical solutions and advantages of the present invention clearer, 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 used to limit the present invention.

[0016] Please refer to Figure 1 , the present invention provides a technical solution, a method for detecting and predicting atmospheric refraction and waveguide environment parameters, including the following steps: Based on the emission of a broadband light source, a beam splitting element is used to distribute the power of the broadband light source beam to form a probe beam and a reference beam. The probe beam is guided through a preset open atmospheric optical path. The preset open atmospheric optical path is a spatial path that has been planned before the start of the experiment or monitoring, connects the broadband light source transmitter and the receiver, has a straight geometric shape, and a length of not less than 1 km. The probe beam propagates in an open and uncontrolled real atmospheric environment. At the same time, the reference beam is guided through a known refractive index stable medium or a vacuum pipeline to obtain the interference signal of the two beams, and the interference signal is processed by Fourier transform to extract the phase difference varying with wavelength, and wavelength-phase difference mapping data is obtained; Based on the wavelength-phase difference mapping data, the phase difference values at different wavelengths are extracted. According to the refractive characteristics differences of dry air and water vapor for light of different wavelengths, a linear equation system is established to solve the contribution amounts of each component. Multiple sets of broadband light source transmitters and receivers are set in a specified area to form a cross-optical path network covering the monitoring area. The integral phase difference of each optical path is recorded, the monitoring area is gridified, the refractive index of each grid is adjusted through iterative calculation, and at the same time, the minimum total variation component constraint is imposed until the reconstruction object edge residual meets the preset threshold, and the threshold is automatically determined by minimizing the reconstruction residual, and an atmospheric refractive index perturbation field is established; Based on the emission of a tunable semiconductor laser, the first absorption line responsive to water vapor concentration is selected, the second absorption line responsive to temperature is selected, the laser is driven to scan a 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, and the path-integrated water vapor concentration and path-integrated temperature are converted according to the calibration data to obtain 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 the slowly varying background trend to obtain the pulsation sequences of temperature and water vapor concentration. The autocorrelation function and cross-correlation function of the pulsation sequences are calculated. According to the path length information, the temperature structure parameter, humidity structure parameter and temperature-humidity covariance structure parameter are deduced, and combined with the spatial refractive index distribution information provided by the atmospheric refractive index perturbation field, the evolution of the atmospheric optical environment parameters is inferred to generate an atmospheric environment parameter prediction set.

[0017] The steps for obtaining the wavelength-phase difference mapping data are as follows: Based on the emission of a broadband light source, the beam splitting element is controlled to adjust the power distribution ratio of the probe beam and the reference beam, the probe beam is calibrated to propagate along the open atmospheric optical path defined by the predetermined coordinate points, and the reference beam is coupled into a vacuum pipeline with controlled internal pressure and temperature. The beam collimation parameters and path geometric parameters are recorded to obtain an optical path configuration parameter set; Based on the optical path configuration parameter set, synchronously trigger the emission of the probe beam and the reference beam. Through the Michelson interferometer configuration, make the two beams generate spatial interference fringes at the beam combination point, capture the change of the interference fringe intensity with time or the optical path difference scanning, and convert the analog voltage signal into a digital sequence through an analog-to-digital converter to obtain the interference signal sequence; Based on the interference signal sequence, perform a Fourier transform on the collected digital sequence to obtain the spectral representation of the signal. Identify the peak positions and phase values corresponding to each wavelength component from the spectrum. By comparing with the calibration data of the reference arm, calculate and extract the change of the phase difference between the probe light and the reference light caused by the atmospheric refractive index perturbation with respect to the wavelength, and obtain the wavelength-phase difference mapping data.

