Spaceborne array lidar three-dimensional terrain mapping data comprehensive simulation method and system

Abstract

The application provides a spaceborne array laser radar three-dimensional terrain mapping data comprehensive simulation method and system, and the method comprises the steps of: establishing a spaceborne array laser radar three-dimensional terrain mapping simulation link; constructing a spaceborne array laser radar comprehensive simulation model to generate a spaceborne array laser radar three-dimensional terrain simulation dataset; and adopting noise rate, average signal photon number, detection probability, signal-to-noise ratio and elevation accuracy as multiple evaluation indexes to evaluate the quality of the spaceborne array laser radar three-dimensional terrain mapping simulation data under different parameter configurations. The application designs a spaceborne array laser photon cloud data simulation method for the ground laser angle reflection CCR, generates a set of spaceborne array laser radar three-dimensional terrain simulation dataset taking the parameters of a certain type of domestic satellite as an example, adopts multiple evaluation indexes to evaluate the quality of the spaceborne array laser simulation data under different parameter configurations, and provides a solid foundation for the development of array laser three-dimensional terrain mapping satellites.

Description

Technical Field

[0001] This invention relates to the field of active remote sensing technology, and more specifically, to a method and system for comprehensive simulation of three-dimensional terrain mapping data from a spaceborne array lidar. Background Technology

[0002] Since the 1970s, satellite laser altimetry has attracted widespread attention as an active remote sensing technology, and is considered one of the three core technologies in Earth observation in the 21st century, along with imaging spectroscopy and synthetic aperture radar. The main principle of satellite laser altimetry is to mount a laser altimeter on a satellite platform, which emits laser pulse signals to the ground at a certain frequency. By measuring the time difference between the laser pulse signal's emission, reflection from the ground surface, and reception, the precise distance of the laser pulse's one-way transmission is calculated. Combined with precise measurements of the satellite's orbit, attitude, and laser pointing angle, the three-dimensional coordinates and elevation distribution information of the laser footprint on the ground are ultimately obtained.

[0003] The development trend of satellite laser altimetry is gradually evolving from single-beam laser sparse point measurement and multi-beam along-track two-dimensional profile measurement to continuous three-dimensional point cloud measurement over arrayed laser regions. my country's ZY3-02 satellite, launched on May 30, 2016, successfully conducted its first laser altimetry payload and mapping application test. The Gaofen-7 satellite, launched on November 3, 2019, achieved operational use of a two-beam full-waveform laser altimetry system, primarily for acquiring elevation control points for global 1:10,000 scale stereo mapping. The ZY3-03 satellite, launched on July 25, 2020, carries a single-beam threshold detection laser altimetry system, enabling the acquisition of elevation control points for 1:50,000 scale stereo mapping. A terrestrial ecosystem carbon monitoring satellite equipped with a multi-beam lidar was successfully launched on August 4, 2022, capable of measuring sparse points on the Earth's surface using multi-beam lasers along its orbit. The ICESat-2 satellite, launched on September 15, 2018, is the world's first laser altimeter satellite to use photon counting technology. Its Advanced Terrain Laser Altimeter System (ATLAS) can perform dense terrain profile measurements along the orbit with six beams, providing an important foundation for the future development of dense three-dimensional laser terrain mapping satellites.

[0004] However, there are currently no lidar satellites internationally capable of directly obtaining three-dimensional terrain data. Although optical stereo photogrammetry and radar interferometry can also be used for three-dimensional terrain mapping, they suffer from drawbacks such as long data processing links, multi-view image occlusion, radar signal obscuring due to high mountains, and inability to measure understory and underwater terrain. Summary of the Invention

[0005] In view of this, the purpose of this invention is to address the shortcomings of existing optical and radar satellites in effectively meeting the needs of polar glacier mapping, forest and understory topography mapping, high mountain mapping, and coastal zone mapping. This invention designs a comprehensive simulation method and system for spaceborne array lidar three-dimensional topographic mapping data, establishes a spaceborne single-photon array laser altimetry simulation link, constructs a comprehensive spaceborne laser simulation model including an array laser geometric positioning model, a radiation transfer model, and a single-photon detection model, and designs a spaceborne array laser photon cloud data simulation method for ground laser angular reflection (CCR). Taking the parameters of a certain type of domestic satellite as an example, a set of spaceborne array laser simulation datasets is generated. Multiple evaluation indicators are used to assess the quality of spaceborne array laser simulation data under different parameter configurations, providing a solid foundation for the development of array laser three-dimensional topographic mapping satellites.

[0006] This invention provides a comprehensive simulation method for three-dimensional terrain mapping data from a spaceborne array lidar, comprising the following steps:

[0007] S1. Establish a three-dimensional terrain mapping simulation link for spaceborne array lidar;

[0008] S2. Construct a comprehensive simulation model for three-dimensional terrain mapping using a spaceborne array lidar, and generate a three-dimensional terrain simulation dataset for the spaceborne array lidar.

[0009] S3. Multiple evaluation indicators, including noise rate, average signal photon number, detection probability, signal-to-noise ratio, and elevation accuracy, are used to evaluate the quality of spaceborne array laser simulation data under different parameter configurations.

[0010] The method for constructing the spaceborne laser integrated simulation model in step S2 includes the following steps:

[0011] S21. Construct a precise geometric positioning model for the array laser, including:

[0012] Perform the relevant coordinate system definition and transformation;

[0013] Based on the defined and transformed coordinate system, a rigorous geometric positioning model for the spaceborne array laser altimeter is established.

[0014] Specifically, before satellite launch, it is necessary to conduct application requirements analysis, technical specification design, product design, and key technology research. Simulation analysis is an important way to support related work. Conducting comprehensive simulation of spaceborne laser data for high-precision 3D mapping, studying different footprint sizes, array densities, atmospheric conditions, lighting conditions, and terrain features, analyzing the data characteristics of spaceborne array laser 3D imaging, evaluating measurement accuracy and application feasibility, can provide in-depth guidance for satellite overall design, parameter optimization, and optimal operating mode selection.

[0015] As an active imaging altimeter, the spaceborne multibeam array laser altimeter with GM-APD focal plane mainly locates the target based on the distance ρ between the target and the satellite.

[0016] Traditional spaceborne laser altimeters calculate the target's three-dimensional coordinates by tracing the propagation path of the emitted laser. However, for spaceborne array laser altimeters, the emitted laser is only used to illuminate the ground surface. Since the coordinates of the target corresponding to each detector pixel need to be calculated, the spaceborne array laser altimeter must trace from the lidar pixel position to the corresponding ground target position to achieve target localization.

[0017] S22. Construct an array laser radiation transmission model;

[0018] S23. Construct a single-photon detector response model.

[0019] Furthermore, the method for defining and transforming the relevant coordinate system in step S21 includes the following steps:

[0020] S211. Establish the coordinate system of the array lidar (O L -X L Y L Z L ); with the center of the lens of the lidar imaging system as the origin O. L The Z-axis is perpendicular to the detector's focal plane and points towards the nadir. The X-axis and Y-axis are parallel to the edge of the focal plane array and form a right-handed system with the Z-axis.

[0021] In a lidar system, the detector array, lenses, and pixels are rigidly connected, so the relative positions of the detector array and lenses, as well as the pixel spacing, can be considered constant. Let the distance between the optical center of the laser detector and the focal plane be... The coordinates of the array center in the lidar coordinate system are represented as (0, 0, -). Suppose the detector array has n rows and m columns, where m and n are even numbers, and the pixel size is... Taking the first pixel in the upper right corner of the detector array as the first row and first column pixel, the coordinates of the r-th row and c-th column pixel in the array lidar coordinate system are expressed as follows:

[0022] ;

[0023] Equation (1) is obtained by calculating the coordinates of the r-th row and c-th column pixel in the array lidar coordinate system:

[0024] (1)

[0025] 3D coordinates of the corresponding laser footprint points on the ground In the lidar coordinate system, it is represented by equation (2):

[0026] (2)

[0027] In equations (1) and (2), To obtain the distance from the pixel position to the target for the lidar system; To point the projection on X L O L Y L plane and X L The angle between the positive axes; For pointing to Z L The angle between the positive axes;

[0028] S212, Establish the satellite body coordinate system (O B -X B Y B Z B The satellite's coordinate system is defined as follows: the satellite's center of mass is the origin O. B The X-axis points in the direction of flight, the Z-axis points to the nadir, and the direction of the Y-axis is determined by the right-hand rule.

[0029] The coordinate system of the array lidar is not strictly parallel to the coordinate system of the satellite body; there is an installation angle between the array lidar and the satellite body. Therefore, it is necessary to transform the position of the ground point in the array lidar coordinate system to the satellite body coordinate system through coordinate translation and rotation transformations.

[0030] (3)

[0031] In equation (3), These are the coordinates of a ground point in the satellite's coordinate system. This is the rotation matrix for transforming the array lidar to the satellite body coordinate system. It is the offset between the center of the array lidar lens and the origin of the satellite's coordinate system;

[0032] S213. Establish the orbital coordinate system (O O -X O Y O Z O The origin of the orbital coordinate system (which is a transitional coordinate system connecting the satellite's on-board coordinates and pixel coordinates) is the satellite's center of mass. The X-axis points in the direction of the satellite's flight, the Z-axis points in the Earth's center, and the Y-axis is perpendicular to the XOZ plane and forms a right-handed coordinate system with the X-axis and Z-axis.

