On-Orbit Photon Counting Laser Ranging Forward Scattering Correction Method and Device

Abstract

The present invention provides a method and device for forward scattering correction of spaceborne photon counting lidar ranging, which relates to the technical field of lidar ranging, and is used to solve the technical problems that the prior art cannot meet the requirements of real-time processing for high-frequency observation tasks and it is difficult to achieve high-precision correction of forward scattering errors. The method includes: obtaining payload parameters of a spaceborne lidar system and atmospheric optical physical parameters under different conditions; generating an initial parameter set according to the payload parameters and the atmospheric optical physical parameters; using the Monte Carlo method to simulate a first change characteristic of the photon path under cloudy conditions compared with the photon path under clear sky conditions, and simulating a second change characteristic of the photon path under aerosol conditions compared with the photon path under clear sky conditions; fusing the first change characteristic and the second change characteristic to obtain forward scattering correction data; querying a corresponding forward scattering correction value in the forward scattering correction data according to the current atmospheric optical physical parameters to correct the ranging error.

Description

Technical Field

[0001] The present invention relates to the technical field of lidar ranging, and more particularly, to a method and device for forward scattering correction of spaceborne photon counting lidar ranging. Background Art

[0002] Spaceborne photon counting lidar (such as ICESat-2) has been widely used in fields such as global topographic surveying, glacier monitoring, forest surveying, and ocean exploration due to its high spatial resolution and sensitivity. This system uses single-photon detection technology and has the advantages of high sensitivity and high spatial resolution. However, when the laser beam passes through the atmosphere, especially clouds, photons are affected by the forward scattering of cloud particles and aerosols, causing some photon paths to deviate and be delayed in reaching the detector, resulting in ranging accuracy deviation. Atmospheric scattering also includes two cases: multiple scattering and single scattering, and multiple scattering is particularly significant in media such as thick clouds and fog. This complex scattering phenomenon not only reduces the reliability of lidar altimetry data, but also directly discards some effective observation data without effective correction means, thus limiting the operational application potential of spaceborne photon counting lidar.

[0003] Currently, the forward scattering correction of spaceborne photon counting lidar mainly relies on complex Monte Carlo simulations using the optical and physical property information of atmospheric clouds and aerosols to obtain correction values. By statistically simulating the random scattering paths of photons in the medium through Monte Carlo simulations, the propagation and scattering characteristics of photons can be accurately restored under ideal conditions. However, due to the extremely high computational resources and time costs of the Monte Carlo simulation method, it cannot meet the real-time processing requirements of high-frequency observation tasks. In addition, due to the complexity of the atmospheric multipath scattering effect, it is difficult to achieve high-precision correction of forward scattering errors. Summary of the Invention

[0004] In view of this, the present invention provides a method and device for forward scattering correction of spaceborne photon counting lidar ranging, so as to solve the technical problems that the prior art cannot meet the real-time processing requirements of high-frequency observation tasks and is difficult to achieve high-precision correction of forward scattering errors.

[0005] One aspect of the present invention provides a method for forward scattering correction of spaceborne photon counting lidar ranging, including: obtaining payload parameters of a spaceborne lidar system and atmospheric optical physical parameters under different conditions, where the atmospheric optical physical parameters under different conditions include atmospheric optical physical parameters under cloud conditions and atmospheric optical physical parameters under aerosol conditions; generating an initial parameter set according to the payload parameters and the atmospheric optical physical parameters under different conditions; according to the initial parameter set, using the Monte Carlo method to simulate the first change characteristics of the photon path under cloud conditions compared with the photon path under clear sky conditions, and simulating the second change characteristics of the photon path under aerosol conditions compared with the photon path under clear sky conditions; fusing the first change characteristics and the second change characteristics to obtain forward scattering correction data; in response to receiving a ranging task, querying the forward scattering correction value corresponding to the current atmospheric optical physical parameters in the forward scattering correction data according to the current atmospheric optical physical parameters to correct the ranging error.

[0006] According to an embodiment of the present invention, before using the Monte Carlo method to simulate the first change characteristics of the photon path under cloud conditions compared with the photon path under clear sky conditions and simulating the second change characteristics of the photon path under aerosol conditions compared with the photon path under clear sky conditions according to the initial parameter set, it further includes: determining a first initial photon number according to the standard deviation of the photon scattering path and the target error, where the first initial photon number is used to characterize the correction accuracy; determining a second initial photon number according to the total computational resource consumption required for a given photon and the average computational cost constant required for a single photon, where the second initial photon number is used to characterize the correction cost; determining a target initial photon number according to the first initial photon number and the second initial photon number.

[0007] According to an embodiment of the present invention, using the Monte Carlo method to simulate the first change characteristics of the photon path under cloud conditions compared with the photon path under clear sky conditions according to the initial parameter set includes: randomly generating a first initial photon position obeying a uniform distribution using the Monte Carlo method according to the initial parameter set and the target initial photon number, where the atmospheric optical physical parameters under cloud conditions in the initial parameter set are set to a non-uniform distribution state; calculating the first free path of the photon in the cloud medium according to the first initial photon position; updating the photon position according to the first free path to obtain the first path change characteristics of the photon in the cloud medium; calculating a first photon counting lidar forward scattering correction amount according to the first path change characteristics, where the first photon counting lidar forward scattering correction amount characterizes the first change characteristics of the photon path under cloud conditions compared with the photon path under clear sky conditions.

[0008] According to an embodiment of the present invention, based on an initial parameter set, using the Monte Carlo method to simulate the second change characteristics of the photon path under aerosol conditions compared to the photon path under clear sky conditions includes: based on the initial parameter set and the target initial photon number, using the Monte Carlo method to randomly generate a second initial photon position that obeys a uniform distribution, wherein the atmospheric optical physical parameters under aerosol conditions in the initial parameter set are set to a non-uniform distribution state; based on the second initial photon position, calculating the second free path of the photon in the aerosol medium; based on the second free path, updating the photon position to obtain the second path change characteristics of the photon in the aerosol medium; based on the second path change characteristics, calculating a second photon counting lidar forward scattering correction amount, wherein the second photon counting lidar forward scattering correction amount characterizes the second change characteristics of the photon path under aerosol conditions compared to the photon path under clear sky conditions.

[0009] According to an embodiment of the present invention, the atmospheric optical physical parameters under cloud conditions include: optical thickness of the cloud layer, effective radius of cloud particles, asymmetry factor of cloud particles, cloud layer thickness and cloud bottom height.

[0010] According to an embodiment of the present invention, the atmospheric optical physical parameters under aerosol conditions include: optical thickness of aerosol, effective radius of aerosol particles, asymmetry factor of aerosol particles, thickness of aerosol layer and height of bottom of aerosol layer.

[0011] According to an embodiment of the present invention, fusing the first change feature and the second change feature to obtain forward scatter correction data includes: generating a first 5-dimensional lookup table with non-uniform distribution according to the first change feature; generating a second 5-dimensional lookup table with non-uniform distribution according to the second change feature; fusing the first 5-dimensional lookup table and the second 5-dimensional lookup table to obtain a target 5-dimensional lookup table, wherein the target 5-dimensional lookup table represents the forward scatter correction data generated based on 5 dimensions.