[0018] Specifically, based on the emission of a broadband light source, first, by controlling a beam splitting element such as a tunable neutral density filter or a polarization beam splitter, adjust the power distribution ratio of the probe beam and the reference beam. Initially, it can be set to 50:50, and then fine-tune it according to the signal-to-noise ratio of the interference signal. For example, if the probe beam attenuates greatly in the atmosphere, appropriately increase the initial power ratio of the probe beam. The goal is to make the light intensities of the two beams close at the beam combination point to obtain high-contrast interference fringes. Subsequently, use a quadrant detector or a CCD camera as feedback, and calibrate the probe beam by controlling the precision two-dimensional electric translation stage and the pitch and roll stage installed with the probe light emission collimating lens to ensure that it accurately propagates along the open atmospheric optical path defined by multiple pre-measured ground control points (for example, the points accurately calibrated by GPS or total station), ,…, ). The calibration is completed when the offset of the center of the probe spot at the target point (such as the center of the receiver target at the farthest end) is less than a preset value. This preset value is determined according to the path length and the light source divergence angle. For example, for a 1-kilometer path, the offset is controlled within 1 centimeter. At the same time, efficiently couple the reference beam into a vacuum pipeline with precisely controlled internal pressure and temperature through a fiber optic coupler. The pressure of the vacuum pipeline is maintained at a level below Pascals by the connected vacuum pump and pressure sensor to ensure that its refractive index is close to that of a vacuum (i.e., 1). The temperature is stabilized at, for example, through the heating / cooling jacket around the pipeline and the temperature sensor using a PID (Proportional-Integral-Derivative) controller. During this process, record in detail the collimation parameters of the beam, including the beam divergence angle (for example, the measured divergence angle is 0.5 milliradians), the pointing stability (for example, record the root mean square value of the spot center jitter within 10 minutes, which is required to be less than 5 micro-radians), and the geometric parameters of the path, including the precise three-dimensional coordinates of each predetermined coordinate point and the total length of the optical path (for example, the length measured by a laser rangefinder is 1052.34 meters), etc., to obtain the optical path configuration parameter set.

[0019] Based on the optical path configuration parameters, use a pulse signal generator or a digital delay generator to synchronously trigger the light sources of the probe beam and the reference beam (e.g., simultaneously turn on the shutter of the light source or modulate the signal), 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, through a standard Michelson interferometer configuration, which includes a 50:50 broadband beam splitter, a fixed mirror (for the reference optical arm), a precisely movable mirror (for the probe optical arm, but in this application, the probe optical arm is an open atmospheric path, and the reference optical arm usually has an adjustable optical path difference scanning device built-in), and a beam combining element, the probe beam passing through the atmospheric path and the reference beam passing through the vacuum pipeline 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, pseudo-color interference fringes may be formed. If optical path difference scanning is performed, the intensity change of the central interference fringe with time or optical path difference scanning is captured. The optical path difference scanning is achieved by precisely controlling the position of the reference arm mirror with a piezoelectric ceramic transducer (PZT). The scanning range covers at least the coherence length of several central wavelengths. For example, the scanning range is micrometers, the scanning frequency is 100 Hz, and the generated interference optical signal is received by a high-speed photodetector (e.g., 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 (e.g., 16 bits) ensures sufficient dynamic range and quantization accuracy to obtain the interference signal sequence.

[0020] Based on the interference signal sequence, first apply digital signal processing techniques to the collected digital sequence representing the intensity change of the interference fringes. For example, first perform baseline correction and noise filtering, such as using a high-pass filter to remove the DC component or low-frequency drift, then apply a window function (e.g., Hanning window or Blackman window) to reduce spectral leakage, and then perform a fast Fourier transform (FFT) algorithm on the processed digital sequence to obtain the complex spectral representation of the signal, i.e., the amplitude spectrum and the phase spectrum. From the amplitude spectrum of this spectrum, identify the peaks corresponding to the wavelength components of the light source. The position (frequency) of the peak is related to the wavelength (or wavenumber). Determine the central wavelength corresponding to each peak through the calibrated spectrum of the light source, and extract the phase values at these peak frequencies. Subsequently, by comparing with the pre-acquired calibration data of the reference arm, which is the phase information obtained by performing the same interference measurement and Fourier transform processing when the probe arm is also placed in a vacuum or a known stable medium condition, or by using an optical element with known transfer characteristics to replace the probe arm. , this calibration data reflects the fixed phase delay and dispersion characteristics introduced by the instrument itself and the reference optical path. Then, the change of the phase difference between the probe light and the reference light caused by the atmospheric refractive index perturbation with respect to wavelength is calculated and extracted. The calculation formula is , where is a global phase constant, which can be determined by setting the phase difference at a certain wavelength to zero or by other methods. The finally obtained is the wavelength-phase difference mapping data.

