Spaceborne hyperspectral detection lidar atmospheric particle retrieval method

Abstract

The application discloses a kind of spaceborne hyperspectral detection lidar atmospheric particle retrieval method, include following part: solving the laser ranging value and altitude corresponding to the sampling point of spaceborne hyperspectral resolution lidar (HSRL) echo signal;Using the method of removing noise reduces the noise of echo signal;Distance and system constant correction is carried out to the denoising signal;Using forecast model reanalysis data set, S6 atmosphere model and iodine molecule hyperspectral filter absorption spectrum establishes molecular scattering signal transmittance lookup table;Cloud and aerosol backscattering coefficient and scattering ratio are calculated;Utilize scattering ratio and voltage signal-to-noise ratio threshold method to carry out hierarchical identification;Effective retrieval area is determined by hierarchical area processing;Calculate initial extinction coefficient and radar ratio;Radar ratio is carried out Gaussian smoothing filtering, and final radar ratio is obtained, and final extinction coefficient profile is calculated.The characteristics of the application are that cloud and aerosol hierarchical identification is carried out to spaceborne HSRL echo signal, molecular transmittance lookup table of hyperspectral channel is established, and accurate and efficient solution is carried out to cloud and aerosol optical parameter.

Description

TECHNICAL FIELD

[0001] The present application belongs to the field of satellite optical remote sensing of atmospheric environment, and particularly relates to a method for retrieving atmospheric particles (clouds and aerosols) by a satellite-borne HSRL (High-Spectral-Resolution Lidar). BACKGROUND

[0002] Aerosol refers to a multiphase system composed of the atmosphere and solid and liquid particles suspended therein, with a particle diameter of 0.001-100 microns; cloud refers to a visible aggregate floating in the air composed of small water droplets or small ice crystals formed by the condensation of water vapor in the atmosphere. Clouds and aerosols play an important role in the earth's atmospheric environment and the regulation of the earth's climate, and therefore, obtaining high temporal and spatial resolution vertical profiles and optical properties of global atmospheric clouds and aerosols is of great significance for weather forecasting, global radiation balance and air quality monitoring.

[0003] As an active remote sensing tool, lidar is widely used in cloud and aerosol profile detection due to its high temporal and spatial resolution and continuous detection at any time. In atmospheric lidar, high spectral resolution lidar can directly retrieve cloud and aerosol optical parameters without assuming lidar ratio, significantly improve the retrieval accuracy, and become one of the important technologies in the field of atmospheric detection. However, neither ground-based high spectral resolution lidar nor airborne high spectral resolution lidar can achieve real-time global measurement of clouds and aerosols at any time.

[0004] Satellite-borne HSRL separates the Mie scattering of aerosols and the Rayleigh scattering of molecules in the echo signal based on the high spectral channel of the iodine molecule filter, thereby directly retrieving the optical parameters of clouds and aerosols without assuming the lidar ratio. The satellite-borne HSRL has the following advantages:

[0005] (1) It can achieve global measurement of clouds and aerosols at any time.

[0006] (2) It can directly retrieve the optical parameter profiles of clouds and aerosols through lidar detection signals, greatly improving the retrieval accuracy.

[0007] Patent document CN114296103A discloses a method for retrieving extinction coefficient of airborne high spectral resolution lidar, but the patent technology solves the data processing and retrieval of airborne high spectral resolution lidar, and the retrieval height range is much lower than that of satellite platform, which is not suitable for retrieval of satellite platform data. SUMMARY