[0012] According to an embodiment of the present invention, the method also includes: in response to not completely finding the forward scattering correction value corresponding to the current atmospheric optical and physical parameters in the forward scattering correction data, calculating the forward scattering correction intermediate value corresponding to the current atmospheric optical and physical parameters using a multidimensional interpolation algorithm; and correcting the ranging error based on the forward scattering correction intermediate value.

[0013] According to an embodiment of the present invention, the method also includes: in response to the range of the current atmospheric optical and physical parameters exceeding the range of the forward scattering correction data, using a boundary extrapolation mechanism to extrapolate a forward scattering correction estimated value corresponding to the current atmospheric optical and physical parameters; or using a neighboring value replacement mechanism to query a forward scattering correction replacement value corresponding to the current atmospheric optical and physical parameters; and correcting the ranging error according to the forward scattering correction estimated value or the forward scattering correction replacement value.

[0014] Another aspect of the present invention provides an on - satellite photon - counting lidar forward - scattering correction device, comprising: an acquisition module, configured to acquire payload parameters of an on - satellite lidar system and atmospheric optical and physical parameters under different conditions, wherein the atmospheric optical and physical parameters under different conditions include atmospheric optical and physical parameters under cloud conditions and atmospheric optical and physical parameters under aerosol conditions; a generation module, configured to generate an initial parameter set according to the payload parameters and the atmospheric optical and physical parameters under different conditions; a simulation module, configured to simulate, according to the initial parameter set, using the Monte Carlo method, a first variation characteristic of the photon path under cloud conditions compared with the photon path under clear - sky conditions, and a second variation characteristic of the photon path under aerosol conditions compared with the photon path under clear - sky conditions; a fusion module, configured to fuse the first variation characteristic and the second variation characteristic to obtain forward - scattering correction data; a correction module, configured to, in response to receiving a ranging task, query, according to the current atmospheric optical and physical parameters, a forward - scattering correction value corresponding to the current atmospheric optical and physical parameters in the forward - scattering correction data, and correct the ranging error.

[0015] Another aspect of the present invention provides an electronic device, comprising: one or more processors; a memory, configured to store one or more programs, wherein when the one or more programs are executed by the one or more processors, the one or more processors are caused to implement the method as described above.

[0016] Another aspect of the present invention provides a computer - readable storage medium, storing computer - executable instructions, which are used to implement the method as described above when executed.

[0017] Another aspect of the present invention provides a computer program product, which includes computer - executable instructions, and the instructions are used to implement the method as described above when executed.

[0018] Compared with the prior art, the on - satellite photon - counting lidar forward - scattering correction method and device provided by the present invention have at least the following beneficial effects:

[0019] (1) The on - satellite photon - counting lidar forward - scattering correction method and device provided by the embodiments of the present invention, by combining the optical and physical characteristics of atmospheric clouds and aerosols, pre - generate forward - scattering correction data (configurable as a look - up table structure) using refined Monte Carlo simulation. In practical applications, only a small number of input parameters such as atmospheric optical depth and aerosol mode are required, and the correction value can be quickly queried from the forward - scattering correction data to correct the forward - scattering error. It is particularly suitable for achieving high - precision lidar ranging correction in complex atmospheric environments and under cloudy and aerosol - rich conditions. Since the fast - query mechanism significantly shortens the correction time, it can meet the real - time processing requirements of high - frequency observation tasks of on - satellite photon - counting lidars.

[0020] (2) The on-orbit photon counting lidar forward scattering correction method and device provided by the embodiments of the present invention construct a high-resolution non-uniform 5D look-up table by combining the optical and physical properties (such as optical thickness, particle size, asymmetry factor, physical thickness, and height) of clouds and aerosols in five dimensions. Since the method of introducing the resolution of the non-uniform look-up table is adopted, the balance between correction accuracy and calculation efficiency is ensured within the range of key parameters, and the applicable range of the technology is further broadened.

[0021] (3) The on-orbit photon counting lidar forward scattering correction method and device provided by the embodiments of the present invention are optimized by adopting a multi-dimensional interpolation algorithm, ensuring that accurate correction values can be obtained under any input conditions.

[0022] (4) The on-orbit photon counting lidar forward scattering correction method and device provided by the embodiments of the present invention can be flexibly adjusted according to the payload parameters (working wavelength, field of view angle, and orbital altitude) of different lidars to adapt to different on-orbit lidar systems. In addition, it can be further combined with real-time observation data for dynamic update, and has good expandability. Description of the Drawings

[0023] Through the following description of the embodiments of the present invention with reference to the drawings, the above and other objects, features, and advantages of the present invention will become clearer. In the drawings:

[0024] Figure 1 Schematically shows a flowchart of the on-orbit photon counting lidar forward scattering correction method according to an embodiment of the present invention;

[0025] Figure 2 Schematically shows a graph of the variation trend of the forward scattering correction value with the cloud layer height and the effective radius of cloud particles under cloud conditions according to an embodiment of the present invention;

[0026] Figure 3 Schematically shows a graph of the variation trend of the forward scattering correction value with the cloud layer height and the effective radius of cloud particles under aerosol conditions according to an embodiment of the present invention;

[0027] Figure 4 Schematically shows a graph of the linear regression analysis result between the estimated value of the corrected look-up table and the Monte Carlo calculated value under cloud conditions according to an embodiment of the present invention;

[0028] Figure 5 Schematically shows a graph of the linear regression analysis result between the estimated value of the corrected look-up table and the Monte Carlo calculated value under aerosol conditions according to an embodiment of the present invention;

[0029] Figure 6 Schematically shows a schematic diagram of the on-orbit photon counting lidar forward scattering correction method according to an embodiment of the present invention;

[0030] Figure 7 Schematically shows a structural block diagram of an on - satellite photon - counting laser ranging forward - scattering correction device according to an embodiment of the present invention;

[0031] Figure 8 Schematically shows a structural block diagram of an electronic device suitable for implementing an on - satellite photon - counting laser ranging forward - scattering correction method according to an embodiment of the present invention. Detailed implementation manners

[0032] Hereinafter, embodiments of the present invention will be described with reference to the accompanying drawings. However, it should be understood that these descriptions are merely exemplary and are not intended to limit the scope of the present invention. In the following detailed description, for the sake of explanation, many specific details are set forth to provide a comprehensive understanding of the embodiments of the present invention. However, obviously, one or more embodiments can also be implemented without these specific details. In addition, in the following description, descriptions of well - known structures and technologies are omitted to avoid unnecessarily confusing the concepts of the present invention.

[0033] The terms used herein are merely for describing specific embodiments and are not intended to limit the present invention. The terms "including", "comprising", etc. used herein indicate the presence of the described features, steps, operations, and / or components, but do not exclude the presence or addition of one or more other features, steps, operations, or components.

[0034] All terms (including technical and scientific terms) used herein have the meanings commonly understood by those skilled in the art, unless otherwise defined. It should be noted that the terms used herein should be interpreted as having a meaning consistent with the context of this specification and should not be interpreted in an idealized or overly rigid manner.