[0021] The steps to obtain the atmospheric refractive index perturbation field are as follows: Based on the wavelength-phase difference mapping data, the phase difference measurement values of multiple target wavelength points are evenly selected therefrom. Using the refractive index dispersion coefficients of dry air and water vapor at each wavelength, an overdetermined linear equation set is constructed, where the unknowns are the dry air density contribution and the water vapor density contribution of the path integral, and a refractive component equation is established; Based on the refractive component equation, pairs of broadband light source emission units and spectral acquisition units are deployed at multiple points around the area to be measured. The connection between the emission and reception units is planned to form an intersecting optical path network. The spectral phase difference of each optical path is measured independently, and the integral phase difference data of all optical paths are summarized to obtain the cross-path integral phase set; Based on the cross-path integral phase set, the monitoring space is discretized into a three-dimensional voxel grid. An initial refractive index estimate value is assigned to each voxel. The voxel refractive index is adjusted according to the difference between the measured value 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 an atmospheric refractive index perturbation field is established.

[0022] Specifically, based on the wavelength-phase difference mapping data , multiple target wavelength points are evenly selected therefrom at equal wavelength intervals or equal wavenumber intervals. For example, if the spectral range of the broadband light source is from 600 nm to 1000 nm, a point can be selected every 20 nm, and a total of 21 wavelength points' phase difference measurement values are selected (where , ), Next, using the refractive index dispersion empirical formulas (such as the Ciddor formula or the Owens formula) of known dry air and water vapor at each selected wavelength to calculate the refractive index dispersion coefficients, denoted as and , these coefficients describe the refractive index contributions of unit density dry air and water vapor at different wavelengths. Then, an overdetermined linear equation set is constructed. Its 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 , where is the value obtained by subtracting 1 from the atmospheric refractive index at point s on the path and at wavelength , and can be expressed as , where and are the densities of dry air and water vapor respectively. Therefore, for the j - th wavelength, there is an equation: , where the unknowns are the path - integral dry - air density contribution and the path - integral water - vapor density contribution along the entire optical path. Since there are measurement data at M wavelength points (M>2, that is, the number of equations is greater than the number of unknowns), an over - determined linear equation system is formed. The least - squares method is used to solve this equation system to obtain and the optimal estimated values, and this set of equations is the established refraction - component equation.

[0023] Based on the ability to solve for the single - path integral dry - air and water - vapor contributions obtained from the refraction - component equation, a total of 8 stations are deployed around the area to be measured, such as at the four corner points and the mid - points of the four sides of a square area with a side length of 1 km. Each station is equipped with a broadband light - source emission unit and a spectral acquisition unit, or configured as a single - emission or single - reception unit only. By adjusting the orientation of each unit, multiple optical - path connections between the emission unit and the reception unit are planned and established to form a cross - optical - path network covering the monitoring area. For example, if 4 emission units and 4 reception units are deployed, up to 16 independent or partially overlapping optical paths can be formed to ensure that the optical paths form a dense cross - coverage within the monitoring area to improve the spatial resolution. For each independent optical path in this network (for example, the path from the transmitter to the receiver ), the above - mentioned spectral phase - difference measurement process is independently and repeatedly executed, that is, the wavelength - phase - difference mapping data of this optical path is obtained, and the path - integral dry - air density contribution and path - integral water - vapor density contribution of this path are calculated using the refraction - component equation, or directly using the integral phase - difference values of each wavelength. Then, the integral phase - difference data (or the integral refractive - index contribution data calculated therefrom) measured for all optical paths are aggregated to form a data set containing each optical path and its corresponding measured values, and the cross - path integral phase set is obtained.