[0033] Since the coordinate centers of the satellite's body coordinate system and the orbital coordinate system are the same, only a three-axis rotation is needed to complete the coordinate transformation from the satellite's body coordinate system to the orbital coordinate system.

[0034] (4)

[0035] In equation (4), These are the coordinates of the ground point in the orbital coordinate system; This is the rotation matrix for transforming the satellite's body coordinate system to its orbital coordinate system. The three attitude angles of the satellite determined by the star sensor: roll angle Pitch angle Yaw angle composition:

[0036] (5)

[0037] S214. Establish a fixed inertial reference frame in space (The International Celestial Reference Frame, ICR); with the Earth's center of mass as the origin, the X-axis pointing to the vernal equinox, the Z-axis pointing to the celestial north pole, and the Y-axis perpendicular to the XOZ plane, forming a right-handed system with the X-axis and Z-axis. The J2000 coordinate system is usually used.

[0038] Transform the orbital coordinate system to the ICRF coordinate system using coordinate translation and rotation:

[0039] (6)

[0040] In equation (6), To determine the offset of the origin of the orbital coordinate system from the origin of the ICRF coordinate system, and to solve for the rotation matrix from the orbital coordinate system to the ICRF coordinate system, we need to know the satellite's position vector in the ICRF coordinate system at time t. and velocity vector The expression for calculating the rotation matrix between the orbital coordinate system and the ICRF coordinate system is:

[0041] (7)

[0042] In equation (7), ,

[0043] S215. Establish the fixed Earth reference frame (The International Terrestrial Reference Frame, ITRF); with the Earth's center of mass as the origin, the X-axis points to the intersection of the Greenwich Meridian and the Earth's equator, the Z-axis points to the Earth's North Pole, and the Y-axis is perpendicular to the XOZ plane and forms a right-handed system with the X-axis and Z-axis. The WGS84 reference is usually adopted.

[0044] The origin of both the ICRF and ITRF coordinate systems is the Earth's center of mass. The ICRF coordinate system is established by multiplying by a rotation matrix. Transform to ITRF coordinate system:

[0045] (8)

[0046] In equation (8), These are coordinates on a fixed Earth-based reference frame. The formula for calculation is:

[0047] ;

[0048] in, These are the polar motion matrix, the Earth's rotation matrix, and the precession and nutation matrices, respectively.

[0049] Furthermore, the method for establishing the spaceborne single-photon array laser altimetry simulation link in step S1 includes the following steps:

[0050] S11. Calculate the object-space three-dimensional coordinates corresponding to the array laser detection pixels;

[0051] S12, Simulated signal and noise photon radiation response, including: constructing a Delaunay triangulation using point cloud data from airborne radar, obtaining surface reflectivity information for the corresponding wavelength of laser based on the intensity of the point cloud, simulating the surface echo waveform [see equations (14), (27)] and noise waveform [see equation (29)] using echo simulation model and noise simulation model respectively, and combining the surface echo waveform and the noise waveform to obtain a comprehensive target echo containing signal and noise;

[0052] S13, Analog array laser detector response, including:

[0053] S131. The target echo is synthesized by convolution of the impulse response function to obtain the echo received by the array laser altimetry system [see equation (32)].

[0054] S132. The Monte Carlo method is used to simulate the detector's detection process. Let there be a total of p. n=m*n For each pixel, the probability of each detection time slot is calculated according to the single-photon detector detection model [see Equation (37)]. The probability value is compared with a random number that follows a uniform distribution U(0,1). When the probability value is greater than the random number, the time tag of the corresponding time slot is obtained; when the probability value is less than or equal to the random number, the corresponding time slot is eliminated. A group of photons with time tags is obtained. Photons in the dead zone are eliminated to obtain the photon point cloud detected by a single pixel.

[0055] S133. Repeat steps S311-S312 to simulate all photon events detected by all pixels and complete the simulation of all pixels.

[0056] Furthermore, the expression for the rigorous geometric positioning model in the rigorous geometric positioning model of the spaceborne array laser altimeter in step S21 is:

[0057] (9)

[0058] In equation (9), These are the coordinates of the pixel position in ITRF. It is the position of the phase center of the GPS antenna of the GPS positioning system.

[0059] Furthermore, the method for constructing the array laser radiation transfer model in step S22 includes the following steps:

[0060] S221. Calculate the signal radiation scattered by the Lambert body, which includes solar radiation and laser. During transmission, the laser first comes into contact with the atmosphere in the environment and interacts with atmospheric molecules and particles, resulting in radiation attenuation and laser beam deflection. According to the different effects of the atmosphere on radiation, the laser beam deflection is caused by atmospheric refraction, and the attenuation of radiation caused by absorption and scattering of molecules and aerosol particles in the atmosphere is described by Lambert's law through atmospheric transmittance, as shown in equation (10). The nonlinear effect of atmospheric turbulence brings about random drift, diffusion and intensity fluctuation of the light spot, resulting in changes in the spatial distribution of laser beam energy, described by the Gamma distribution model, as shown in equation (11).

[0061] (10)

[0062] In equation (10), The irradiance at the time of launch. Let z be the irradiance returned at a distance z. Atmospheric extinction coefficient;

[0063] (11)

[0064] In equation (11), For gamma function, It is the reciprocal of the Rytov variance;

[0065] By acquiring atmospheric information, surface reflectivity, and geometric information at the calculated pixel array coordinates, and considering the effects of the atmosphere, the number of photons that a single pixel can receive after environmental response is calculated.

[0066] (12)

[0067] When the measured ground object is a linear single target, the total number of echo photons of the entire ground object is expressed by the lidar equation (13):

[0068] (13)

[0069] In formula (13) Fixed parameters for hardware. To emit laser single pulse energy, Let hv be the effective area of ​​the receiving system, and hv be the energy of a single photon, which can be calculated using Planck's energy formula. Where h is Planck's constant, v is the laser frequency, and c is the speed of light. λ is the laser wavelength. R is the distance between the lidar and the target. T is the Lambert reflectance. a For unidirectional atmospheric transmittance, The zenith angle at which the laser is emitted. This refers to the local surface slope.

[0070] The laser echo signal of a single pixel arriving at the receiving system can be represented by the convolution of the laser emission pulse and the environmental response function within the field of view of a single pixel:

[0071] (14)

[0072] In equation (14), Σ represents the area occupied by a pixel. This provides reflectivity information for a specific point on the ground. For time delay, Expressed using equation (15):

[0073] (15)

[0074] In equation (15), is the surface elevation at (x, y), and c is the speed of light; the second term is the time delay caused by the curvature of the laser beam's phase leading edge, which can be ignored for spaceborne lidar.

[0075] Spatial distribution E(x,y) and temporal distribution of the laser beam Represented as:

[0076] (16)

[0077] In equation (16), R is the distance between the lidar and the target, and θ T Where is the beam divergence angle, and E is the energy of the emitted laser single pulse. The root mean square pulse width for laser emission;

[0078] S222. Establish a background noise model and estimate the noise rate of solar background radiation scattering through the atmosphere and reflecting off the Earth's surface into the altimeter:

[0079] (29)

[0080] In equation (29), It refers to wavelength-dependent spectral irradiance measured outside the planetary atmosphere. This refers to the bandwidth of the spectral filter. It is the receiver's field of view within solid radians (solid angle units). It is half the receiver's field of view. , These are the zenith angle of the sun at the time of measurement and the zenith angle at which the laser was emitted; For surface reflectance, It is the angle between the sun and the normal to the Earth's surface. Represented as:

[0081] (30)

[0082] In equation (30), For local surface slope, This is the solar azimuth angle.

[0083] Furthermore, for the simulation of echo signals from ground-based laser angular reflections used in laser altimetry satellite calibration or accuracy verification, this invention also designs a satellite-borne array laser photon cloud data simulation method for ground-based laser angular reflection CCRs. This satellite-borne array laser photon cloud data simulation method for ground-based laser angular reflection CCRs includes:

[0084] Calculate the signal radiation scattered by the corner reflector, including:

[0085] Considering the form of the laser Gaussian beam distribution, the CCR echo photon can be represented as:

[0086] (17)

[0087] In equation (17), Let be the scattering cross-section of the corner reflector. Represented as:

[0088] (18)

[0089] In equation (18),

[0090] To normalize the light intensity distribution, Let θ be a first-order Bessel function, and θ be the diffraction angle. The radius of the CCR aperture. This represents the peak cross-sectional area of ​​the far-field light intensity. Represented as:

[0091] (19)

[0092] In equation (19), The reflectance of the coated CCR is 0.78, and D=2r is the diameter of the CCR aperture.