[0008] The purpose of this invention is to overcome the shortcomings of the prior art and provide a method for atmospheric particle inversion using a spaceborne hyperspectral lidar (HSRL) to obtain high-precision global cloud and aerosol optical parameters. The method involves solving for the laser ranging values ​​and altitude corresponding to the sampling points of the spaceborne HSRL echo signal; using various denoising methods to reduce noise in the HSRL echo signal; correcting the HSRL detection signal for distance and system constants; establishing a molecular transmittance lookup table for the hyperspectral detection channel using temperature and pressure profiles from a numerical weather prediction model reanalysis dataset, the S6 atmospheric model, and the absorption spectrum of an iodine molecule filter, and calculating the aerosol transmittance and atmospheric molecular parameters of the hyperspectral detection channel; calculating the cloud and aerosol backscattering coefficients and scattering ratios based on the attenuated backscattering coefficient; calculating the echo voltage-to-noise ratio; performing hierarchical identification using the scattering ratio and voltage-to-noise ratio threshold method; determining the effective data inversion area through hierarchical region processing; initially inverting the cloud and aerosol optical thickness, extinction coefficient, and radar ratio; and obtaining the final radar ratio by applying Gaussian smoothing filtering to the initially inverted radar ratio, from which the final extinction coefficient is calculated.

[0009] The technical solution of the present invention is as follows:

[0010] A method for atmospheric particle inversion using a spaceborne hyperspectral lidar, characterized by comprising the following steps:

[0011] (1) The spaceborne lidar system mainly consists of two parts: a transmitter and a receiver. The transmitter emits a pulsed laser beam with a wavelength of 532 nm, which acts on atmospheric molecules, clouds, and aerosols, resulting in transmission, absorption, and scattering. At the receiver, the lidar telescope receives the backscattered signals from atmospheric molecules, clouds, and aerosols, and obtains polarization signals, parallel channel signals, and pure molecular scattering signals through hyperspectral detection.

[0012] (2) Solve for the laser ranging value and altitude corresponding to each sampling point in the echo signal.

[0013] (3) The echo voltage signal is denoised and smoothed by using the methods of profile superposition, moving average and wavelet denoising.

[0014] (4) Based on step (3), the atmospheric echo signal detected by the spaceborne lidar is corrected for distance and system constant to obtain the corrected attenuated backscatter signal.

[0015] (5) Based on the temperature and pressure profiles, the absorption spectra of the S6 atmospheric model and the iodine molecular filter given by the reanalysis meteorological dataset of the numerical weather prediction model, establish a lookup table of molecular transmittance of the hyperspectral channel, and solve for the aerosol transmittance and atmospheric molecular parameters of the hyperspectral channel.

[0016] (6) The aerosol backscattering coefficient is initially inverted using the attenuated backscattering signal, molecular transmittance lookup table, aerosol transmittance and atmospheric molecular parameters, and the atmospheric scattering ratio is calculated.

[0017] (7) The voltage signal noise ratio is calculated using the echo voltage signal and the background noise of the upper atmospheric region.

[0018] (8) Using atmospheric scattering ratio and voltage signal noise ratio, set the threshold for cloud and aerosol layer identification, perform cloud and aerosol layer identification, and filter out the surface from the existing layers based on the elevation of the radar pointing point.

[0019] (9) The cloud and aerosol layers are merged into a layered region, and the surface and clean atmosphere are merged into a non-layered region. Only the data of the layered region is retained as valid data to participate in the subsequent inversion of cloud and aerosol optical parameters.

[0020] (10) Using attenuated backscattered signals, molecular transmittance lookup tables, aerosol transmittance, atmospheric molecular parameters and layer identification results, preliminary inversion of cloud and aerosol optical thickness (atmospheric optical thickness), extinction coefficient and radar ratio optical parameters is performed.

[0021] (11) Taking advantage of the small dynamic range of lidar, Gaussian smoothing filtering is applied to the lidar ratio to obtain the final lidar ratio inversion result. The optimized inversion results of cloud and aerosol extinction coefficients are obtained by combining the relationship between extinction coefficient and lidar ratio.

[0022] Compared with the prior art, the beneficial effects of the present invention are:

[0023] (1) This invention utilizes reanalysis datasets from numerical weather prediction models and absorption spectra from iodine molecular filters to establish molecular transmittance lookup tables for hyperspectral channels at different temperatures and pressures, improving the efficiency of processing satellite remote sensing data. Based on hyperspectral detection data from spaceborne lidar, this invention proposes a novel method for hierarchical identification, achieving effective identification of cloud and aerosol hierarchies in the atmosphere and improving the inversion accuracy of hyperspectral detection data. Using acquired lidar data and processing methods based on spaceborne lidar hyperspectral detection data, data processing and optical parameter inversion for a spaceborne platform's hyperspectral resolution lidar are realized.