[0024] Based on the cross - path integral phase set, first, the three - dimensional monitoring space (for example, a space of 1 km * 1 km * 0.5 km) is discretized into a regular three - dimensional voxel grid. The size of the voxel is determined according to the desired resolution and computing resources. For example, the size of each voxel is 20 m * 20 m * 10 m. For each voxel in the grid Assign an initial refractive index estimate , which can be set to the refractive index calculated based on the standard atmospheric model or the average refractive index obtained from historical data of the same period. Then, enter the iterative calculation process. In the i-th iteration, for each optical path p, according to the current refractive index distribution of each volume element , calculate the theoretical integral phase difference (or integral refractive index) of this optical path , where is the length of the optical path p within the volume element . Compare this calculated value with the actual measured value of this optical path to obtain the residual . Based on these residuals, use the algebraic reconstruction technique (ART) or the simultaneous iterative reconstruction technique (SIRT) algorithm to adjust the refractive index values of each volume element. For example, the update rule of SIRT is , where is the total length of the optical path p, is the relaxation factor, usually taking a value between 0.1 and 1.0, for example, set to 0.5. At the same time, in order to ensure the stability and physical rationality of the solution, introduce the total variation regularization term as a constraint, which penalizes the norm of the refractive index gradient in the solution, tending to produce smooth regions with clear boundaries. Its objective function is in the form of , where is the regularization parameter, and its value is determined by cross-validation or the L-curve method. For example, it can be initially set to 0.01. The iterative process continues until the root mean square value of the residuals of all optical 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 of the refractive index unit (corresponding to 0.1 of the N value), or the change amount of the refractive index field between consecutive iterations is less than a certain minimum value (for example, the maximum absolute value of the change amount of the refractive index of all volume elements is less than ), the iteration stops. At this time, the refractive index distribution of each volume element obtained is the established atmospheric refractive index perturbation field

[0025] The steps for obtaining path integral temperature and humidity data are as follows: Control the operating temperature and injection current of the laser, select and stabilize the output of the first near-infrared absorption spectral line sensitive to water vapor concentration changes and the second absorption spectral line sensitive to atmospheric temperature changes, set the parameters for the laser wavelength to perform periodic scanning at the spectral line center, and obtain the laser scanning parameter set; Based on the laser scanning parameter set, drive the modulated laser beam output by the laser to pass through the target atmospheric path, filter out the background light and then receive it by the photodetector, amplify the absorption signal output by the detector, demodulate and extract the amplitude data points of the second harmonic signal to obtain the harmonic amplitude of the absorption signal The steps for obtaining path-integrated temperature and humidity data further include: based on the harmonic amplitudes of the absorption signals, using the quantitative relationship model between the second harmonic amplitudes and gas concentration and temperature obtained by pre-calibration with standard gases in advance, 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 obtaining path-integrated temperature and humidity data.

[0026] Specifically, control the operating temperature and injection current of the laser. Select a first absorption spectral line that is sensitive to changes in water vapor concentration and has an appropriate absorption intensity in the near-infrared band. For example, select the absorption line near 1392.53 nm of water vapor. At the same time, select a second absorption spectral line that is sensitive to changes in atmospheric temperature. For example, use a certain absorption line near 760 nm in the oxygen A band that has an obvious response to temperature, or select another water vapor absorption line with different low-energy level transition energies. Stabilize the temperature of the laser chip at a preset value through the temperature control unit. For example, for a distributed feedback (DFB) laser, set the operating temperature to , and this temperature stability target is the upper limit of the allowable temperature drift calculated based on the laser wavelength tuning coefficient (such as 0.08 nm / °C) and the required wavelength stability (such as less than 1 / 100 of the absorption line width. If the line width is 0.01 nm, the wavelength stability is better than 0.0001 nm), and the injection current is controlled by the laser drive power supply. For example, set it to mA, and its stability target mA is determined according to the current tuning coefficient and the same wavelength stability requirement. Then set the parameters for the laser output wavelength to perform periodic scanning around the center of the selected absorption spectral line, including the scanning center wavelength (i.e., the spectral line center wavelength ), the scanning amplitude. For example, set it to 3 to 5 times the spectral line half-width. If the spectral line half-width is 0.02 nm, the scanning amplitude can be set to nm, and the scanning frequency. For example, use a triangular wave or sawtooth wave scanning at 1 kHz. This frequency selection needs to be much higher than the atmospheric turbulence change frequency but lower than the higher frequency sine wave used for wavelength modulation. These set values of the selected spectral line wavelengths, operating temperature and current, and scanning parameters (center, amplitude, frequency, waveform) together constitute the laser scanning parameter set.