[0035] In the case of using expressions such as "at least one of A, B, and C, etc.", generally, it should be interpreted according to the meaning commonly understood by those skilled in the art (for example, "a system having at least one of A, B, and C" should include, but is not limited to, a system having only A, only B, only C, having A and B, having A and C, having B and C, and / or having A, B, and C, etc.).

[0036] In the embodiments of the present invention, in aspects such as the collection, update, analysis, processing, use, transmission, provision, disclosure, storage, etc. of the involved data (for example, including but not limited to user personal information), they all comply with the provisions of relevant laws and regulations, are used for legal purposes, and do not violate public order and good customs. In particular, necessary measures are taken for user personal information to prevent illegal access to user personal information data and to maintain the security of user personal information and network security.

[0037] Spaceborne photon counting lidar (such as ICESat-2) has been widely used in global topographic surveying, glacier monitoring, forest surveying, ocean exploration and other fields due to its high spatial resolution and sensitivity. This system uses single-photon detection technology and has the advantages of high sensitivity and high spatial resolution. However, when the laser beam passes through the atmosphere, especially clouds, photons are affected by the forward scattering of cloud particles and aerosols, causing partial photon path deviation and delayed arrival at the detector, resulting in ranging accuracy deviation. Atmospheric scattering also includes two cases: multiple scattering and single scattering, among which multiple scattering is particularly significant in media such as thick clouds and fog. This complex scattering phenomenon not only reduces the reliability of lidar altimetry data, but also directly discards some valid observation data without effective correction means, thus limiting the potential of spaceborne photon counting lidar for operational applications.

[0038] Currently, the forward scattering correction of spaceborne photon counting lidar mainly relies on complex Monte Carlo simulations through the optical and physical property information of atmospheric clouds and aerosols to obtain correction values. By statistically simulating the random scattering paths of photons in the medium through Monte Carlo simulation, the propagation and scattering characteristics of photons can be accurately restored under ideal conditions.

[0039] However, the Monte Carlo simulation has extremely high requirements for computing resources and time, and a large number of photon trajectory samples are needed to obtain statistically significant results, making it difficult to meet the real-time processing requirements of high-frequency observation tasks. Therefore, a mature operational scattering correction method has not yet been formed, resulting in the atmospheric scattering effect still being the key bottleneck for improving the utilization rate and reliability of lidar altimetry data. In addition, the Monte Carlo simulation requires comprehensive and accurate input data, including parameters such as the distribution, optical thickness, and particle size of clouds and aerosols, and these parameters usually rely on other observation means to obtain, increasing the possibility of error propagation.

[0040] It can be seen that the existing technology has technical problems that it cannot meet the real-time processing requirements of high-frequency observation tasks and it is difficult to achieve high-precision correction of forward scattering errors.

[0041] Based on this, the embodiments of the present invention provide a method for forward scattering correction of spaceborne photon counting lidar to solve the technical problems that the existing technology cannot meet the real-time processing requirements of high-frequency observation tasks and it is difficult to achieve high-precision correction of forward scattering errors.

[0042] To make the objectives, technical solutions and advantages of the present invention clearer and more understandable, the following further elaborates on the present invention in detail with reference to specific embodiments and the accompanying drawings.

[0043] Figure 1 Schematically shows a flowchart of a method for forward scattering correction of spaceborne photon counting lidar according to an embodiment of the present invention.

[0044] As Figure 1 shown, the on-orbit photon counting lidar forward scattering correction method of this embodiment may include operations S1 to S5, for example.

[0045] In operation S1, obtain the payload parameters of the on-orbit lidar system and the atmospheric optical and physical parameters under different conditions. Among them, the atmospheric optical and physical parameters under different conditions include the atmospheric optical and physical parameters under cloud conditions and the atmospheric optical and physical parameters under aerosol conditions.

[0046] In operation S2, generate an initial parameter set according to the payload parameters and the atmospheric optical and physical parameters under different conditions.

[0047] In operation S3, according to the initial parameter set, use the Monte Carlo method to simulate the first change characteristic of the photon path under cloud conditions compared with the photon path under clear sky conditions, and simulate the second change characteristic of the photon path under aerosol conditions compared with the photon path under clear sky conditions.

[0048] In operation S4, fuse the first change characteristic and the second change characteristic to obtain the forward scattering correction data.

[0049] In operation S5, in response to receiving a ranging task, according to the current atmospheric optical and physical parameters, query the forward scattering correction value corresponding to the current atmospheric optical and physical parameters in the forward scattering correction data to correct the ranging error.

[0050] The on-orbit photon counting lidar forward scattering correction method provided by the embodiment of the present invention combines the optical and physical characteristics of clouds and aerosols, and pre-uses refined Monte Carlo simulation to generate forward scattering correction data (which can be configured as a look-up table structure). In practical applications, only a small number of input parameters such as atmospheric optical thickness and aerosol mode are required, and the correction value can be quickly obtained by querying in the forward scattering correction data to correct the forward scattering error, which is especially suitable for realizing high-precision lidar ranging correction under complex atmospheric environments and cloudy and aerosol-rich conditions. Since the fast query mechanism significantly shortens the correction time, it can meet the real-time processing requirements of the high-frequency observation tasks of on-orbit photon counting lidars.

[0051] In this embodiment, operation S1 obtains the payload parameters of the on-orbit lidar system and the atmospheric optical and physical parameters under different conditions. Specifically, the following parameters can be obtained:

[0052] The payload parameters of the on-orbit lidar system include, for example:

[0053] λ: The working wavelength of the lidar (unit: nanometer)

[0054] FOV: The field of view angle of the lidar (unit: micro-radian)

[0055] Zorb : Orbit altitude where the lidar is located (unit: km)

[0056] Atmospheric optical physical parameters under cloud conditions, such as including:

[0057] τ c : Optical thickness of the cloud layer

[0058] r c : Effective radius of cloud particles (unit: μm)

[0059] g c : Asymmetry factor of cloud particles

[0060] D c : Thickness of the cloud layer (unit: km)

[0061] H c : Bottom height of the cloud layer (unit: km)

[0062] Atmospheric optical physical parameters under aerosol conditions, such as including:

[0063] τ a : Optical thickness of the aerosol

[0064] r a : Effective radius of aerosol particles (unit: μm)

[0065] g a : Asymmetry factor of aerosol particles

[0066] D a : Thickness of the aerosol layer (unit: km)

[0067] H a : Bottom height of the aerosol layer (unit: km)

[0068] In this embodiment, operation S2 generates an initial parameter set according to the payload parameters and the atmospheric optical physical parameters under different conditions. For example, the above parameters can be integrated to form a complete initial parameter set .