[0024] (2) By combining lidar technology with a satellite platform, long-range, high-precision detection of atmospheric molecules, clouds, and aerosols is achieved. Hyperspectral detection technology is used to acquire polarization signals, parallel channel signals, and pure molecular scattering signals from the echo signals, improving the ability to detect atmospheric components. Using the laser ranging formula, satellite position coordinates, the latitude, longitude, and elevation of the lidar pointing point, and the delay time of the echo acquisition segment, the laser ranging value and altitude corresponding to the echo signal sampling point are accurately calculated, improving the accuracy of ranging and altitude calculations.

[0025] (3) By setting scattering ratio thresholds and voltage signal-to-noise ratio thresholds, accurate identification of cloud and aerosol layers was achieved, and the layered regions were used as effective data for subsequent aerosol optical parameter inversion. This innovative layer identification and processing method improved the accuracy and reliability of the inversion results. Using the echo voltage signal received by the satellite for quality control and layer identification, it is possible to invert not only the optical parameters of clouds and aerosols within the airborne detection range but also optical parameters over a higher range. Furthermore, due to the satellite's real-time global monitoring, the number of received signals is extremely large. This invention, starting from data inversion efficiency, proposes a method for establishing a hyperspectral channel molecular transmittance lookup table, which greatly improves the efficiency of batch processing of satellite remote sensing data.

[0026] (4) Compared to CN114296103A, this invention utilizes the echo voltage signal received by the satellite for quality control and hierarchical identification, enabling the inversion of optical parameters of clouds and aerosols within the airborne detection range, as well as optical parameters at a higher range. Furthermore, due to the satellite's real-time global monitoring around the clock, the number of received signals is extremely large. Based on data inversion efficiency, this invention proposes a method for establishing a lookup table of molecular transmittance for hyperspectral channels, greatly improving the efficiency of batch processing of satellite remote sensing data. Attached Figure Description

[0027] Figure 1 This is a schematic diagram illustrating the specific process of the present invention.

[0028] Figure 2 This is a schematic diagram for calculating the pointing point of a lidar. Detailed Implementation

[0029] To more clearly illustrate the processing method based on hyperspectral detection data from spaceborne lidar, the present invention will be further described below with reference to examples and accompanying drawings. Figure 1 A schematic diagram illustrating the specific process of the algorithm of this invention is provided.

[0030] The specific implementation scheme of the present invention is as follows:

[0031] (1) The spaceborne lidar system mainly consists of two parts: a transmitter and a receiver. The transmitter emits a pulsed laser beam with a wavelength of 532 nm, which acts on atmospheric molecules, clouds, and aerosols, resulting in transmission, absorption, and scattering. At the receiver, the lidar telescope receives the backscattered signals from atmospheric molecules, clouds, and aerosols, and obtains the echo signals (including polarization signals, parallel channel signals, and pure molecular scattering signals) through hyperspectral detection.

[0032] (2) Solving for the laser ranging value and altitude corresponding to the echo signal sampling point

[0033] To obtain the laser ranging value and altitude corresponding to the sampling point of the echo signal (the total signal received from the three channels), the satellite position coordinates, the latitude and longitude of the lidar pointing point, the elevation of the pointing point, and the delay time of the echo acquisition segment are required. The laser ranging formula is as follows:

[0034]

[0035] Where T d T is the delay time of the echo acquisition segment. a N is a fixed time difference between the trigger pulse and the laser pulse emission, where N is the number of position points in the echo signal acquisition segment, DA is the echo signal sampling frequency, and C is the speed of light in vacuum.