[0027] Based on the laser scanning parameter set, specifically using the set scanning center wavelength, scanning amplitude, and scanning frequency therein, drive a tunable semiconductor laser (such as a DFB laser) to output laser. At the same time, superimpose a high-frequency sine modulation current (such as a frequency kHz, and the modulation depth corresponds to a wavelength modulation amplitude of about 2.2 times the spectral line width) on top of a slow scanning current (such as a 1 kHz triangular wave), so that the output wavelength of the laser , the modulated laser beam passes through a collimation system and then through a predetermined target atmospheric path. At the receiving end, first, a narrowband interference filter with a central wavelength matching the operating wavelength of the laser 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 is received by a photodetector (such as an indium gallium arsenide PIN photodiode for the near-infrared band) and converted into a photocurrent signal. This photocurrent signal is first converted into a voltage signal by a transimpedance amplifier (TIA) and preliminarily amplified. The gain of the amplifier is dynamically adjusted according to the signal intensity and the input range of the subsequent analog-to-digital converter. For example, it is adjusted so that the absorption signal peak occupies 50% to 80% of the ADC dynamic range. Subsequently, the voltage signal containing absorption information is input to a digital lock-in amplifier. The reference signal frequency of the lock-in amplifier is set to twice the frequency of the high-frequency sine 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 the maximum (or the quadrature component reaches the minimum), a sequence of data points of the amplitude of the second harmonic signal (2f signal) changing with time (i.e., with the scanned wavelength) during the slow wavelength scanning process is extracted and recorded to obtain the harmonic amplitude of the absorption signal.

[0028] The steps for obtaining the path-integrated temperature and humidity data further include: Based on the harmonic amplitude of the absorption signal, that is, the curves of the amplitude of the second harmonic signal changing with the scanned wavelength obtained for the water vapor absorption line and the temperature-sensitive absorption line respectively, first extract the peak value from each curve , and then use the quantitative relationship model established through a standard gas calibration experiment in advance. This model is established by connecting the laser system under test to a gas chamber filled with a standard gas with known concentration, temperature, and pressure, changing the gas concentration in the gas chamber (for example, for water vapor, by controlling water sources with different saturated vapor pressures to generate gases with 0% to 90% relative humidity, corresponding to a water vapor concentration range of, for example, from 0 to ppmv) and temperature (for example, by controlling the temperature of the gas chamber within the range of 5°C to 45°C with a step of 5°C using a temperature control jacket), and recording the second harmonic peak values under different conditions . For the water vapor concentration, establish a polynomial fitting relationship, such as , where the coefficient is obtained by least squares fitting of the calibration data points, such as (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-integrated temperature, if a single temperature-sensitive spectral line is used, establish a relationship, and obtain the temperature T through look-up table or inverse function method. Or, if two spectral lines with different low-level energies are used (such as the spectral line pair of water vapor ), then the second harmonic peak ratio is strongly related to temperature. Establish the relationship, for example , and the coefficient is also obtained through calibration. For example , substitute the second harmonic peak of the water vapor spectrum measured in real time on site and the second harmonic peak (or ratio) of the temperature-sensitive spectrum (or spectrum pair) into these calibration models, calculate the path-integrated water vapor concentration value and the 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, and obtain the path-integrated temperature and humidity data.

[0029] The steps to obtain the atmospheric environment parameter prediction set are as follows: Based on the path-integrated temperature and path-integrated water vapor concentration multi-point time sampling data in the path-integrated temperature and humidity data, perform Butterworth high-pass filtering on each time series separately to separate the fluctuation components caused by atmospheric turbulence and obtain the temperature and humidity pulsation value sequence; Based on the temperature and humidity pulsation value sequence, calculate 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, and deduce the temperature structure parameter, humidity structure parameter, and temperature and humidity covariance structure parameter from the zero-delay value of the covariance function to establish the atmospheric turbulence characteristic parameters; Based on the atmospheric turbulence characteristic parameters and combined with the three-dimensional refractive index mean distribution provided by the atmospheric refractive index perturbation field, simulate and calculate the beam path bending, intensity fluctuation, and arrival angle fluctuation to generate the atmospheric environment parameter prediction set.