[0093] Considering the dihedral angle error, the far-field normalized optical amplitude of the CCR is obtained according to Fraunhofer diffraction theory:

[0094] (20)

[0095] In equation (20), Let CCR be the radius; Let n be the normalized polarization complex amplitude of the nth part, for the coated CCR. ; For wave number equal to , The wavelength of the laser; , ; Let be the angle between the outgoing beam and the incident beam. If the errors of the three dihedral angles of the CCR are equal, then... hour, The refractive index of n is 1.46; and These are the polar coordinates in the CCR coordinate system and the polar coordinates of the far-field diffraction point P, respectively. θ is the diffraction angle. Let P be the azimuth angle of the diffraction point P;

[0096] Simplifying equation (20) yields the analytical solution for the normalized amplitude of the CCR far field:

[0097] (twenty one)

[0098] In equation (21), For a first-order Bessel function, the remaining parameters in equation (21) are expressed as:

[0099]

[0100] Based on the relationship between amplitude and light intensity, the far-field light intensity distribution reflected by the CCR can be obtained as follows:

[0101] (twenty two)

[0102] The average normalized intensity on the diffraction angle θ ring is:

[0103] (twenty three)

[0104] Because the satellite platform operates at high speed in space, when the CCR echo beam is reflected back to the location where the laser pulse was emitted, the satellite's position deviates from the beam's direction by an angle, known as the velocity difference angle. According to astrophysical knowledge, the formula for calculating this velocity difference angle is:

[0105] (twenty four)

[0106] In equation (24), Re is the Earth's radius (6370km), g is the gravitational acceleration, H is the satellite's orbital altitude, and z is the zenith angle;

[0107] When the spaceborne laser altimeter uses nadir measurement, the velocity difference angle is approximately:

[0108] (25)

[0109] The orbital altitude of the spaceborne single-photon laser altimeter platform is approximately 500 kilometers, corresponding to a velocity difference angle of approximately... ;

[0110] The satellite is located at (x s ,y s The number of photons that can be received at point () is:

[0111] (26)

[0112] In equation (26), x c With y c CCR coordinates;

[0113] For spaceborne lidar, considering that the emitted laser pulse is Gaussian and the detected target is a linear single target, the received signal according to diffraction theory simplifies equation (26) to:

[0114] (27)

[0115] In equation (27), The average number of photons received for both land cover types They are represented by equations (13) and (26) respectively; The root mean square pulse width of the received signal. Expressed using equation (28):

[0116] (28)

[0117] In equation (28), This is expressed as the root mean square pulse width of the emitted pulse. For surface roughness, and Let θ be the slope of the Earth's surface along the rail direction and perpendicular to the rail direction, respectively; c be the speed of light; and θ be the slope of the Earth's surface along the rail direction and perpendicular to the rail direction, respectively. TThis is the laser divergence angle.

[0118] Furthermore, the method for constructing the single-photon detector response model in step S23 includes:

[0119] After the pulse waveform S(t) reaches the altimeter, it is collected and recorded. The impulse response function (IRF) of the altimeter is:

[0120] (31)

[0121] In equation (31), IRF is the impulse response function, k = ceil (Total time / Step) al k is the number of statistical boxes along the track. The function is for rounding up; IRF calculations are divided into photon number statistics along two directions: orbit and elevation. The step size for each track-based statistical frame; Totaltime is the total track-based statistical time.

[0122] After determining the range of each statistical frame along the track, perform histogram elevation statistics on the photon point cloud within that range according to elevation, with a step size of StepH. For the first The backscattered signal value of each elevation statistical box, the box containing the peak backscattered signal is set to the elevation position of the ground surface by default and set to p;

[0123] It is the range of the impulse response function, in which and The elevation values ​​are determined by customizing the required Surfu (above ground), Surfd (below ground), and the elevation statistics step size StepH. Since the number of photons above the ground is generally small, it is difficult to accurately calculate the backscattered signal value above the ground. Therefore, the Surfu value should not be too large; preferably, it is 0.15m. The Surfd value is based on the altimeter's maximum depth measurement distance (e.g., the ICESat-2's maximum depth measurement distance is approximately 30m, so Surfd can be set to 30m). j represents the total number of elevation statistics frames, which is n+m+1.

[0124] Combined with the receiving efficiency of the receiving system The photoelectric conversion quantum efficiency of the detector After calculating the impulse response function, the laser signal and system background noise are combined and convolved with the impulse response function to obtain the echo received by the altimeter of the entire single-photon laser altimeter system.

[0125] (32)

[0126] In equation (32), Sn S(t) represents the echo received by the entire single-photon laser altimeter system, and S(t) represents the signal echo. This is background noise from the sun. For dark counting noise, the noise is synthesized into ;

[0127] After passing through the filter, the laser light is further transmitted to the single-photon detector, which then... Detected within each time slot The probability of a photon is represented by a Poisson distribution:

[0128] (33)

[0129] The detection of a laser beam after passing through atmospheric turbulence involves two stochastic processes: atmospheric turbulence and Poisson detection by the detector. The stochastic process of atmospheric turbulence affecting photons influences the parameter N in the Poisson stochastic process of photon detection by the detector. Using Mandel's equation, the probability density of laser detection after passing through atmospheric turbulence is:

[0130] (34)

[0131] The probability that no photon detection occurs within a single time slot is:

[0132] (35)

[0133] If the detection of a photon within a single time slot is complementary to the absence of a photon detection event within a single time slot, then the probability of detecting a photon event within a single time slot is:

[0134] (36)

[0135] Most single-photon detectors pause for a period of time after responding to the first incident photon before responding to subsequent incident photons; this is known as a dead time. This reduces the probability of a single-photon detector detecting a returning photon to some extent. If the effect of the dead time is taken into account, the detection probability of a single-photon detector in the i-th time slot is the probability that no photon is detected during the dead time and the probability that the photon is detected in the i-th time slot without considering the dead time:

[0136] (37).

[0137] Furthermore, the method for evaluating the quality of spaceborne array laser simulation data under different parameter configurations includes:

[0138] S31. Calculate the photon point cloud noise rate, whereby the point cloud noise rate is defined as the number of noise photon events recorded by a single pixel of the array laser altimeter per unit time:

[0139] (38)

[0140] In equation (38), The noise rate defined in this paper, This represents the number of noise records made in 50 detections for a single pixel. For window height, The noise is the total number of photons within 50 beams minus the signal identified by the built-in filtering algorithm, where c is the speed of light.

[0141] Taking ICESat-2 (Natural Resources Satellite Remote Sensing) as an example, the laser emission frequency is 10KHz. If we consider the satellite's flight speed of 7km / s, 50 beams correspond to a satellite flight distance of approximately 35m. Since the footprint diameter of ICESat-2 is 17.5m, a distance of 35m is equivalent to the size of two footprints.

[0142] S32. Calculate the average signal photon count, which is defined as the average number of signal photon events recorded per pixel in a single detection:

[0143] (39)

[0144] In equation (39), The average number of signal photons. This represents the total number of signal photons recorded in 50 detections per pixel.

[0145] S33. Calculate the detection probability, which is defined as the probability that a single pixel can detect the target in a single detection:

[0146] (40)

[0147] In equation (39), Indicates the detection probability. This indicates the number of signal photons recorded out of 50 detections;

[0148] S34. Calculate the signal-to-noise ratio (SNR). Define the SNR of altimeter data as the logarithm of the ratio of signal photons to noise within a 1m elevation range:

[0149] (41)

[0150] In equation (41), SNR is the signal-to-noise ratio of the point cloud. The number of noises within the range. .

[0151] Since the echo of the measured height data is very complex and it is difficult to obtain the pulse width of the echo directly, this invention defines the signal-to-noise ratio of the height measurement data.

[0152] Furthermore, the method for calculating the object-side three-dimensional coordinates of the array laser detector pixels in step S11 includes: calculating the two-dimensional coordinates of the laser detector pixels in the array lidar coordinate system and the pixel pointing vector based on the altimeter parameters; calculating the object-side three-dimensional coordinates by combining the satellite attitude and orbit parameters with the ground reference terrain; calculating the atmospheric refraction correction using atmospheric pressure, temperature, and humidity parameters to obtain the actual distance information; calculating the object-side three-dimensional coordinates based on the geometric model of the spaceborne array laser altimeter; and obtaining the object-side three-dimensional coordinates with additional offset by comprehensively considering the tidal correction and the influence of optical aberration.

[0153] This invention also provides a comprehensive simulation system for three-dimensional terrain mapping data from a spaceborne array lidar, used to implement the comprehensive simulation method for three-dimensional terrain mapping data from a spaceborne array lidar as described above, including:

[0154] Spaceborne Single-Photon Array Laser Altimetry Simulation Link Subsystem: Used to establish a spaceborne single-photon array laser altimetry simulation link;

[0155] Integrated simulation model construction subsystem: used to construct a comprehensive simulation model of spaceborne lasers and generate a simulation dataset of spaceborne array lasers;

[0156] The array laser data quality evaluation subsystem is used to evaluate the quality of spaceborne array laser simulation data under different parameter configurations using multiple evaluation indicators such as noise rate, average signal photon count, detection probability, signal-to-noise ratio, and elevation accuracy.

[0157] To facilitate the analysis of the performance of domestically produced altimeters under different terrain conditions, this invention utilizes Python to develop an easy-to-operate program. The main modules of this program include:

[0158] Target 3D Coordinate Calculation Module: This module allows users to plan satellite flight paths and solve for the coordinates of each pixel;

[0159] Background noise calculation module: Calculates the theoretical noise rate of a pixel based on parameters such as the solar altitude angle input by the user;

[0160] Signal echo simulation module: This module supports calculating the theoretically received echo of a pixel based on user-input parameters and terrain data;

[0161] Detection Unit Response Module: This module records photon point cloud data based on and using the Monte Carlo method;

[0162] Simulation data quality evaluation module: This module supports evaluating the quality of simulated point clouds based on different input parameters.