[0069]

[0070] After generating the initial parameter set, in order to improve the calibration accuracy and reduce computing resources, it is necessary to determine the optimal initial number of photons. That is, before performing operation S3 to simulate the first change characteristics of the photon path under cloud conditions compared with the photon path under clear sky conditions and the second change characteristics of the photon path under aerosol conditions compared with the photon path under clear sky conditions according to the initial parameter set using the Monte Carlo method, it is necessary to first determine the initial number of photons

[0071] According to an embodiment of the present invention, determining the initial number of photons may include, for example:

[0072] Determining a first initial number of photons according to the standard deviation of the photon scattering path and the target error, where the first initial number of photons is used to characterize the calibration accuracy;

[0073] Determining a second initial number of photons according to the total computing resource consumption required for a given photon and the average computing cost constant required for a single photon, where the second initial number of photons is used to characterize the calibration cost;

[0074] Determining the target initial number of photons according to the first initial number of photons and the second initial number of photons.

[0075] Since the initial number of photons N directly affects the calibration accuracy and computing cost, in this embodiment, computing accuracy and computing resources are fully considered when determining the initial number of photons N.

[0076] For the consideration of computing accuracy, the initial number of photons N1 (the first initial number of photons) can be determined according to the following formula:

[0077]

[0078] where σ represents the standard deviation of the photon scattering path, represents the target error.

[0079] For the consideration of computing resources, the initial number of photons N2 (the second initial number of photons) can be determined according to the following formula:

[0080]

[0081] where c represents the average computing cost constant required for a single photon, and the function R(N) is used to estimate the resource consumption required for a given photon N.

[0082] Taking the above two aspects into consideration, the model for determining the initial number of photons N can be optimized as:

[0083]

[0084] where the first term is used to minimize the statistical error, the second term considers the computing resource consumption, is a regularization parameter that weighs the importance of the two.

[0085] This optimization model helps to optimize the use of computing resources while ensuring the simulation accuracy. Therefore, according to this optimization model, the target initial number of photons N can be finally determined.

[0086] After determining the target initial number of photons N, next, according to the initial parameter set With the target initial photon number N, the Monte Carlo method is used to separately simulate and obtain:

[0087] (1) The change ΔL in the photon path under cloudy conditions compared to the photon path under clear sky conditions c (the first change feature).

[0088] (2) The change ΔL in the photon path under aerosol conditions compared to the photon path under clear sky conditions a (the second change feature).

[0089] According to an embodiment of the present invention, the first change feature of the photon path under cloudy conditions compared to the photon path under clear sky conditions simulated by the Monte Carlo method in operation S3 according to the initial parameter set includes:

[0090] According to the initial parameter set and the target initial photon number, the Monte Carlo method is used to randomly generate a first initial photon position that follows a uniform distribution, where the atmospheric optical physical parameters under cloudy conditions in the initial parameter set are set to a non-uniform distribution state;

[0091] According to the first initial photon position, calculate the first free path of the photon in the cloud medium;

[0092] According to the first free path, update the photon position to obtain the first path change feature of the photon in the cloud medium;

[0093] According to the first path change feature, calculate the first photon counting lidar forward scattering correction amount, where the first photon counting lidar forward scattering correction amount characterizes the first change feature of the photon path under cloudy conditions compared to the photon path under clear sky conditions.

[0094] In this embodiment, the Monte Carlo method is used to trace the path of multiple scattering of photons in the cloud medium, and record the state of photon propagation in the cloud medium to analyze its scattering characteristics and path distribution.

[0095] For example, first according to the initial parameter set and the target initial photon number N, a series of random numbers (the first initial photon position) R ∈ [0, 1] that follow a uniform distribution are generated, and the photon free path and the new photon position of the photon are calculated.

[0096] It should be noted that in this embodiment, the atmospheric optical physical parameters under cloud conditions in the initial parameter set are set to a non-uniform distribution state, for example:

[0097] τ c = [0.01:0.02:0.1 0.2:0.1:0.9 1.0:0.2:2.0]

[0098] r c =[1:1:80 82:100]

[0099] g c =[-0.9:0.1:0 0.1:0.1:0.5 0.6:0.05:0.9]

[0100] D c =[0.3:0.2:3]

[0101] H c =[0.5:0.2:6]

[0102] Then, calculate the photon free path L (the first free path). The free path L of photons in the cloud medium can be calculated by the following formula:

[0103]

[0104] where: δ represents the extinction coefficient, and R ∈ [0, 1].

[0105] Further, update the photon position. The photon propagates along the current direction and the position is updated to:

[0106]

[0107] where, represents the position of the current photon, represents the position of the photon after update.

[0108] According to the updated data of the photon position, the path change characteristics (the first path change characteristics) of photons in the cloud layer medium can be obtained.

[0109] Finally, calculate the forward scattering correction amount of the first photon counting lidar, that is, the change ΔL of the photon path under cloudy conditions compared to the photon path under clear sky conditions c (the first change characteristic).

[0110] Figure 2 Schematically shows the trend diagram of the forward scattering correction value (unit: centimeter) under cloud conditions according to the embodiments of the present invention with respect to the cloud layer height (unit: kilometer) and the effective radius of cloud particles (unit: micron).

[0111] Such as Figure 2As shown, when the effective radius of cloud particles is small (e.g., 0.1 to 1 micron), the forward scattering effect is significantly enhanced, resulting in a larger correction value; while when the effective radius of cloud particles increases to a certain extent (e.g., above 10 microns), the correction value gradually decreases. At the same time, the cloud layer height also has a significant impact on the forward scattering correction value: a lower cloud layer height (e.g., below 1 kilometer) corresponds to a larger correction value, while the correction value changes more smoothly for a higher cloud layer height (e.g., 4 to 6 kilometers). According to the analysis results of this figure, the distribution range of the lookup table parameters can be optimized, especially increasing the resolution in the small particle size range and low cloud layer height to more accurately reflect the variation characteristics of the forward scattering correction value, thereby improving the accuracy and efficiency of the correction.

[0112] According to an embodiment of the present invention, in operation S3, according to the initial parameter set, the second variation characteristics of the photon path under aerosol conditions compared to the photon path under clear sky conditions simulated by the Monte Carlo method include:

[0113] According to the initial parameter set and the target initial number of photons, the Monte Carlo method is used to randomly generate the second initial photon positions that follow a uniform distribution, where the atmospheric optical physical parameters under aerosol conditions in the initial parameter set are set to a non-uniform distribution state;

[0114] According to the second initial photon positions, calculate the second free path of the photons in the aerosol medium; according to the second free path, update the photon positions to obtain the second path variation characteristics of the photons in the aerosol medium;

[0115] According to the second path variation characteristics, calculate the second forward scattering correction amount of the photon counting lidar, where the second forward scattering correction amount of the photon counting lidar characterizes the second variation characteristics of the photon path under aerosol conditions compared to the photon path under clear sky conditions.

[0116] In this embodiment, the Monte Carlo method is also used to trace the paths of photons scattered multiple times in the aerosol medium and record the propagation state of the photons in the cloud medium to analyze their scattering characteristics and path distributions.

[0117] Since the principle of tracing the paths of photons scattered multiple times in the aerosol medium by the Monte Carlo method is the same as that in the cloud medium, therefore, the process of tracing the paths of photons scattered multiple times in the aerosol medium by the Monte Carlo method will not be described in detail in this embodiment. For details, reference can be made to the above process of tracing the paths of photons scattered multiple times in the cloud medium by the Monte Carlo method.