[0030] Specifically, based on the path-integrated temperature and path-integrated water vapor concentration in the path-integrated temperature and humidity data, where represents discrete sampling moments, for example, sampling once per second. For each complete time series (for example, one-hour continuous temperature data and water vapor concentration data), independently apply a digital Butterworth high-pass filter for processing. This filter is designed as a fourth-order Butterworth filter. The Butterworth filter is selected because it has the maximum flat amplitude-frequency response in the passband, and its cut-off frequency is set based on distinguishing the rapid fluctuations caused by atmospheric turbulence from the slow background trends caused by weather system evolution or diurnal variations. For example, if the time scale of interest is from a few seconds to more than ten minutes of turbulence, the cut-off frequency can be set to 0.001 Hz, corresponding to a period of about 16.7 minutes. This means that the slow changes with a period longer than 16.7 minutes will be filtered out, while the fluctuations with a period shorter than this will be retained. This cut-off frequency The 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., the trend of atmospheric structure changes greater than 5 km needs to be filtered out), and its calculation method is , where U is the average wind speed, is the maximum scale to be filtered out, for example , the filtering operation converts the original time series into a temperature fluctuation series , and similarly converts the original water vapor concentration time series into a water vapor concentration fluctuation series , where and are the low-frequency components removed by high-pass filtering, so as to separate the fast fluctuation components dominated by atmospheric turbulence and obtain a series of temperature and humidity fluctuation values.

[0031] Based on the series of temperature and humidity fluctuation values, that is, the temperature fluctuation time series and the water vapor concentration fluctuation time series , first calculate the statistical characteristics of these fluctuation series, specifically including calculating the autocovariance function of the temperature fluctuation time series , the autocovariance function of the water vapor concentration fluctuation time series , and the cross-covariance function between the temperature fluctuation and the water vapor concentration fluctuation , where is the time delay, and the angle brackets represent time averaging. Then, from the zero-time-delay values of these covariance functions, that is, (temperature fluctuation variance), (water vapor concentration fluctuation variance), and (temperature and humidity fluctuation covariance), estimate the structure parameters of atmospheric turbulence. Specifically, the temperature structure parameter , the humidity structure parameter , and the temperature and humidity covariance structure parameter (structure parameter, not a function) are estimated through the following relationships: , and , where A is a constant related to the turbulence spectrum type, and its value ranges from 0.1 to 1.0. Here, based on the von Kármán spectrum, for example, A can be taken as 0.5, is the outer scale of turbulence of the corresponding physical quantity, and its value is set according to experience or obtained from the product of the integral time scale of the covariance function and the average wind speed. For example, if the average wind speed is 5 m / s and the integral time scale is 20 s, then the outer scale is estimated to be 100 m. If is measured, then , and establish the characteristic parameters of atmospheric turbulence.

[0032] Based on the atmospheric turbulence characteristic parameters established in the previous steps, namely the temperature structure parameter , the humidity structure parameter , and the temperature-humidity covariance structure parameter , and combined with the three-dimensional refractive index mean distribution in the atmospheric refractive index perturbation field provided by broadband light source interferometric measurement 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 optical wavelength. For example, for the visible light band, . Then, adopt the numerical simulation method of beam propagation, such as the paraxial approximation (PWE) based on the Helmholtz equation combined with the split-step Fourier transform, to simulate the process of the beam propagating in the atmosphere containing the above three-dimensional refractive index mean distribution and the three-dimensional refractive index structure parameter field . For the beam path bending, it is calculated by solving the eikonal equation or considering the refractive index gradient in ray tracing. For the intensity fluctuation (scintillation index ), it is obtained by calculating the normalized intensity variance in the PWE simulation, or using the integral formula based on the Rytov approximation (for spherical waves under weak fluctuation conditions), where is the wave number, L is the path length. For the arrival angle fluctuation , it is 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 a preset number of 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. for each path is generated to form an atmospheric environment parameter prediction set.

[0033] The above is only a preferred embodiment of the present invention, and it does not limit the present invention in other forms. Any person skilled in the art may use the disclosed technical content to make changes or modifications into equivalent embodiments with equivalent changes and apply them to other fields. However, as long as it does not depart from the technical solution content of the present invention, any simple modification, equivalent change, and modification made to the above embodiments based on the technical essence of the present invention still fall within the protection scope of the technical solution of the present invention.

Claims

1. A method for detecting and predicting atmospheric refraction and waveguide environment parameters, characterized in that Including the following steps: Based on the emission of a broadband light source, a beam splitting element is used to distribute the power of the broadband light source beam, forming 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. An interference signal of the two beams is obtained, and the interference signal is subjected to Fourier transform processing to extract the phase difference varying with wavelength, obtaining wavelength-phase difference mapping data; Based on the wavelength-phase difference mapping data, the phase difference values at different wavelengths are extracted. According to the refractive characteristics differences of dry air and water vapor for light of different wavelengths, a linear equation system is established to solve the contribution amounts of each component. Multiple broadband light source transmitters and receivers are set in a specified area to form a cross optical path network covering the monitoring area. The integral phase difference of each optical path is recorded, the monitoring area is gridified, and the refractive index of each grid is adjusted through iterative calculation while applying the minimum constraint of the total variation component until the residual of the reconstructed object edge meets the preset threshold, establishing an atmospheric refractive index perturbation field.