[0163] The present invention also provides a computer device, the computer device including a memory, a processor and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, it implements the steps of the comprehensive simulation method for three-dimensional terrain mapping data of spaceborne array lidar as described above.

[0164] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0165] The method and system for comprehensive simulation of three-dimensional terrain mapping data from spaceborne array lidar provided by this invention establishes a spaceborne single-photon array lidar altimetry simulation link, constructs a comprehensive simulation model of spaceborne lidar including an array lidar geometric positioning model, a radiation transfer model, and a single-photon detection model, and generates a spaceborne array lidar simulation dataset using parameters of a certain type of domestic satellite as an example; and uses multiple evaluation indicators to assess the quality of spaceborne array lidar simulation data under different parameter configurations, providing a solid foundation for the development of array lidar three-dimensional terrain mapping satellites. Attached Figure Description

[0166] Various other advantages and benefits will become apparent to those skilled in the art upon reading the following detailed description of preferred embodiments. The accompanying drawings are for illustrative purposes only and are not intended to limit the invention.

[0167] In the attached diagram:

[0168] Figure 1 This is a flowchart illustrating the simulation of spaceborne single-photon array laser altimetry data according to an embodiment of the present invention.

[0169] Figure 2 This is a schematic diagram illustrating the calculation of three-dimensional coordinates of a spaceborne single-photon array laser target according to an embodiment of the present invention;

[0170] Figure 3 This is a schematic diagram showing the angle between the pixel vectors in the lidar coordinate system according to an embodiment of the present invention;

[0171] Figure 4 This is a schematic diagram of the speed difference angle according to an embodiment of the present invention;

[0172] Figure 5 This is a timing diagram of the single-photon detection system according to an embodiment of the present invention;

[0173] Figure 6 This is a schematic diagram of the h5 format storage format of the simulation dataset in an embodiment of the present invention;

[0174] Figure 7 This is a GUI interface diagram of a program written in Python according to an embodiment of the present invention;

[0175] Figure 8This is a simplified geometric model diagram of an embodiment of the present invention;

[0176] Figure 9 This is a simplified simulation result diagram of an embodiment of the present invention;

[0177] Figure 10 This is a diagram showing the CCR deployment and spaceborne laser simulation data of an embodiment of the present invention;

[0178] Figure 11 This is a design diagram of a mountain airborne point cloud and a satellite flight trajectory according to an embodiment of the present invention;

[0179] Figure 12 This is a simulated point cloud image of a spaceborne array laser system in a mountainous region, according to an embodiment of the present invention.

[0180] Figure 13 This is a design diagram of an urban airborne point cloud and a satellite flight trajectory according to an embodiment of the present invention;

[0181] Figure 14 This is a simulated point cloud diagram of a spaceborne array laser system in an urban area, according to an embodiment of the present invention.

[0182] Figure 15 This is a schematic diagram of the configuration of a computer device according to an embodiment of the present invention. Detailed Implementation

[0183] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numerals in different drawings denote the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this disclosure. Rather, they are merely examples of apparatuses and products consistent with some aspects of this disclosure as detailed in the appended claims.

[0184] The terminology used in this disclosure is for the purpose of describing particular embodiments only and is not intended to be limiting of the disclosure. The singular forms “a,” “the,” and “the” as used in this disclosure and the appended claims are also intended to include the plural forms unless the context clearly indicates otherwise. It should also be understood that the term “and / or” as used herein refers to and includes any and all possible combinations of one or more of the associated listed items.

[0185] It should be understood that although the terms first, second, third, etc., may be used in this disclosure to describe various information, such information should not be limited to these terms. These terms are used only to distinguish information of the same type from one another. For example, without departing from the scope of this disclosure, first information may also be referred to as second information, and similarly, second information may also be referred to as first information. Depending on the context, the word "if" as used herein may be interpreted as "when," "when," or "in response to determination."

[0186] The embodiments of the present invention will be described in further detail below.

[0187] This invention provides a method for comprehensive simulation of three-dimensional terrain mapping data from a spaceborne array lidar, comprising the following steps:

[0188] S1. Establish a three-dimensional terrain mapping simulation link for spaceborne array lidar, including the following steps:

[0189] S11. Calculate the object-side three-dimensional coordinates corresponding to the array laser detector pixels, including: calculating the two-dimensional coordinates of the laser detector pixels in the array lidar coordinate system and the pixel pointing vector based on the altimeter parameters; calculating the object-side three-dimensional coordinates by combining the satellite attitude and orbit parameters with the ground reference terrain; calculating the atmospheric refraction correction using atmospheric pressure, temperature, and humidity parameters to obtain the actual distance information; calculating the object-side three-dimensional coordinates based on the geometric model of the spaceborne array laser altimeter; and obtaining the object-side three-dimensional coordinates with additional offset by comprehensively considering the tidal correction and the influence of optical aberration.

[0190] S12, Simulated signal and noise photon radiation response, including: constructing a Delaunay triangulation using point cloud data from airborne radar, obtaining surface reflectivity information for the corresponding wavelength of laser based on the intensity of the point cloud, simulating the surface echo waveform [see equations (14), (27)] and noise waveform [see equation (29)] using echo simulation model and noise simulation model respectively, and combining the surface echo waveform and the noise waveform to obtain a comprehensive target echo containing signal and noise;

[0191] S13, Analog array laser detector response, including:

[0192] S131. The target echo is synthesized by convolution of the impulse response function to obtain the echo received by the array laser altimetry system [see equation (32)].

[0193] S132. The Monte Carlo method is used to simulate the detector's detection process, assuming a total of For each pixel, the probability of each detection time slot is calculated according to the single-photon detector detection model [see Equation (37)]. The probability value is compared with a random number that follows a uniform distribution U(0,1). When the probability value is greater than the random number, the time tag of the corresponding time slot is obtained; when the probability value is less than or equal to the random number, the corresponding time slot is eliminated. A group of photons with time tags is obtained. Photons in the dead zone are eliminated to obtain the photon point cloud detected by a single pixel.

[0194] S133. Repeat steps S311-S312 to simulate all photon events detected by all pixels and complete the simulation of all pixels.

[0195] S2. Construct a comprehensive simulation model for three-dimensional terrain mapping using a spaceborne array lidar, and generate a three-dimensional terrain simulation dataset for the spaceborne array lidar.

[0196] The method for constructing a comprehensive simulation model of spaceborne lasers includes the following steps:

[0197] S21. Construct a precise geometric positioning model for the array laser, including: defining and transforming the relevant coordinate system, including the following steps:

[0198] S211. Establish the coordinate system of the array lidar (O L -X L Y L Z L ); with the center of the lens of the lidar imaging system as the origin O. L The Z-axis is perpendicular to the detector's focal plane and points towards the nadir. The X-axis and Y-axis are parallel to the edge of the focal plane array and form a right-handed system with the Z-axis.

[0199] Let the distance between the optical center of the laser detector and the focal plane be... The coordinates of the array center in the lidar coordinate system are represented as (0, 0, -). Suppose the detector array has n rows and m columns, where m and n are even numbers, and the pixel size is... Taking the first pixel in the upper right corner of the detector array as the first row and first column pixel, the coordinates of the r-th row and c-th column pixel in the array lidar coordinate system are expressed as follows:

[0200] , ;

[0201] Equation (1) is obtained by calculating the coordinates of the r-th row and c-th column pixel in the array lidar coordinate system:

[0202] (1)

[0203] The angle between the pointing vector of a pixel and the corresponding ground point in lidar coordinates is as follows: Figure 3 As shown;

[0204] The three-dimensional coordinates (XYZ)TL of the corresponding ground laser footprint point are expressed in the lidar coordinate system as Equation (2):

[0205] (2)

[0206] In equations (1) and (2), To obtain the distance from the pixel position to the target for the lidar system; To point the projection on X L O L Y L plane and X L The angle between the positive axes; For pointing to Z L The angle between the positive axes;

[0207] S212, Establish the satellite body coordinate system (O B -X B Y B Z B The satellite's coordinate system is defined as follows: the satellite's center of mass is the origin O. B The X-axis points in the direction of flight, the Z-axis points to the nadir, and the direction of the Y-axis is determined by the right-hand rule.

[0208] By performing coordinate translation and rotation transformations, the positions of ground points in the array lidar coordinate system are transformed to the satellite body coordinate system:

[0209] (3)

[0210] In equation (3), These are the coordinates of a ground point in the satellite's coordinate system. This is the rotation matrix for transforming the array lidar to the satellite body coordinate system. It is the offset between the center of the array lidar lens and the origin of the satellite's coordinate system;

[0211] S213. Establish the orbital coordinate system (O O -X O Y O Z O The origin of the orbital coordinate system is the satellite's center of mass, the X-axis points in the direction of the satellite's flight, the Z-axis points in the Earth's center, and the Y-axis is perpendicular to the XOZ plane and forms a right-handed system with the X-axis and Z-axis.