[0036] After obtaining the ranging value, it is necessary to use the ranging information to further solve the altitude of each sampling point of the echo signal, as shown in Figure (2). r is the distance from the satellite platform to the sampling point, h is the altitude corresponding to each sampling point, l is the distance from the satellite platform to the ground pointing point, and d is the elevation of the pointing point. The calculation formula is as follows:

[0037] Calculate the Earth's radius R based on latitude and longitude, and then calculate the X, Y, and Z coordinates of the laser pointing point based on the Earth's radius, latitude and longitude, and elevation.

[0038]

[0039] X=(r+d)·cosφ·cosλ (9)

[0040] Y=(r+d)·cosφ·sinλ (10)

[0041] Z=(r(1-f) 2 +d)·sinφ (11)

[0042] Where φ is latitude, λ is longitude, A is the Earth's semi-major axis (6378137m), f is the polar flattening (1 / 298.257223565), and d is the elevation of WGS-84 at that latitude and longitude.

[0043] Based on the X, Y, Z coordinates of the laser pointing point and the X coordinate of the satellite platform 星 Y 星 Z 星 Coordinates, calculating the distance l between the satellite platform and the ground pointing point.

[0044]

[0045] Where X 星 Y 星 Z 星 These are the X, Y, and Z coordinates of the satellite in the WGS-84 coordinate system.

[0046] Then, the altitude h of each sampling point is further calculated.

[0047] h = l + dr (13)

[0048] Where r is the distance from the satellite to the sampling point, i.e., the laser ranging value.

[0049] Using the calculated altitude of the acquisition points, the echo data acquisition points were matched to a height grid ranging from 42km to -0.96km, with a vertical resolution of 24m.

[0050] (3) Noise reduction of echo voltage signal

[0051] In this embodiment, the horizontal resolution of the signal is 337.5 m, and the vertical resolution is 24 m. To reduce signal noise while ensuring high resolution of the inversion results, 59 superimposed averages of the echo voltage signals are performed horizontally, and 2 superimposed averages are performed vertically. First, the signal (the superimposed averaged echo voltage signal) is filtered using a moving average method, with sliding window lengths of 10, 10, and 15 for the parallel, polarization, and hyperspectral channels, respectively. Then, wavelet denoising algorithm with appropriate denoising orders is used to denoise the signal; the denoising orders for the parallel, polarization, and hyperspectral channels are 3, 3, and 6, respectively. The use of these denoising algorithms improves the horizontal resolution of the subsequent aerosol optical parameter inversion results to 20 km and the vertical resolution to 48 m.

[0052] (4) Perform distance and system constant correction on the echo signal.

[0053] Based on step (3), the echo signal detected by the spaceborne HSRL is corrected for distance and system constant. Using the channel system constant calibrated in orbit and the response parameters and gain coefficients of the detector calibrated on the ground, the attenuation backscattering coefficients of the three channels are obtained, as shown in the following formula:

[0054]

[0055] Where r is the distance from the satellite platform to the atmospheric sounding area, The attenuation backscattering coefficient for the corresponding channel, and the return optical power. The input voltage amplitude represents the denoised voltage of the echo signal incident on the corresponding channel. i = C, M represent the reference channel and the hyperspectral molecular channel, respectively; j = ⊥, ∥ represent the polarization and parallel components, respectively; k = 1, 2, 3 represent the polarization channel, the reference parallel channel, and the hyperspectral channel, respectively. A1, A2, and A3 are the on-orbit calibration system constants for the 532nm polarization channel, the reference parallel channel, and the hyperspectral channel, respectively. R1, R2, and R3 are the detector response parameters for the 532nm polarization channel, the reference parallel channel, and the hyperspectral channel, respectively, measured on the ground. G1, G2, and G3 are the detector amplification gain coefficients for the 532nm polarization channel, the reference parallel channel, and the hyperspectral channel, respectively, measured on the ground.