2. The method for detecting and predicting atmospheric refraction and waveguide environment parameters according to claim 1, characterized in that, The method further includes: Based on the emission of a tunable semiconductor laser, a first absorption line responsive to water vapor concentration is selected, and a second absorption line responsive to temperature is selected. The laser is driven to scan a preselected laser wavelength range, and the laser absorption signal passing through the atmosphere is captured by a photodetector. The signal is subjected to digital lock-in amplification to extract the second harmonic amplitude, and the path integral water vapor concentration and path integral temperature are converted according to the calibration data, obtaining path integral temperature and humidity data; Based on the path integral temperature and path integral water vapor concentration in the form of time series in the path integral temperature and humidity data, a digital filter is applied to filter out the slowly changing background trend, obtaining the pulsation sequences of temperature and water vapor concentration. The autocorrelation function and cross-correlation function of the pulsation sequences are calculated. According to the path length information, the temperature structure parameter, humidity structure parameter, and temperature-humidity covariance structure parameter are deduced, and combined with the spatial refractive index distribution information provided by the atmospheric refractive index perturbation field, the evolution of 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 environment parameters according to claim 1, wherein The obtaining steps of the wavelength-phase difference mapping data are: Based on the emission of a broadband light source, the beam splitting element is controlled to adjust the power distribution ratio of the detection beam and the reference beam, calibrate the detection beam to propagate along the open atmospheric optical path defined by the predetermined coordinate points, and couple the reference beam into a vacuum pipeline with controlled internal pressure and temperature. The beam collimation parameters and path geometric parameters are recorded, obtaining an optical path configuration parameter set; Based on the optical path configuration parameter set, the emission of the detection beam and the reference beam is synchronously triggered. Through the configuration of a Michelson interferometer, the two beams generate spatial interference fringes at the beam combination point, capture the change of the interference fringe intensity with time or optical path difference scanning, and convert the analog voltage signal into a digital sequence through an analog-to-digital converter, obtaining an interference signal sequence; Based on the interference signal sequence, perform Fourier transform on the acquired digital sequence to obtain the spectral representation of the signal. Identify the peak positions and phase values corresponding to each wavelength component from the spectrum. By comparing with the calibration data of the reference arm, calculate and extract the change of the phase difference between the probe light and the reference light caused by the atmospheric refractive index perturbation with respect to wavelength, and obtain the wavelength-phase difference mapping data.

4. The method for detecting and predicting atmospheric refraction and waveguide environment parameters according to claim 1, wherein The steps for obtaining the atmospheric refractive index perturbation field are as follows: Based on the wavelength-phase difference mapping data, uniformly select the phase difference measurement values at multiple target wavelength points therefrom. Utilize the refractive index dispersion coefficients of dry air and water vapor at each wavelength to construct an overdetermined linear equation system, where the unknowns are the dry air density contribution and the water vapor density contribution of the path integral, and establish a refractive component equation. Based on the refractive component equation, deploy paired broadband light source emission units and spectral acquisition units at multiple points around the area to be measured. Plan the connections between the emission and reception units to form a crossed optical path network. Independently measure the spectral phase difference for each optical path, and summarize the integral phase difference data of all optical paths to obtain the crossed path integral phase set. Based on the crossed path integral phase set, discretize the monitoring space into a three-dimensional voxel grid. Assign an initial refractive index estimate to each voxel. Adjust the voxel refractive index according to the difference between the measured values of each optical path and the calculated values of the current model. At the same time, introduce a total variation regularization term to constrain the smoothness of the iterative solution until the residual reaches the preset accuracy, and establish the atmospheric refractive index perturbation field.