[0212] Since the coordinate centers of the satellite's body coordinate system and the orbital coordinate system are the same, only a three-axis rotation is needed to complete the coordinate transformation from the satellite's body coordinate system to the orbital coordinate system.

[0213] (4)

[0214] In equation (4), These are the coordinates of the ground point in the orbital coordinate system; This is the rotation matrix for transforming the satellite's body coordinate system to its orbital coordinate system. The three attitude angles of the satellite determined by the star sensor: roll angle Pitch angle Yaw angle composition:

[0215] (5)

[0216] S214. Establish a fixed inertial reference frame in space; with the Earth's center of mass as the origin, the X-axis pointing to the vernal equinox, the Z-axis pointing to the celestial north pole, and the Y-axis perpendicular to the XOZ plane and forming a right-handed system with the X-axis and Z-axis, using the J2000 coordinate system;

[0217] Transform the orbital coordinate system to the ICRF coordinate system using coordinate translation and rotation:

[0218] (6)

[0219] In equation (6), To determine the offset of the origin of the orbital coordinate system from the origin of the ICRF coordinate system, and to solve for the rotation matrix from the orbital coordinate system to the ICRF coordinate system, we need to know the satellite's position vector in the ICRF coordinate system at time t. and velocity vector The expression for calculating the rotation matrix between the orbital coordinate system and the ICRF coordinate system is:

[0220] (7)

[0221] In equation (7),

[0222] S215. Establish a fixed Earth reference system; with the Earth's center of mass as the origin, the X-axis points to the intersection of the Greenwich Meridian and the Earth's equator, the Z-axis points to the Earth's North Pole, and the Y-axis is perpendicular to the XOZ plane and forms a right-handed system with the X-axis and Z-axis, using the WGS84 datum.

[0223] The origin of both the ICRF and ITRF coordinate systems is the Earth's center of mass. The ICRF coordinate system is established by multiplying by a rotation matrix. Transform to ITRF coordinate system:

[0224] (8)

[0225] In equation (8), These are coordinates on a fixed Earth-based reference frame. The formula for calculation is:

[0226] ;

[0227] Where W(t), R(t), and PN(t) are the polar motion matrix, Earth rotation matrix, precession matrix, and nutation matrix, respectively.

[0228] Based on the defined and transformed coordinate system, a rigorous geometric positioning model for the spaceborne array laser altimeter is established. The expression for the rigorous geometric positioning model is as follows:

[0229] (9)

[0230] In equation (9), These are the coordinates of the pixel position in ITRF. It is the position of the phase center of the GPS antenna of the GPS positioning system.

[0231] The rigorous geometric positioning model of the spaceborne array laser altimeter constructed in this embodiment is as follows: Figure 2 As shown;

[0232] S22. Construct an array laser radiation transmission model, including the following steps:

[0233] S221. Calculate the signal radiation scattered by the Lambert body, which includes solar radiation and laser. During transmission, the laser first comes into contact with the atmosphere in the environment and interacts with atmospheric molecules and particles, resulting in radiation attenuation and laser beam deflection. According to the different effects of the atmosphere on radiation, the laser beam deflection is caused by atmospheric refraction, and the attenuation of radiation caused by absorption and scattering of molecules and aerosol particles in the atmosphere is described by Lambert's law through atmospheric transmittance, as shown in equation (10). The nonlinear effect of atmospheric turbulence brings about random drift, diffusion and intensity fluctuation of the light spot, resulting in changes in the spatial distribution of laser beam energy, described by the Gamma distribution model, as shown in equation (11).

[0234] (10)

[0235] In equation (10), The irradiance at the time of launch. Let z be the irradiance returned at a distance z. Atmospheric extinction coefficient;

[0236] (11)

[0237] In equation (11), Let m be the gamma function, and m be the reciprocal of the Rytov variance.

[0238] By acquiring atmospheric information, surface reflectivity, and geometric information at the calculated pixel array coordinates, and considering the effects of the atmosphere, the number of photons that a single pixel can receive after environmental response is calculated.

[0239] (12)

[0240] When the measured ground object is a linear single target, the total number of echo photons of the entire ground object is expressed by the lidar equation (13):

[0241] (13)

[0242] In formula (13) Fixed parameters for hardware. To emit laser single pulse energy, For the effective area of ​​the receiving system, The energy of a single photon can be calculated using Planck's energy formula. , Let be Planck's constant. Where c is the laser frequency and c is the speed of light. λ is the laser wavelength. R is the distance between the lidar and the target. T is the Lambert reflectance. a For unidirectional atmospheric transmittance, θ p The zenith angle at which the laser is emitted. This refers to the local surface slope.

[0243] The laser echo signal of a single pixel arriving at the receiving system can be represented by the convolution of the laser emission pulse and the environmental response function within the field of view of a single pixel:

[0244] (14)

[0245] In equation (14), Σ represents the area occupied by a pixel. This provides reflectivity information for a specific point on the ground. For time delay, Expressed using equation (15):

[0246] (15)

[0247] In equation (15), is the Earth's surface elevation at (x, y), and c is the speed of light;

[0248] Spatial distribution E(x,y) and temporal distribution of the laser beam Represented as:

[0249] (16)

[0250] In equation (16), R is the distance between the lidar and the target, and θ T Where is the beam divergence angle, and E is the energy of the emitted laser single pulse. The root mean square pulse width for laser emission;

[0251] S222. Establish a background noise model and estimate the noise rate of solar background radiation scattering through the atmosphere and reflecting off the Earth's surface into the altimeter:

[0252] (29)

[0253] In equation (29), It refers to wavelength-dependent spectral irradiance measured outside the planetary atmosphere. This refers to the bandwidth of the spectral filter. It is the receiver's field of view within solid radians (solid angle units). It is half the receiver's field of view. , These are the zenith angle of the sun at the time of measurement and the zenith angle at which the laser was emitted; For surface reflectance, It is the angle between the sun and the normal to the Earth's surface. Represented as:

[0254] (30)

[0255] In equation (30), For local surface slope, This is the solar azimuth angle.

[0256] The comprehensive simulation method for three-dimensional terrain mapping data of spaceborne array lidar in this embodiment also includes a simulation method for spaceborne array lidar photon cloud data designed for ground-based laser angular reflection (CCR). This simulation method for spaceborne array lidar photon cloud data designed for ground-based laser angular reflection (CCR) includes:

[0257] Calculate the signal radiation scattered by the corner reflector, including:

[0258] Considering the form of the laser Gaussian beam distribution, the CCR echo photon can be represented as:

[0259] (17)

[0260] In equation (17), δ(θ) is the scattering cross-section of the corner reflector, and δ(θ) is expressed as:

[0261] (18)

[0262] In equation (18),

[0263] To normalize the light intensity distribution, Let θ be a first-order Bessel function, θ be the diffraction angle, and r be the CCR aperture radius. This represents the peak cross-sectional area of ​​the far-field light intensity. Represented as:

[0264] (19)

[0265] In equation (19), The reflectance of the coated CCR is 0.78, and D=2r is the diameter of the CCR aperture.

[0266] The far-field normalized optical amplitude of CCR is obtained based on Fraunhofer diffraction theory:

[0267] (20)

[0268] In equation (20), Let CCR be the radius; Let n be the normalized polarization complex amplitude of the nth part, for the coated CCR. ; For wave number equal to , The wavelength of the laser; , θ0 is the angle between the outgoing beam and the incident beam. If the errors of the three dihedral angles of the CCR are equal and equal to β, , The refractive index is 1.46; and These are the polar coordinates in the CCR coordinate system and the polar coordinates of the far-field diffraction point P, respectively. θ is the diffraction angle. Let P be the azimuth angle of the diffraction point P;

[0269] Simplifying equation (20) yields the analytical solution for the normalized amplitude of the CCR far field:

[0270] (twenty one)

[0271] In equation (21), For a first-order Bessel function, the remaining parameters in equation (21) are expressed as:

[0272]

[0273] Based on the relationship between amplitude and light intensity, the far-field light intensity distribution reflected by the CCR can be obtained as follows:

[0274] (twenty two)

[0275] at the diffraction angle The average normalized intensity on the ring is:

[0276] (twenty three)

[0277] Because the satellite platform operates at high speed in space, when the CCR echo beam is reflected back to the location where the laser pulse was emitted, the satellite's position deviates from the beam's direction by an angle, known as the velocity difference angle. Figure 4 As shown, according to astrophysical knowledge, the formula for calculating the velocity difference angle is:

[0278] (twenty four)

[0279] In equation (24), Re is the Earth's radius (6370km), g is the gravitational acceleration, H is the satellite's orbital altitude, and z is the zenith angle;

[0280] When the spaceborne laser altimeter uses nadir measurement, the velocity difference angle is approximately:

[0281] (25)

[0282] The orbital altitude of the spaceborne single-photon laser altimeter platform is approximately 500 kilometers, corresponding to a velocity difference angle of approximately... ;

[0283] The satellite is located at (x s ,y s The number of photons that can be received at point () is:

[0284] (26)

[0285] In equation (26), x c With y c CCR coordinates;

[0286] For spaceborne lidar, considering that the emitted laser pulse is Gaussian and the detected target is a linear single target, the received signal according to diffraction theory simplifies equation (26) to:

[0287] (27)

[0288] In equation (27), Ns is the average number of photons received, and Ns for the two land cover types is represented by equation (13) and equation (26) respectively; The root mean square pulse width of the received signal. Expressed using equation (28):

[0289] (28)

[0290] In equation (28), This is expressed as the root mean square pulse width of the emitted pulse. For surface roughness, and Let θ be the slope of the Earth's surface along the rail direction and perpendicular to the rail direction, respectively; c be the speed of light; and θ be the slope of the Earth's surface along the rail direction and perpendicular to the rail direction, respectively. T This refers to the laser divergence angle;

[0291] S23. Construct a single-photon detector response model, including:

[0292] The pulse waveform S(t) is collected and recorded after arriving at the altimeter. The pulse response function of the altimeter is:

[0293] (31)

[0294] In equation (31), IRF is the impulse response function, k = ceil (Totaltime / Step) al k is the number of statistical boxes along the track. The function is for rounding up; IRF calculations are divided into photon number statistics along two directions: orbit and elevation. Step al The step size for each track-based statistical frame; Totaltime is the total track-based statistical time.