[0056] (5) Establishment of molecular permeability lookup table and solution of aerosol permeability and atmospheric molecular parameters

[0057] To improve the efficiency of HSRL data processing, a molecular transmittance lookup table for the hyperspectral channels was established. This table utilizes meteorological profile data from the numerical weather prediction model reanalysis dataset. The Rayleigh scattering spectrum of atmospheric molecules was calculated using temperature and pressure profiles and the S6 atmospheric model. This spectrum was then convolved with the absorption spectrum of an iodine molecular filter measured in the laboratory to obtain the molecular transmittance data, which was then entered into the table. The transmittance of aerosols can be approximated as the result of convolving the Gaussian linear spectrum of laser light with the absorption spectrum of the iodine molecular filter. Simultaneously, using the temperature and pressure profiles from the numerical weather prediction model reanalysis dataset and combining Rayleigh scattering theory, the backscattering coefficient, extinction coefficient, and depolarization ratio of atmospheric molecules were calculated.

[0058] (6) Calculation of backscattering coefficient and scattering ratio

[0059] Using the attenuated backscattering coefficients of the three denoised channels, the molecular transmittance lookup table of the hyperspectral channel, and the aerosol transmittance, atmospheric molecular backscattering coefficient, and atmospheric molecular depolarization ratio, the aerosol backscattering coefficient β is calculated. a (r), the formula is as follows:

[0060]

[0061] Among them, T m (r) and T a(r) represents the transmittance of the molecular Rayleigh scattering echo signal and the aerosol Mie scattering echo signal after passing through the hyperspectral channel iodine molecular filter at a detection distance of r, respectively; δ(r) is the total atmospheric depolarization ratio, which can be expressed as the ratio of the attenuated backscattering coefficient of the polarization channel to the attenuated backscattering coefficient of the reference parallel channel; K(r) is the ratio of the attenuated backscattering coefficient of the reference parallel channel to that of the hyperspectral channel; δ m The depolarization ratio of atmospheric molecules; β m (r) and β a (r) represents the backscattering coefficients of atmospheric molecules and aerosols, respectively.

[0062] Using the calculated aerosol backscattering coefficient and atmospheric molecule backscattering coefficient, the scattering ratio is obtained using the following formula:

[0063] (7) Calculate the echo voltage signal-to-noise ratio

[0064] Using the raw voltage echo signals from the polarization channel and the reference parallel channel of the spaceborne lidar, and the corresponding background noise in the clean upper-level atmosphere, the voltage signal-to-noise ratio of the polarization channel and the reference parallel channel is calculated using the following formula:

[0065]

[0066] Among them, U i (r) represents the original voltage signal of the receiving channel. The average background noise of the high-altitude clean background atmosphere region of the receiving channel (first 100-500 voltage sampling points) is represented by i = ⊥ and ∥, which represent the polarization and parallel components, respectively. Considering the resolution of the aerosol optical parameter inversion results, the voltage signal-to-noise ratio profile is averaged 59 times in the horizontal direction and 2 times in the vertical direction, resulting in a horizontal resolution of 20 km and a vertical resolution of 48 m.

[0067] (8) Cloud and aerosol layer recognition

[0068] Using the calculated atmospheric scattering ratio, an appropriate scattering ratio threshold is set. Locations exceeding the threshold for cloud and aerosol scattering ratios are initially identified as clouds and aerosols, while locations below the threshold are initially identified as clean atmosphere without any layers. In the preliminary layer identification results, when the elevation of a layer is lower than the elevation of the lidar pointing point, that layer is marked as the ground surface.

[0069] Then, using the calculated voltage signal-to-noise ratio (VNR), different VNR thresholds are set according to different daytime and nighttime scenarios to optimize the initial hierarchical identification results, resulting in more accurate cloud and aerosol hierarchical identification results. In the initial hierarchical identification results, positions with a VNR greater than the VNR threshold are ultimately identified as clouds and aerosols; otherwise, they are classified as clean air.

[0070] (9) Cloud and aerosol layer regional processing

[0071] Using the results of cloud and aerosol layer identification, cloud and aerosol layers are merged into layered regions, while surface and clean atmosphere are merged into non-layered regions. Only the data from the layered regions are retained as valid data and used in subsequent aerosol optical parameter inversion.