5. The method for detecting and predicting atmospheric refraction and waveguide environment parameters according to claim 2, characterized in that, The steps for obtaining the path integral temperature and humidity data are as follows: Control the operating temperature and injection current of the laser. Select and stably output the first near-infrared absorption line sensitive to the change in water vapor concentration and the second absorption line sensitive to the change in atmospheric temperature. Set the parameters for the laser wavelength to perform periodic scanning at the center of the spectral line to obtain the laser scanning parameter set. Based on the laser scanning parameter set, drive the modulated laser beam output by the laser to pass through the target atmospheric path. After filtering out the background light, it is received by a photodetector. Amplify the absorption signal output by the detector, demodulate and extract the amplitude data points of the second harmonic signal to obtain the harmonic amplitude of the absorption signal.

6. The method for detecting and predicting atmospheric refraction and waveguide environment parameters according to claim 5, characterized in that, The steps for obtaining the path integral temperature and humidity data further include: Based on the harmonic amplitude of the absorption signal, utilize the quantitative relationship model between the second harmonic amplitude and the gas concentration and temperature obtained by pre-calibration with standard gases. Convert the measured second harmonic amplitudes of the two spectral lines into the path integral water vapor concentration value and the path integral temperature value respectively to form a time-synchronized measurement data sequence, and obtain the path integral temperature and humidity data.

7. The method for detecting and predicting atmospheric refraction and waveguide environment parameters according to claim 2, characterized in that, The steps for obtaining the set of predicted atmospheric environment parameters are as follows: Based on the path integral temperature and the path integral water vapor concentration multi-point time sampling data in the path integral temperature and humidity data, perform Butterworth high-pass filtering on each time series respectively to separate the fluctuation components caused by atmospheric turbulence and obtain the temperature and humidity pulsation value sequence. Based on the above temperature and humidity pulsation value sequence, calculate 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. Deduce the temperature structure parameter, humidity structure parameter, and temperature-humidity covariance structure parameter from the zero-delay value of the covariance function, and establish the atmospheric turbulence characteristic parameters.

8. The method for detecting and predicting atmospheric refraction and waveguide environment parameters according to claim 7, characterized in that, The step of obtaining the atmospheric environment parameter prediction set further includes: based on the atmospheric turbulence characteristic parameters and combined with the three-dimensional refractive index mean distribution provided by the atmospheric refractive index perturbation field, simulate and calculate the beam path bending, intensity fluctuation, and arrival angle fluctuation, and generate the atmospheric environment parameter prediction set.

9. An atmospheric refraction and duct environment parameter detection and prediction system for the method of detecting and predicting atmospheric refraction and duct environment parameters according to any one of claims 1-8, characterized in that, Including: A spectral interference measurement module, which is based on the emission of a broadband light source. A beam splitting element 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, and at the same time, the reference beam is guided through a stable medium with a known refractive index or a vacuum pipeline. The interference signal of the two beams is obtained, and the interference signal is subjected to Fourier transform processing to extract the phase difference varying with the wavelength, and the wavelength phase difference mapping data is obtained. A refractive index perturbation field reconstruction module, which is based on the wavelength phase difference mapping data, extracts the phase difference values at different wavelengths, and establishes a linear equation set to solve the contribution amounts of each component according to the refractive characteristics differences of dry air and water vapor to light rays of different wavelengths. Multiple groups of broadband light source transmitters and receivers are set in a specified area to form a cross-optical path network covering the monitoring area. The integral phase difference of each optical path is recorded, the monitoring area is gridded, and the refractive index of each grid is adjusted through iterative calculation while applying the minimum total variation component constraint until the reconstruction object edge residual meets the preset threshold, and the atmospheric refractive index perturbation field is established. An absorption spectrum measurement module, which is based on the emission of a tunable semiconductor laser. The first absorption line responsive to the water vapor concentration and the second absorption line responsive to the 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, and the digital lock-in amplifier is used to extract the second harmonic amplitude of the signal, and 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. An atmospheric environment prediction module, which is based on the path-integrated temperature and path-integrated water vapor concentration in the form of a time series in the path-integrated temperature and humidity data. The digital filter is used to filter out the slowly changing background trend to obtain the temperature and water vapor concentration pulsation sequences. The autocorrelation function and cross-correlation function of the pulsation sequences are calculated. According to the path length information, the temperature structure parameter, humidity structure parameter, and temperature-humidity covariance structure parameter are deduced, and combined with the spatial refractive index distribution information provided by the atmospheric refractive index perturbation field, the evolution of the atmospheric optical environment parameters is inferred, and the atmospheric environment parameter prediction set is generated.

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