[0118] It should be noted that in this embodiment, the initial parameter set the atmospheric optical physical parameters under aerosol conditions are also set to a non-uniform distribution state, for example:

[0119] τ a=[0.01:0.02:0.1 0.2:0.1:1]

[0120] r a =[0.1:0.2:5 6:1:50]

[0121] g a =[0.6:0.05:0.9]

[0122] D a =[0.3:0.2:3]

[0123] H a =[0.5:0.2:6]

[0124] Based on the same process as the cloud medium, the forward scattering correction amount of the second photon counting lidar is finally calculated, that is, the change ΔL of the photon path under aerosol conditions compared to the photon path under clear sky conditions a (the second change feature).

[0125] Figure 3 Schematically shows the variation trend diagram of the forward scattering correction value (unit: centimeter) under aerosol conditions according to the embodiments of the present invention with respect to the cloud layer height (unit: kilometer) and the effective radius of cloud particles (unit: micron).

[0126] As Figure 3 shown, according to the relationship between forward scattering and aerosol layer height and effective particle radius, it can be seen that in the region with a steeper change, the parameter step size can be set smaller.

[0127] After calculating the first change feature ΔL c and the second change feature ΔL a , a non-uniform 5D look-up table 5DLUT c and 5DLUT a .

[0128] According to the embodiments of the present invention, operation S4 fuses the first change feature and the second change feature to obtain forward scattering correction data including:

[0129] Generate a first 5D look-up table with a non-uniform distribution according to the first change feature;

[0130] Generate a second 5D look-up table with a non-uniform distribution according to the second change feature;

[0131] Fuse the first 5D look-up table and the second 5D look-up table to obtain a target 5D look-up table, where the target 5D look-up table represents forward scattering correction data generated based on 5 dimensions.

[0132] In this embodiment, according to the first change feature ΔL cand the second variation feature ΔL a Generate a non-uniform 5D look-up table 5DLUT respectively c and the 5DLUT a After that, fuse the non-uniform 5D look-up table 5DLUT c and the 5DLUT a to obtain the final target 5D look-up table

[0133] The spaceborne photon counting laser ranging forward scattering correction method and device provided by the embodiments of the present invention construct a high-resolution non-uniform 5D look-up table by combining the optical and physical characteristics of clouds and aerosols in 5 dimensions (such as optical thickness, particle size, asymmetry factor, physical thickness, and height, etc.). Since the method of introducing the resolution of the non-uniform look-up table is adopted, the balance between correction accuracy and calculation efficiency is ensured within the range of key parameters, and the applicable range of the technology is further broadened

[0134] After generating the 5D look-up table, in order to improve the correction accuracy, the look-up table can also be corrected for accuracy. Specifically, the predicted value P generated for the look-up table can be used LUT and the Monte Carlo calculated value P MC to re-calibrate the predicted data through linear regression to make it closer to the ideal Monte Carlo calculated value

[0135] For example, first perform the regression analysis of the predicted value P LUT and the Monte Carlo calculated value P MC and then perform the correction verification

[0136] Regarding the predicted value P LUT and the Monte Carlo calculated value P MC Regression analysis:

[0137] Assume that the initially fitted regression line is: , where a represents the original slope and b represents the intercept. Ideally, it is hoped that the relationship between the output value and the actual value of the look-up table is one-to-one, that is, the slope a should be 1 and the intercept b should be close to 0. By calculating the deviation between the actual regression line and the ideal regression line (with a slope of 1), the correction amount to be performed can be determined, and the adjustment formula is:

[0138]

[0139] Through this formula, convert the predicted value P in all look-up tables LUT to the corrected predicted value so that the new fitted line is closer, that is: .

[0140] Regarding the correction verification:

[0141] Perform a second linear regression analysis on the corrected data to verify the correction effect. The accuracy of the corrected data can be evaluated by calculating the new root mean square error (RMSE) and mean absolute error (MAE). Conduct a statistical test and use the coefficient of determination R 2 value to evaluate the goodness of fit and the effectiveness of data correction. The closer the R 2 value is to 1, the higher the model interpretability and the better the data fitting.

[0142] Figure 4 Schematically shows the linear regression analysis result graph between the estimated value of the corrected look-up table and the Monte Carlo calculated value under cloud conditions according to an embodiment of the present invention.

[0143] Figure 5 Schematically shows the linear regression analysis result graph between the estimated value of the corrected look-up table and the Monte Carlo calculated value under aerosol conditions according to an embodiment of the present invention.

[0144] As Figure 4 and Figure 5 shown, the degree of fit between the two is very high, and the correlation coefficient R 2 of the linear regression both reaches 0.99, indicating that the predicted value of the look-up table can well reflect the actual Monte Carlo calculated value. At the same time, the root mean square error (RMSE) and mean absolute error (MAE) are both less than 0.22 cm, further proving the high accuracy of the look-up table. The regression slopes both reach 0.97, which is very close to the ideal slope of 1, indicating that the correction effect is very ideal.

[0145] In this embodiment, operation S5 responds to receiving a ranging task, and according to the current atmospheric optical physical parameters, queries the forward scattering correction value corresponding to the current atmospheric optical physical parameters in the forward scattering corrected data to correct the ranging error. Specifically, it can be:

[0146] When the lidar system performs ranging, collect the current atmospheric optical physical parameters (since the look-up table has been refined, only a small number of parameters need to be collected), then according to the current atmospheric optical physical parameters, look up the corresponding forward scattering correction value in the look-up table, and then use this forward scattering correction value to correct the ranging error. The specific formula is as follows:

[0147]

[0148] Wherein, L corr represents the corrected ranging value, L obs represents the uncorrected ranging value of the lidar ranging, and ΔL represents the forward scattering correction value retrieved through the look-up table.

[0149] The on-orbit photon counting laser ranging forward scattering correction method and device provided by the embodiments of the present invention can achieve efficient correction with only a small number of input parameters, avoid error propagation caused by the high requirements for the comprehensiveness and accuracy of input data in the prior art, significantly reduce the calculation amount and the difficulty of real-time processing, and improve the feasibility and accuracy of laser altimetry data in operational applications.

[0150] According to an embodiment of the present invention, the on-orbit photon counting laser ranging forward scattering correction method further includes:

[0151] In response to the forward scattering correction value corresponding to the current atmospheric optical physical parameters not being fully queried in the forward scattering correction data, use the multi-dimensional interpolation algorithm to calculate the forward scattering correction intermediate value corresponding to the current atmospheric optical physical parameters;

[0152] Correct the ranging error according to the forward scattering correction intermediate value.

[0153] In this embodiment, since the interval of parameter points in the look-up table is limited and the actual observation conditions may fall between the grid points of the look-up table, the multi-dimensional interpolation algorithm is adopted in this embodiment to smooth the look-up table to ensure that accurate correction factors can be provided under any input conditions.

[0154] When the input parameters do not exactly match the grid points of the look-up table, use the multi-dimensional interpolation algorithm to calculate the correction factor.