[0295] After determining the range of each statistical frame along the track, perform a histogram elevation statistical analysis on the photon point cloud within that range according to elevation, with a step size of StepH, β(z) j ) represents the backscattered signal value of the j-th elevation statistical box. The box containing the peak backscattered signal is set to the elevation location of the ground surface by default and is set to p.

[0296] [pn, p+m] is the range of the impulse response function, where... and The elevation values ​​are determined by customizing the required Surfu (above ground), Surfd (below ground), and the step size StepH for elevation statistics. Since the number of photons above the ground is generally small, it's difficult to accurately calculate the backscattered signal value above the ground; therefore, the Surfu value should not be too large, and is set to 0.15m. The Surfd value is based on the altimeter's maximum depth measurement distance; the ICESat-2's maximum depth measurement distance is approximately 30m, so Surfd is set to 30m. The total number of elevation statistics frames is set to n+m+1.

[0297] Combined with the receiving efficiency of the receiving system The photoelectric conversion quantum efficiency of the detector After calculating the impulse response function, the laser signal and system background noise are combined and convolved with the impulse response function to obtain the echo received by the altimeter of the entire single-photon laser altimeter system.

[0298] (32)

[0299] In equation (32), The echo received by the entire single-photon laser altimeter system. For signal echo, This is background noise from the sun. For dark counting noise, the noise is synthesized into ;

[0300] After passing through the filter, the laser light is further transmitted to the single-photon detector. The probability of the single-photon detector detecting k photons in the i-th time slot is represented by a Poisson distribution:

[0301] (33)

[0302] The detection of a laser beam after passing through atmospheric turbulence involves two stochastic processes: atmospheric turbulence and Poisson detection by the detector. The stochastic process of atmospheric turbulence affecting photons influences the parameter N in the Poisson stochastic process of photon detection by the detector. Using Mandel's equation, the probability density of laser detection after passing through atmospheric turbulence is:

[0303] (34)

[0304] The probability that no photon detection occurs within a single time slot is:

[0305] (35)

[0306] If the detection of a photon within a single time slot is complementary to the absence of a photon detection event within a single time slot, then the probability of detecting a photon event within a single time slot is:

[0307] (36)

[0308] Most single-photon detectors pause for a period of time after responding to the first incident photon before responding to subsequent incident photons; this is known as a dead time. This reduces the probability of the single-photon detector detecting the echo photon to some extent. Figure 5 As shown, considering the effect of the dead zone, the detection probability of a single-photon detector in the i-th time slot is the probability that no photon detection occurs during the dead zone duration and the probability that the i-th time slot is detected without considering the dead zone:

[0309] (37).

[0310] S3. Multiple evaluation indicators, including noise rate, average signal photon number, detection probability, signal-to-noise ratio, and elevation accuracy, are used to evaluate the quality of spaceborne array laser simulation data under different parameter configurations.

[0311] Methods for evaluating the quality of spaceborne array laser simulation data under different parameter configurations include:

[0312] S31. Calculate the photon point cloud noise rate, whereby the point cloud noise rate is defined as the number of noise photon events recorded by a single pixel of the array laser altimeter per unit time:

[0313] (38)

[0314] In equation (38), The noise rate defined in this paper, This represents the number of noise records made in 50 detections for a single pixel. For window height, The noise is the total number of photons within 50 beams minus the signal identified by the built-in filtering algorithm, where c is the speed of light.

[0315] S32. Calculate the average signal photon count, which is defined as the average number of signal photon events recorded per pixel in a single detection:

[0316] (39)

[0317] In equation (39), The average number of signal photons. This represents the total number of signal photons recorded in 50 detections per pixel.

[0318] S33. Calculate the detection probability, which is defined as the probability that a single pixel can detect the target in a single detection:

[0319] (40)

[0320] In equation (39), Indicates the detection probability. This indicates the number of signal photons recorded out of 50 detections;

[0321] S34. Calculate the signal-to-noise ratio (SNR). Define the SNR of altimeter data as the logarithm of the ratio of signal photons to noise within a 1m elevation range:

[0322] (41)

[0323] In equation (41), SNR is the signal-to-noise ratio of the point cloud. The number of noises within the range. .

[0324] Figure 1 The simulation process of spaceborne single-photon array laser altimetry data in this embodiment is shown.

[0325] This invention also provides a comprehensive simulation system for three-dimensional terrain mapping data from a spaceborne array lidar, used to implement the comprehensive simulation method for three-dimensional terrain mapping data from a spaceborne array lidar as described above, including:

[0326] Spaceborne Single-Photon Array Laser Altimetry Simulation Link Subsystem: Used to establish a spaceborne single-photon array laser altimetry simulation link;

[0327] Integrated simulation model construction subsystem: used to construct a comprehensive simulation model of spaceborne lasers and generate a simulation dataset of spaceborne array lasers;

[0328] The array laser data quality evaluation subsystem is used to evaluate the quality of spaceborne array laser simulation data under different parameter configurations using multiple evaluation indicators such as noise rate, average signal photon count, detection probability, signal-to-noise ratio, and elevation accuracy.

[0329] This embodiment designs the simulation data file (simulation dataset) specifications based on the data characteristics of array lasers. The output data is in .h5 format and contains three groups: the MetaData group records metadata descriptions, including parameters such as the number of beams, detector array specifications, and simulation time set during the simulation. The heights and quality_assessment groups store the coordinate information and quality evaluation information corresponding to each pixel, respectively. The datasets contained in the heights group are: laser emission time delta_time, height of each point cloud, signal and noise photon label signal_label, and planar position information x, y of each point cloud. The datasets contained in the quality_assessment group are quality evaluation indicators statistically analyzed based on the point cloud data accumulated from 50 detections per pixel, namely: signal-to-noise ratio SNR, background noise rate bckgrd, detection probability prd, and average signal photon count signal_mean, etc. Figure 6 As shown. This embodiment uses Python to write an easy-to-use program, the GUI interface of which is shown below. Figure 7 As shown.

[0330] In an application example of a certain type of satellite to be launched (see Table 1), the present invention conducts a satellite-borne array laser simulation practice.

[0331] Table 1. Parameter settings for a certain type of satellite

[0332]

[0333] Simple shape:

[0334] To facilitate subsequent point cloud data processing, satellite altimetry data for different terrains were simulated, using built-in flat, stepped, terraced, and inverted terrace terrain models, such as... Figure 8 As shown in Table 1, the altimeter parameters were set to 0.3 and 80° solar altitude (characterizing strong background radiation). The altimeter data for these simple shapes were simulated. Figure 9 As shown. To better illustrate the simulation results for different terrains, Figure 9 Except for flat terrain, which displays noise point clouds, the simulation results for other terrains only display signal point clouds.

[0335] CCR echo photons:

[0336] The altimeter in Table 1 has only a single channel, a dead zone of 250 ns, a pixel size of 8.3 meters, a repetition rate of 1 kHz, and a ground sampling interval of 7 meters. These parameters determine that the altimeter is not suitable for detecting CCR targets. To demonstrate the simulation results of the above process for CCR targets, this embodiment uses the parameters of the ICESat-2 / ATLAS altimeter (see Table 2). The CCR parameters and their deployment locations are shown in Table 3.

[0337] Table 2 Parameters of ICESat-2 / ATLAS Altimeter

[0338]

[0339] Table 3. CCR parameters used in simulation and their placement locations.

[0340]

[0341] Figure 10 The CCR deployment and spaceborne laser simulation data of this embodiment are shown.

[0342] Actual terrain:

[0343] Two terrain types were selected: urban and mountainous. The urban terrain mainly included three land cover types: buildings, vegetation, and water bodies, with a point cloud density of 23.29 pts / m². 2 The mountainous terrain slopes from west to east, with mountains dominating the west and gentle slopes formed by year-round rain erosion in the east. The point cloud density is 9.86 pts / m². 2 The point cloud data rendering and the drawn flight trajectory are as follows: Figure 11 , Figure 13 As shown. The simulated point cloud of a spaceborne laser array in an urban area is as follows. Figure 12 , Figure 14 As shown.