[0072] (10) Preliminary inversion of optical parameters of clouds and aerosols

[0073] Using the calculated attenuated backscattered signal, molecular transmittance lookup table, aerosol transmittance, atmospheric molecular parameters, and layer identification results, the optical thickness (atmospheric optical thickness) of clouds and aerosols in the layered region is calculated using the following formula:

[0074]

[0075] Where τ(r) is the atmospheric optical thickness; α a (r) and α m (r) represents the extinction coefficients of aerosols and atmospheric molecules, respectively.

[0076] The optical thickness is smoothed and denoised using a moving average method to improve the accuracy of the extinction coefficient inversion. The aerosol extinction coefficient α is calculated using the following formula. a (r) and radar ratio S a Calculation of (r):

[0077]

[0078] Among them, S a (r) represents the lidar ratio of clouds and aerosols.

[0079] (11) Results of inversion of optical parameters of clouds and aerosols

[0080] Using the lidar ratio of clouds and aerosols obtained from the initial inversion, the lidar ratio is Gaussian smoothed and filtered to obtain the final lidar ratio inversion result. Then, combined with the relationship between the extinction coefficient and the lidar ratio, the optimized inversion result of the extinction coefficient of clouds and aerosols is obtained.

[0081] This invention utilizes echo voltage signals received by satellites for quality control and hierarchical identification, which can effectively identify and invert clouds and aerosols within the airborne altitude range, and can also be applied to the inversion of clouds and aerosols at a higher range; by establishing a molecular transmittance lookup table for hyperspectral channels, the inversion efficiency of satellite remote sensing data can be greatly improved.

Claims

1. A method for atmospheric particle inversion using a spaceborne hyperspectral lidar, characterized in that, include: S1. Use a spaceborne hyperspectral lidar system to detect and obtain backscattered signals from atmospheric molecules, clouds and aerosols. Obtain echo signals containing polarized signals, parallel channel signals and pure molecular scattering signals through hyperspectral detection. S2. Determine the laser ranging value and altitude corresponding to each sampling point in the echo signal; S3. Perform denoising and smoothing processing on the echo signal to obtain the denoised signal; S4. Perform distance and system constant correction on the denoised echo signal to obtain the corrected attenuated backscattered signal; S5. Establish a lookup table for the molecular transmittance of the hyperspectral channels and calculate the aerosol transmittance and atmospheric molecular parameters of the hyperspectral channels; S6. Using the attenuated backscattering signal, molecular transmittance lookup table, aerosol transmittance and atmospheric molecular parameters, the aerosol backscattering coefficient is initially inverted, and the atmospheric scattering ratio is calculated. S7. Calculate the voltage signal-to-noise ratio based on the original voltage echo signal and the background noise of the corresponding clean upper atmosphere area, and perform superposition and averaging processing. S8. Using atmospheric scattering ratio and voltage signal-to-noise ratio, set the threshold for cloud and aerosol layer identification, perform cloud and aerosol layer identification, and filter out the surface from the existing layers based on the elevation of the radar pointing point. S9. The cloud and aerosol layers are merged into a layered region, and the surface and clean atmosphere are merged into a non-layered region. Only the data of the layered region is retained as valid data to participate in the subsequent inversion of cloud and aerosol optical parameters. S10. Using attenuated backscattered signals, molecular transmittance lookup tables, aerosol transmittance, atmospheric molecular parameters, and layer identification results, preliminary inversion of atmospheric optical thickness, extinction coefficient, and radar ratio optical parameters is performed. S11. Taking advantage of the small dynamic range of lidar, Gaussian smoothing filtering is applied to the lidar ratio to obtain the final lidar ratio inversion result. Combined with the relationship between the extinction coefficient and the lidar ratio, the optimized inversion results of the cloud and aerosol extinction coefficients are obtained.