[0155] The on-orbit photon counting laser ranging forward scattering correction method and device provided by the embodiments of the present invention are optimized by adopting the multi-dimensional interpolation algorithm, ensuring that accurate correction values can be obtained under any input conditions.

[0156] According to an embodiment of the present invention, the on-orbit photon counting laser ranging forward scattering correction method further includes:

[0157] In response to the range of the current atmospheric optical physical parameters exceeding the range of the forward scattering correction data, use the boundary extrapolation mechanism to calculate the forward scattering correction extrapolated value corresponding to the current atmospheric optical physical parameters;

[0158] Or use the adjacent value substitution mechanism to query the forward scattering correction substitution value corresponding to the current atmospheric optical physical parameters; correct the ranging error according to the forward scattering correction extrapolated value or the forward scattering correction substitution value.

[0159] In this embodiment, if the input parameters exceed the range of the look-up table, ensure the robustness of the algorithm by boundary extrapolation or using adjacent values instead.

[0160] Boundary extrapolation: Boundary extrapolation refers to when the input parameters exceed the range of the look-up table, using the boundary values (i.e., the minimum or maximum values) of the look-up table for estimation, or calculating the values beyond the range according to a certain rule. Specifically:

[0161] If the input parameter is greater than the maximum value of the look-up table, the maximum value in the look-up table is used for processing. If the input parameter is less than the minimum value of the look-up table, the minimum value in the look-up table is used for processing.

[0162] Another case is that, based on the relationship between the input parameter and the boundary values of the look-up table, a certain mathematical model (such as linear extrapolation) can be used to predict the results beyond the range.

[0163] This method can ensure that even if the input data exceeds the range of the look-up table, the system can still output a reasonable result.

[0164] Replacement with neighboring values: When the input parameter exceeds the range of the look-up table, the closest value in the look-up table can be used for replacement to ensure the continuous operation of the system. Specifically:

[0165] If the input value is smaller than the minimum value in the look-up table or larger than the maximum value, the closest known value can be selected to replace the value beyond the range. For example, if the minimum value of the look-up table is X and the maximum value is Y, when the input value is less than X, then X is used; when the input value is greater than Y, then Y is used.

[0166] This method does not perform calculation or extrapolation, but directly uses the existing values in the look-up table, which is usually more conservative and avoids the inaccuracy that may be brought by extrapolation.

[0167] It should be noted that the on-board photon counting lidar forward scattering correction method provided by the embodiments of the present invention can be flexibly adjusted according to the payload parameters (operating wavelength, field of view angle, and orbital altitude) of different lidars to adapt to different on-board lidar systems. In addition, it can be further dynamically updated in combination with real-time observation data and has good expandability.

[0168] Figure 6 Schematically shows the principle diagram of the on-board photon counting lidar forward scattering correction method according to the embodiments of the present invention.

[0169] As Figure 6 shown, the principle of the on-board photon counting lidar forward scattering correction method of the embodiments of the present invention is as follows:

[0170] Obtain the payload parameters (operating wavelength, field of view angle, and orbital altitude) of the on-board lidar system, as well as the atmospheric optical physical parameters under different conditions.

[0171] Among them, the atmospheric optical physical parameters under different conditions include:

[0172] Atmospheric optical physical parameters under cloud conditions (optical thickness of clouds, effective radius of cloud particles, asymmetry factor of cloud particles, cloud thickness, and cloud bottom height);

[0173] Atmospheric optical physical parameters under aerosol conditions (optical thickness of aerosols, effective radius of aerosol particles, asymmetry factor of aerosol particles, aerosol layer thickness, and aerosol layer bottom height).

[0174] Generate an initial parameter set according to the payload parameters and the atmospheric optical physical parameters under different conditions.

[0175] According to the initial parameter set, use the Monte Carlo method to simulate the first change characteristics of the photon path under cloud conditions compared with the photon path under clear sky conditions, and simulate the second change characteristics of the photon path under aerosol conditions compared with the photon path under clear sky conditions.

[0176] Fuse the first change characteristics and the second change characteristics to obtain forward scattering correction data (non-uniform look-up table).

[0177] In response to receiving a ranging task, query the forward scattering correction value corresponding to the current atmospheric optical physical parameters in the forward scattering correction data according to the current atmospheric optical physical parameters, and correct the ranging error.

[0178] It should be noted that the principle of the on-board photon counting laser ranging forward scattering correction method in the embodiments of the present invention corresponds to the operation process of the previous on-board photon counting laser ranging forward scattering correction method. Therefore, the specific details are not described herein again.

[0179] Figure 7 Schematically shows a structural block diagram of an on-board photon counting laser ranging forward scattering correction device according to an embodiment of the present invention.

[0180] As Figure 7 shown, the on-board photon counting laser ranging forward scattering correction device 700 according to the embodiment of the present invention includes: an acquisition module 710, a generation module 720, a simulation module 730, a fusion module 740, and a correction module 750.

[0181] Among them, the acquisition module 710 is used to acquire the payload parameters of the on-board lidar system and the atmospheric optical physical parameters under different conditions, where the atmospheric optical physical parameters under different conditions include the atmospheric optical physical parameters under cloud conditions and the atmospheric optical physical parameters under aerosol conditions.

[0182] The generation module 720 is used to generate an initial parameter set according to the payload parameters and the atmospheric optical physical parameters under different conditions.

[0183] The simulation module 730 is configured to simulate, according to an initial parameter set, by using the Monte Carlo method, a first variation characteristic of a photon path under cloudy conditions as compared with a photon path under clear-sky conditions, and a second variation characteristic of a photon path under aerosol conditions as compared with a photon path under clear-sky conditions.

[0184] The fusion module 740 is configured to fuse the first variation characteristic and the second variation characteristic to obtain forward scattering correction data.

[0185] The correction module 750 is configured to, in response to receiving a ranging task, query, according to current atmospheric optical physical parameters, a forward scattering correction value corresponding to the current atmospheric optical physical parameters in the forward scattering correction data, and correct the ranging error.

[0186] Any multiple of the modules, sub-modules, units, and sub-units according to the embodiments of the present invention, or at least part of the functions of any multiple thereof, can be implemented in one module. Any one or more of the modules, sub-modules, units, and sub-units according to the embodiments of the present invention can be split into multiple modules for implementation. Any one or more of the modules, sub-modules, units, and sub-units according to the embodiments of the present invention can be at least partially implemented as a hardware circuit, such as a field programmable gate array (FPGA), a programmable logic array (PLA), a system on a chip, a system on a substrate, a system on a package, an application specific integrated circuit (ASIC), or can be implemented by any other reasonable way of integrating or packaging the circuit in hardware or firmware, or implemented in any one of the three implementation manners of software, hardware, and firmware, or in a suitable combination of any several thereof. Alternatively, one or more of the modules, sub-modules, units, and sub-units according to the embodiments of the present invention can be at least partially implemented as a computer program module, and when the computer program module is run, the corresponding functions can be executed.