[0344] This invention also provides a computer device. Figure 15This is a schematic diagram of the structure of a computer device provided in an embodiment of the present invention; see the accompanying drawings. Figure 15 As shown, the computer device includes: an input device 23, an output device 24, a memory 22, and a processor 21; the memory 22 is used to store one or more programs; when the one or more programs are executed by the one or more processors 21, the one or more processors 21 implement the integrated simulation method for three-dimensional terrain mapping data of spaceborne array lidar as provided in the above embodiments; wherein the input device 23, the output device 24, the memory 22, and the processor 21 can be connected via a bus or other means. Figure 15 Taking the example of a connection between China and Israel via a bus.

[0345] The memory 22, as a read / write storage medium for a computing device, can be used to store software programs and computer-executable programs, such as the program instructions corresponding to the integrated simulation method for three-dimensional terrain mapping data of the spaceborne array lidar described in this embodiment of the invention. The memory 22 may mainly include a program storage area and a data storage area. The program storage area may store the operating system and at least one application program required for a function; the data storage area may store data created based on the use of the device. Furthermore, the memory 22 may include high-speed random access memory and non-volatile memory, such as at least one disk storage device, flash memory device, or other non-volatile solid-state storage device. In some instances, the memory 22 may further include memory remotely located relative to the processor 21, and these remote memories can be connected to the device via a network. Examples of such networks include, but are not limited to, the Internet, corporate intranets, local area networks, mobile communication networks, and combinations thereof.

[0346] The input device 23 can be used to receive input digital or character information, and generate key signal inputs related to user settings and function control of the device; the output device 24 may include display devices such as a display screen.

[0347] The processor 21 executes various functional applications and data processing of the device by running software programs, instructions and modules stored in the memory 22, thereby realizing the above-mentioned comprehensive simulation method for three-dimensional terrain mapping data of spaceborne array lidar.

[0348] The computer equipment provided above can be used to execute the integrated simulation method for three-dimensional terrain mapping data of spaceborne array lidar provided in the above embodiments, and has corresponding functions and beneficial effects.

[0349] This invention also provides a storage medium containing computer-executable instructions. When executed by a computer processor, these instructions are used to perform the comprehensive simulation method for three-dimensional terrain mapping data from a spaceborne array lidar provided in the above embodiments. The storage medium can be any type of memory device or storage device, including: mounting media such as CD-ROM, floppy disk, or magnetic tape; computer system memory or random access memory such as DRAM, DDR RAM, SRAM, EDO RAM, Rambus RAM, etc.; non-volatile memory such as flash memory, magnetic media (e.g., hard disk or optical storage); registers or other similar types of memory elements; the storage medium may also include other types of memory or combinations thereof; furthermore, the storage medium may reside in a first computer system in which the program is executed, or it may reside in a different second computer system connected to the first computer system via a network (such as the Internet); the second computer system can provide program instructions to the first computer for execution. The storage medium includes two or more storage media that can reside in different locations (e.g., in different computer systems connected via a network). The storage medium can store program instructions (e.g., specifically implemented as a computer program) executable by one or more processors.

[0350] Of course, the computer-executable instructions provided in the embodiments of the present invention are not limited to the comprehensive simulation method of three-dimensional terrain mapping data of spaceborne array lidar as described in the above embodiments, but can also execute related operations in the comprehensive simulation method of three-dimensional terrain mapping data of spaceborne array lidar provided in any embodiment of the present invention.

[0351] The technical solution of the present invention has been described above with reference to the preferred embodiments shown in the accompanying drawings. However, it will be readily understood by those skilled in the art that the scope of protection of the present invention is obviously not limited to these specific embodiments. Without departing from the principles of the present invention, those skilled in the art can make equivalent changes or substitutions to the relevant technical features, and the technical solutions after these changes or substitutions will all fall within the scope of protection of the present invention.

[0352] The above description is merely a preferred embodiment of the present invention and is not intended to limit the invention. Various modifications and variations can be made to the present invention by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A comprehensive simulation method for three-dimensional terrain mapping data from a spaceborne array lidar, characterized in that, Includes the following steps: S1. Establish a three-dimensional terrain mapping simulation link for spaceborne array lidar; S2. Construct a comprehensive simulation model for three-dimensional terrain mapping using a spaceborne array lidar, and generate a three-dimensional terrain simulation dataset for the spaceborne array lidar. S3. Multiple evaluation indicators, including noise rate, average signal photon number, detection probability, signal-to-noise ratio, and elevation accuracy, are used to evaluate the quality of spaceborne array laser simulation data under different parameter configurations. The method for constructing the spaceborne laser integrated simulation model in step S2 includes the following steps: S21. Construct a precise geometric positioning model for the array laser, including: Perform the relevant coordinate system definition and transformation; Based on the defined and transformed coordinate system, a rigorous geometric positioning model for the spaceborne array laser altimeter is established. S22. Construct an array laser radiation transmission model; S23. Construct a single-photon detector response model; The method for defining and transforming the relevant coordinate system in step S21 includes the following steps: S211. Establish the coordinate system of the array lidar (O L -X L Y L Z L ); with the center of the lens of the lidar imaging system as the origin O. L The Z-axis is perpendicular to the detector's focal plane and points towards the nadir. The X-axis and Y-axis are parallel to the edge of the focal plane array and form a right-handed system with the Z-axis. Let the distance between the optical center of the laser detector and the focal plane be... The coordinates of the array center in the lidar coordinate system are represented as (0, 0, -). Suppose the detector array has n rows and m columns, where m and n are even numbers, and the pixel size is... Taking the first pixel in the upper right corner of the detector array as the first row and first column pixel, the coordinates of the r-th row and c-th column pixel in the array lidar coordinate system are expressed as follows: ； Equation (1) is obtained by calculating the coordinates of the r-th row and c-th column pixel in the array lidar coordinate system: （1） 3D coordinates of the corresponding laser footprint points on the ground In the lidar coordinate system, it is represented by equation (2): （2） In equations (1) and (2), To obtain the distance from the pixel position to the target for the lidar system; To point the projection on X L O L Y L plane and X L The angle between the positive axes; For pointing to Z L The angle between the positive axes; S212, Establish the satellite body coordinate system (O B -X B Y B Z B The satellite's coordinate system is defined as follows: the satellite's center of mass is the origin O. B The X-axis points in the direction of flight, the Z-axis points to the nadir, and the direction of the Y-axis is determined by the right-hand rule. By performing coordinate translation and rotation transformations, the positions of ground points in the array lidar coordinate system are transformed to the satellite body coordinate system: （3） In equation (3), These are the coordinates of a ground point in the satellite's coordinate system. This is the rotation matrix for transforming the array lidar to the satellite body coordinate system. It is the offset between the center of the array lidar lens and the origin of the satellite's coordinate system; S213. Establish the orbital coordinate system (O O -X O Y O Z O The origin of the orbital coordinate system is the satellite's center of mass, the X-axis points in the direction of the satellite's flight, the Z-axis points in the Earth's center, and the Y-axis is perpendicular to the XOZ plane and forms a right-handed system with the X-axis and Z-axis. The coordinate transformation from the satellite's body coordinate system to the orbital coordinate system is completed by rotating along three axes: （4） In equation (4), These are the coordinates of the ground point in the orbital coordinate system; This is the rotation matrix for transforming the satellite's body coordinate system to its orbital coordinate system. The three attitude angles of the satellite determined by the star sensor: roll angle Pitch angle Yaw angle composition: （5） S214. Establish a fixed inertial reference frame in space; with the Earth's center of mass as the origin of the coordinate system, the X-axis points to the vernal equinox, the Z-axis points to the celestial north pole, and the Y-axis is perpendicular to the XOZ plane and forms a right-handed frame with the X-axis and Z-axis. Transform the orbital coordinate system to the ICRF coordinate system using coordinate translation and rotation: （6） In equation (6), To determine the offset of the origin of the orbital coordinate system from the origin of the ICRF coordinate system, and to solve for the rotation matrix from the orbital coordinate system to the ICRF coordinate system, we need to know the satellite's position vector in the ICRF coordinate system at time t. and velocity vector The expression for calculating the rotation matrix between the orbital coordinate system and the ICRF coordinate system is: （7） In equation (7), ; S215. Establish a fixed Earth reference system; with the Earth's center of mass as the origin, the X-axis points to the intersection of the Greenwich Meridian and the Earth's equator, the Z-axis points to the Earth's North Pole, and the Y-axis is perpendicular to the XOZ plane and forms a right-handed system with the X-axis and Z-axis. The origin of both the ICRF and ITRF coordinate systems is the Earth's center of mass. The ICRF coordinate system is established by multiplying by a rotation matrix. Transform to ITRF coordinate system: （8） In equation (8), These are coordinates on a fixed Earth-based reference frame. The formula for calculation is: ； Where W(t), R(t), and PN(t) are the polar motion matrix, Earth rotation matrix, precession matrix, and nutation matrix, respectively.