2. The atmospheric particle inversion method for spaceborne hyperspectral lidar according to claim 1, characterized in that, Step S2 involves solving for the laser ranging value and altitude corresponding to each sampling point in the echo signal. Specifically, the ranging value is calculated using the satellite position coordinates, the latitude and longitude of the laser radar pointing point, the elevation of the pointing point, and the delay time of the echo acquisition segment, through the laser ranging formula. Then, the altitude of each sampling point is solved using the ranging information, and the echo data acquisition points are matched to a specific height grid.

3. The atmospheric particle inversion method for spaceborne hyperspectral lidar according to claim 2, characterized in that, The laser ranging value r corresponding to each sampling point, i.e., the distance from the satellite to the sampling point, is calculated using the following formula: In the formula, T d T is the delay time of the echo acquisition segment. a N is a fixed time difference between the trigger pulse and the laser pulse emission, where N is the number of position points in the echo acquisition segment, DA is the echo signal sampling frequency, and C is the speed of light in vacuum. The altitude h of each sampling point is given by the following formula: h = l + dr (13) In the formula, l is the distance from the satellite platform to the ground pointing point, d is the elevation of the pointing point, and X 星 Y 星 Z 星 These are the X, Y, and Z coordinates of the satellite in the coordinate system.

4. The atmospheric particle inversion method for spaceborne hyperspectral lidar according to claim 1, characterized in that, Step S4 corrects the distance and system constant of the denoised echo signal to obtain the corrected attenuated backscattered signal. Specifically, the echo signal is corrected for distance and system constant, and the attenuated backscattering coefficients of the three channels are obtained by using the channel system constant calibrated on the orbit and the response parameters and gain coefficients of the detector calibrated on the ground.

5. The atmospheric particle inversion method for spaceborne hyperspectral lidar according to claim 1, characterized in that, Specifically, step S5 involves analyzing the temperature and pressure profiles, atmospheric model, and absorption spectra of the iodine molecular filter provided by the meteorological dataset based on the numerical weather prediction model, establishing a lookup table for the molecular transmittance of the hyperspectral channel, and calculating the aerosol transmittance and atmospheric molecular parameters of the hyperspectral channel.

6. The atmospheric particle inversion method for spaceborne hyperspectral lidar according to claim 1, characterized in that, Step S6 utilizes the attenuated backscattering signal, a molecular transmittance lookup table, aerosol transmittance, and atmospheric molecular parameters to initially retrieve the aerosol backscattering coefficient β. a (r), and calculate the atmospheric scattering ratio R(r) as follows: In the formula, T m (r) and T a (r) represents the transmittance of the molecular Rayleigh scattering echo signal and the aerosol Mie scattering echo signal after passing through the hyperspectral channel iodine molecular filter at a detection distance of r, respectively; δ(r) is the total atmospheric depolarization ratio, which is expressed as the ratio of the attenuated backscattering coefficient of the polarization channel to the attenuated backscattering coefficient of the reference parallel channel; K(r) is the ratio of the attenuated backscattering coefficient of the reference parallel channel to the attenuated backscattering coefficient of the hyperspectral channel. δ m β is the depolarization ratio of atmospheric molecules. m (r) is the backscattering coefficient of atmospheric molecules.

7. The atmospheric particle inversion method for spaceborne hyperspectral lidar according to claim 1, characterized in that, Step 7 calculates the voltage signal-to-noise ratio (UNR) of the receiving channel based on the original voltage echo signal and the background noise of the corresponding clean upper-level atmosphere. i (r), the formula is as follows: In the formula, U i (r) represents the original voltage signal of the receiving channel. The value represents the average background noise in the clean atmospheric region at high altitude of the receiving channel, and i = ⊥ and || represent the polarization and parallel components, respectively.

8. The atmospheric particle inversion method for spaceborne hyperspectral lidar according to claim 6, characterized in that, In step 10, the atmospheric optical thickness τ(r) and the aerosol extinction coefficient α are calculated. a (r) Extinction coefficient α of atmospheric molecules m (r) Radar ratio of aerosols S a (r), the formula is as follows: In the formula, τ(r) is the atmospheric optical thickness; is the attenuation backscattering coefficient of the hyperspectral channel.

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