[0187] For example, any combination of the acquisition module 710, the generation device 720, the simulation module 730, the fusion module 740, and the calibration module 750 can be combined and implemented in one module / unit / sub-unit, or any one of the modules / units / sub-units can be split into multiple modules / units / sub-units. Alternatively, at least part of the functions of one or more of these modules / units / sub-units can be combined with at least part of the functions of other modules / units / sub-units and implemented in one module / unit / sub-unit. According to an embodiment of the present invention, at least one of the acquisition module 710, the generation device 720, the simulation module 730, the fusion module 740, and the calibration module 750 can be at least partially implemented as a hardware circuit, such as a field-programmable gate array (FPGA), a programmable logic array (PLA), a system-on-chip, a system-on-substrate, a system-on-package, an application-specific integrated circuit (ASIC), or can be implemented by any other reasonable means such as hardware or firmware for integrating or packaging circuits, or can be implemented in any one of the three implementation manners of software, hardware, and firmware, or in an appropriate combination of any several of them. Alternatively, at least one of the acquisition module 710, the generation device 720, the simulation module 730, the fusion module 740, and the calibration module 750 can be at least partially implemented as a computer program module, and when the computer program module runs, it can execute corresponding functions.

[0188] It should be noted that the part of the track association device based on parameter space transformation in the embodiments of the present invention corresponds to the part of the track association method based on parameter space transformation in the embodiments of the present invention. For the description of the part of the track association device based on parameter space transformation, please refer to the part of the track association method based on parameter space transformation, and details are not described herein again.

[0189] Figure 8 Schematically shows a structural block diagram of an electronic device suitable for implementing the forward scattering correction method of spaceborne photon counting laser ranging according to an embodiment of the present invention. Figure 8 The shown electronic device is only an example and should not impose any limitation on the functions and usage scope of the embodiments of the present invention.

[0190] Such as Figure 8As shown, the electronic device 800 according to an embodiment of the present invention includes a processor 801, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 802 or a program loaded from a storage section 808 into a random access memory (RAM) 803. The processor 801 can include, for example, a general-purpose microprocessor (e.g., CPU), an instruction set processor, and / or a related chipset, and / or a dedicated microprocessor (e.g., an application-specific integrated circuit (ASIC)), and so on. The processor 801 can also include on-board memory for caching purposes. The processor 801 can include a single processing unit or multiple processing units for performing different actions of the method flow according to an embodiment of the present invention.

[0191] In the storage section 808, various programs and data required for the operation of the electronic device 800 are stored. The processor 801, the ROM 802, and the storage section 808 are connected to each other via a bus 804. The processor 801 performs various operations of the method flow according to an embodiment of the present invention by executing programs in the ROM 802 and / or the storage section 808. It should be noted that the program can also be stored in one or more memories other than the ROM 802 and the storage section 808. The processor 801 can also perform various operations of the method flow according to an embodiment of the present invention by executing programs stored in the one or more memories.

[0192] According to an embodiment of the present invention, the electronic device 800 can further include an input / output (I / O) interface 805, and the input / output (I / O) interface 805 is also connected to the bus 804. The electronic device 800 can further include one or more of the following components connected to the input / output (I / O) interface 805: an input section 806 including a keyboard, a mouse, etc.; an output section 807 including a cathode ray tube (CRT), a liquid crystal display (LCD), etc., and a speaker, etc.; a storage section 808 including a hard disk, etc.; and a communication section 809 including a network interface card such as a LAN card, a modem, etc. The communication section 809 performs communication processing via a network such as the Internet. A drive 810 is also connected to the input / output (I / O) interface 805 as needed. A removable medium 811, such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, etc., is installed on the drive 810 as needed so that a computer program read from it can be installed into the storage section 808 as needed.

[0193] According to an embodiment of the present invention, the method flow according to the embodiment of the present invention can be implemented as a computer software program. For example, an embodiment of the present invention includes a computer program product, which includes a computer program carried on a computer-readable storage medium, and the computer program includes program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from the network through the communication part 809, and / or installed from the removable medium 811. When the computer program is executed by the processor 801, the above functions defined in the system of the embodiment of the present invention are executed. According to an embodiment of the present invention, the above-described systems, devices, apparatuses, modules, units, etc. can be implemented by computer program modules.

[0194] The present invention also provides a computer-readable storage medium, which can be included in the device / device / system described in the above embodiment; or can exist alone without being assembled into the device / device / system. The above computer-readable storage medium carries one or more programs, and when the above one or more programs are executed, the method according to the embodiment of the present invention is implemented.

[0195] According to an embodiment of the present invention, the computer-readable storage medium can be a non-volatile computer-readable storage medium. For example, it can include but is not limited to: portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the above. In the present invention, the computer-readable storage medium can be any tangible medium that contains or stores a program, and the program can be used by or in combination with an instruction execution system, device, or device.

[0196] For example, according to an embodiment of the present invention, the computer-readable storage medium can include the above-described ROM 802 and / or the storage part 808 and / or one or more memories other than the ROM 802 and the storage part 808.

[0197] An embodiment of the present invention also includes a computer program product, which includes a computer program, and the computer program includes program code for executing the method provided by the embodiment of the present invention. When the computer program product runs on an electronic device, the program code is used to cause the electronic device to implement the method provided by the embodiment of the present invention.

[0198] When the computer program is executed by the processor 801, the above functions defined in the system / apparatus of the embodiment of the present invention are executed. According to an embodiment of the present invention, the above-described systems, apparatuses, modules, units, etc. can be implemented by computer program modules.

[0199] In one embodiment, the computer program may rely on tangible storage media such as optical storage devices and magnetic storage devices. In another embodiment, the computer program may also be transmitted and distributed in the form of signals on a network medium, and downloaded and installed through the communication part 809, and / or installed from the removable medium 811. The program code included in the computer program can be transmitted using any suitable network medium, including but not limited to: wireless, wired, etc., or any suitable combination of the above.

[0200] According to an embodiment of the present invention, the program code for executing the computer program provided by the embodiments of the present invention can be written in any combination of one or more programming languages. Specifically, these computing programs can be implemented using high-level procedures and / or object-oriented programming languages, and / or assembly / machine languages. Programming languages include but are not limited to, such as Java, C++, Python, the "C" language, or similar programming languages. The program code can be executed entirely on the user's computing device, partially on the user's device, partially on a remote computing device, or entirely on a remote computing device or server. In the case of a remote computing device, the remote computing device can be connected to the user's computing device through any type of network, including a local area network (LAN) or a wide area network (WAN), or it can be connected to an external computing device (for example, by using an Internet service provider to connect through the Internet).

[0201] The flowcharts and block diagrams in the accompanying drawings illustrate the possible architectures, functions, and operations of systems, methods, and computer program products according to various embodiments of the present invention. In this regard, each block in the flowchart or block diagram may represent a module, a program segment, or a part of code, and the above-mentioned module, program segment, or part of code contains one or more executable instructions for implementing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the blocks may occur in a different order than marked in the accompanying drawings. For example, two consecutive blocks shown may actually be executed substantially in parallel, and they may sometimes be executed in the reverse order, depending on the functions involved. It should also be noted that each block in the block diagram or flowchart, and the combination of blocks in the block diagram or flowchart, can be implemented by a dedicated hardware-based system for performing the specified functions or operations, or can be implemented by a combination of dedicated hardware and computer instructions. Those skilled in the art can understand that the features described in the various embodiments of the present invention can be combined and / or combined in various ways, even if such combinations or combinations are not explicitly described in the present invention. In particular, without departing from the spirit and teachings of the present invention, the features described in the various embodiments of the present invention can be combined and / or combined in various ways. All such combinations and / or combinations fall within the scope of the present invention.

[0202] The embodiments of the present invention have been described above. However, these embodiments are for illustrative purposes only and are not intended to limit the scope of the present invention. Although the embodiments have been described separately above, this does not mean that the measures in each embodiment cannot be used advantageously in combination. Without departing from the scope of the present invention, those skilled in the art can make various substitutions and modifications, and all such substitutions and modifications should fall within the scope of the present invention.

Claims

1. A forward scatter correction method for spaceborne photon counting laser ranging, characterized in that: The method comprises: Obtaining payload parameters of a spaceborne laser radar system and atmospheric optical and physical parameters under different conditions, wherein the atmospheric optical and physical parameters under different conditions include atmospheric optical and physical parameters under cloud conditions and atmospheric optical and physical parameters under aerosol conditions; generating an initial parameter set according to the load parameters and the atmospheric optical physical parameters under the different conditions; According to the initial parameter set, using the Monte Carlo method to simulate a first change characteristic of the photon path under cloud conditions compared to the photon path under clear sky conditions, and to simulate a second change characteristic of the photon path under aerosol conditions compared to the photon path under clear sky conditions; fusing the first variation feature and the second variation feature to obtain forward scatter correction data; In response to receiving the ranging task, according to the current atmospheric optical and physical parameters, the forward scattering correction value corresponding to the current atmospheric optical and physical parameters is searched in the forward scattering correction data to correct the ranging error.

2. The method according to claim 1, characterized in that Before simulating the first change characteristic of the photon path under cloud conditions compared to the photon path under clear sky conditions using the Monte Carlo method according to the initial parameter set, and simulating the second change characteristic of the photon path under aerosol conditions compared to the photon path under clear sky conditions, the method further includes: Determining a first initial photon number according to a standard deviation of a photon scattering path and a target error, wherein the first initial photon number is used to characterize a correction accuracy; Determine a second initial photon number according to the total computing resource consumption required for a given photon and an average computing cost constant required for a single photon, wherein the second initial photon number is used to characterize the correction cost; A target initial photon number is determined according to the first initial photon number and the second initial photon number.

3. The method according to claim 2, characterized in that The method of simulating the first change characteristics of the photon path under cloudy conditions compared with the photon path under clear sky conditions using the Monte Carlo method according to the initial parameter set includes: According to the initial parameter set and the target initial photon number, a first initial photon position that obeys a uniform distribution is randomly generated using a Monte Carlo method, wherein the atmospheric optical physical parameters under cloud conditions in the initial parameter set are set to a non-uniform distribution state; Calculating a first free path of the photon in the cloud medium according to the first initial photon position; According to the first free path, the photon position is updated to obtain a first path change characteristic of the photon in the cloud medium; According to the first path change characteristic, a first photon counting lidar forward scattering correction amount is calculated, wherein the first photon counting lidar forward scattering correction amount represents a first change characteristic of the photon path under cloudy conditions compared to that under clear sky conditions.

4. The method according to claim 2, characterized in that: According to the initial parameter set, the second change characteristics of the photon path under aerosol conditions compared with the photon path under clear sky conditions are simulated using the Monte Carlo method, including: According to the initial parameter set and the target initial photon number, a second initial photon position that obeys a uniform distribution is randomly generated using a Monte Carlo method, wherein the atmospheric optical physical parameters under aerosol conditions in the initial parameter set are set to a non-uniform distribution state; Calculating a second free path of the photon in the aerosol medium according to the second initial photon position; According to the second free path, updating the photon position, and obtaining the second path change characteristics of the photon in the aerosol medium; According to the second path change characteristic, a second photon counting lidar forward scattering correction amount is calculated, wherein the second photon counting lidar forward scattering correction amount characterizes the second change characteristic of the photon path under aerosol conditions compared to the photon path under clear sky conditions.

5. The method according to claim 1, characterized in that: The atmospheric optical physical parameters under the cloud conditions include: Optical thickness of clouds, effective radius of cloud particles, asymmetry factor of cloud particles, cloud thickness and cloud base height.

6. The method according to claim 5, characterized in that The atmospheric optical physical parameters under the aerosol conditions include: Optical thickness of aerosol, effective radius of aerosol particles, asymmetry factor of aerosol particles, thickness of aerosol layer and height of bottom of aerosol layer.

7. The method according to claim 6, characterized in that The fusing the first change feature and the second change feature to obtain forward scatter correction data includes: generating a first 5-dimensional lookup table with non-uniform distribution according to the first change characteristic; generating a second 5-dimensional lookup table with non-uniform distribution according to the second variation characteristic; The first 5-dimensional lookup table and the second 5-dimensional lookup table are merged to obtain a target 5-dimensional lookup table, wherein the target 5-dimensional lookup table represents forward scatter correction data generated based on 5 dimensions.

8. The method according to claim 7, characterized in that The method further comprises: In response to not completely finding the forward scatter correction value corresponding to the current atmospheric optical physical parameter in the forward scatter correction data, calculating the forward scatter correction intermediate value corresponding to the current atmospheric optical physical parameter by using a multidimensional interpolation algorithm; The ranging error is corrected according to the forward scatter correction intermediate value.

9. The method according to claim 7, characterized in that: The method further comprises: In response to the range of the current atmospheric optical and physical parameters exceeding the range of the forward scattering correction data, using a boundary extrapolation mechanism to extrapolate a forward scattering correction extrapolated value corresponding to the current atmospheric optical and physical parameters; Or use the neighbor value substitution mechanism to query the forward scatter correction substitution value corresponding to the current atmospheric optical physical parameters; The ranging error is corrected according to the forward scatter correction estimated value or the forward scatter correction substitute value.

10. A satellite-borne photon counting laser ranging forward scattering correction device, characterized in that: The device comprises: An acquisition module, used to acquire the payload parameters of the spaceborne laser radar system and the atmospheric optical and physical parameters under different conditions, wherein the atmospheric optical and physical parameters under different conditions include the atmospheric optical and physical parameters under cloud conditions and the atmospheric optical and physical parameters under aerosol conditions; A generating module, used for generating an initial parameter set according to the load parameters and the atmospheric optical physical parameters under the different conditions; A simulation module, configured to simulate, based on the initial parameter set, a first change characteristic of a photon path under a cloud condition compared to a photon path under a clear sky condition, and a second change characteristic of a photon path under an aerosol condition compared to a photon path under a clear sky condition by using a Monte Carlo method; A fusion module, used for fusing the first change feature and the second change feature to obtain forward scatter correction data; The correction module is used to respond to receiving the ranging task and query the forward scattering correction value corresponding to the current atmospheric optical and physical parameters in the forward scattering correction data according to the current atmospheric optical and physical parameters to correct the ranging error.

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