2. The method for comprehensive simulation of three-dimensional terrain mapping data from a spaceborne array lidar as described in claim 1, characterized in that, The method for establishing the spaceborne single-photon array laser altimetry simulation link in step S1 includes the following steps: S11. Calculate the object-space three-dimensional coordinates corresponding to the array laser detection pixels; S12. Simulated signal and noise photon radiation response, including: constructing a Delaunay triangulation using point cloud data from airborne radar; obtaining surface reflectivity information for the corresponding wavelength of the laser based on the intensity of the point cloud; simulating the surface echo waveform and noise waveform using an echo simulation model and a noise simulation model respectively; and combining the surface echo waveform and the noise waveform to obtain a comprehensive target echo containing both signal and noise. S13, Analog array laser detector response, including: S131. The target echo is synthesized by convolution of the impulse response function to obtain the echo received by the array laser altimeter system. S132. The Monte Carlo method is used to simulate the detector's detection process, assuming a total of For each pixel, the probability of each detection time slot is calculated based on the single-photon detector detection model. The probability value is compared with a random number following a uniform distribution U(0,1). When the probability value is greater than the random number, the time tag of the corresponding time slot is obtained; when the probability value is less than or equal to the random number, the corresponding time slot is discarded. A group of photons with time tags is obtained. Photons in the dead zone are discarded to obtain the photon point cloud detected by a single pixel. S133. Repeat steps S311-S312 to simulate all photon events detected by all pixels and complete the simulation of all pixels.

3. The method for comprehensive simulation of three-dimensional terrain mapping data from a spaceborne array lidar as described in claim 1, characterized in that, The expression for the rigorous geometric positioning model in step S21, which establishes the rigorous geometric positioning model of the spaceborne array laser altimeter, is as follows: （9） In equation (9), These are the coordinates of the pixel position in ITRF. It is the position of the phase center of the GPS antenna of a satellite measured by the GPS positioning system; The method for constructing the array laser radiation transmission model in step S22 includes the following steps: S221. Calculate the signal radiation scattered by the Lambert body, which includes solar radiation and laser. During transmission, the laser first comes into contact with the atmosphere in the environment and interacts with atmospheric molecules and particles, resulting in radiation attenuation and laser beam deflection. According to the different effects of the atmosphere on radiation, the laser beam deflection is caused by atmospheric refraction, and the attenuation of radiation caused by absorption and scattering of molecules and aerosol particles in the atmosphere is described by Lambert's law through atmospheric transmittance, as shown in equation (10). The nonlinear effect of atmospheric turbulence brings about random drift, diffusion and intensity fluctuation of the light spot, resulting in changes in the spatial distribution of laser beam energy, described by the Gamma distribution model, as shown in equation (11). （10） In equation (10), The irradiance at the time of launch. Let z be the irradiance returned at a distance z. Atmospheric extinction coefficient; （11） In equation (11), Let m be the gamma function, and m be the reciprocal of the Rytov variance. By acquiring atmospheric information, surface reflectivity, and geometric information at the calculated pixel array coordinates, and considering the effects of the atmosphere, the number of photons that a single pixel can receive after environmental response is calculated. （12） When the measured ground object is a linear single target, the total number of echo photons of the entire ground object is expressed by the lidar equation (13): （13） In equation (13), C h For fixed hardware parameters, E t To emit laser single pulse energy, A r The effective area of ​​the receiving system is given by R, where hv is the energy of a single photon, which can be calculated using Planck's energy formula: hv = hc / λ, where h is Planck's constant, v is the laser frequency, c is the speed of light, and λ is the laser wavelength; R is the distance between the lidar and the target, ρ is the Lambertian reflectivity, and T is the laser wavelength. a For unidirectional atmospheric transmittance, θ p The zenith angle at which the laser is emitted. This refers to the local surface slope. The laser echo signal of a single pixel arriving at the receiving system can be represented by the convolution of the laser emission pulse and the environmental response function within the field of view of a single pixel: （14） In equation (14), Σ represents the area occupied by a pixel, and β(x,y,R) represents the reflectivity information of a point on the ground. For time delay, Expressed using equation (15): （15） In equation (15), is the Earth's surface elevation at (x, y), and c is the speed of light; Spatial distribution E(x,y) and temporal distribution of the laser beam Represented as: （16） In equation (16), R is the distance between the lidar and the target, and θ T Where is the beam divergence angle, and E is the energy of the emitted laser single pulse. The root mean square pulse width for laser emission; S222. Establish a background noise model and estimate the noise rate of solar background radiation scattering through the atmosphere and reflecting off the Earth's surface into the altimeter: （29） In equation (29), It refers to wavelength-dependent spectral irradiance measured outside the planetary atmosphere. This refers to the bandwidth of the spectral filter. It is the receiver's field of view within the stereoscopic curvature. It is half the receiver's field of view. , These are the zenith angle of the sun at the time of measurement and the zenith angle at which the laser was emitted; For surface reflectance, It is the angle between the sun and the normal to the Earth's surface. Represented as: （30） In equation (30), For local surface slope, This is the solar azimuth angle.

4. The method for comprehensive simulation of three-dimensional terrain mapping data from a spaceborne array lidar as described in claim 1, characterized in that, It also includes a simulation method for spaceborne array laser photonic cloud data designed for ground-based laser corner reflection CCR, wherein the simulation method for spaceborne array laser photonic cloud data designed for ground-based laser corner reflection CCR includes: Calculate the signal radiation scattered by the corner reflector, including: Considering the form of the laser Gaussian beam distribution, the CCR echo photon can be represented as: （17） In equation (17), δ(θ) is the scattering cross-section of the corner reflector, and δ(θ) is expressed as: （18） In equation (18), To normalize the light intensity distribution, J1() is the first-order Bessel function, θ is the diffraction angle, and r is the CCR aperture radius. This represents the peak cross-sectional area of ​​the far-field light intensity. Represented as: （19） In equation (19), ρ is the reflectivity of the coated CCR, the reflectivity of the aluminum-coated CCR is 0.78, and D=2r is the diameter of the CCR aperture. The far-field normalized optical amplitude of CCR is obtained based on Fraunhofer diffraction theory: （20） In equation (20), r is the radius of the CCR; Let n be the normalized polarization complex amplitude of the nth part, for the coated CCR. ; k is the wave number equal to , The wavelength of the laser; , θ0 is the angle between the outgoing beam and the incident beam. If the errors of the three dihedral angles of the CCR are equal and equal to β, The refractive index of n is 1.46; and These are the polar coordinates in the CCR coordinate system and the polar coordinates of the far-field diffraction point P, respectively. θ is the diffraction angle. Let P be the azimuth angle of the diffraction point P; Simplifying equation (20) yields the analytical solution for the normalized amplitude of the CCR far field: （21） In equation (21), For a first-order Bessel function, the remaining parameters in equation (21) are expressed as: ； Based on the relationship between amplitude and light intensity, the far-field light intensity distribution reflected by the CCR can be obtained as follows: （22） The average normalized intensity on the diffraction angle θ ring is: （23） Because the satellite platform operates at high speed in space, when the CCR echo beam is reflected back to the location where the laser pulse was emitted, the satellite's position deviates from the beam's direction by a velocity difference angle. The formula for calculating this velocity difference angle is: （24） In equation (24), Re is the Earth's radius. Here, H is the acceleration due to gravity, H is the satellite's orbital altitude, and z is the zenith angle. When the spaceborne laser altimeter uses nadir measurement, the velocity difference angle is approximately: （25） Satellite located The number of photons that can be received at this location is: （26） In equation (26), x c With y c CCR coordinates; For spaceborne lidar, considering that the emitted laser pulse is Gaussian and the detected target is a linear single target, the received signal according to diffraction theory simplifies equation (26) to: （27） In equation (27), Ns is the average number of photons received, and Ns for the two land cover types is represented by equation (13) and equation (26) respectively; The root mean square pulse width of the received signal. Expressed using equation (28): （28） In equation (28), This is expressed as the root mean square pulse width of the emitted pulse. For surface roughness, and Let θ be the slope of the Earth's surface along the rail direction and perpendicular to the rail direction, respectively; c be the speed of light; and θ be the slope of the Earth's surface along the rail direction and perpendicular to the rail direction, respectively. T This is the laser divergence angle.

5. The method for comprehensive simulation of three-dimensional terrain mapping data from a spaceborne array lidar as described in claim 1, characterized in that, The method for constructing the single-photon detector response model in step S23 includes: The pulse waveform S(t) is collected and recorded after arriving at the altimeter. The pulse response function of the altimeter is: （31） In equation (31), IRF is the impulse response function. This represents the number of boxes along the track. The function is for rounding up; IRF calculations are divided into photon number statistics along two directions: orbit and elevation. The step size for each statistical frame along the track. This represents the total time for statistical analysis along the track. After determining the range of each statistical frame along the track, perform histogram elevation statistics on the photon point cloud within that range according to elevation, with a step size of [missing information]. , For the first The backscattered signal value of each elevation statistical box, the box containing the peak backscattered signal is set to the elevation position of the ground surface by default and set to p; It is the range of the impulse response function, in which and Define the required Surfd elevation values ​​above and below the ground surface, as well as the elevation statistical step size. Seek; The total number of elevation statistics boxes is set to n+m+1; Combined with the receiving efficiency of the receiving system The photoelectric conversion quantum efficiency of the detector After calculating the impulse response function, the laser signal and system background noise are combined and convolved with the impulse response function to obtain the echo received by the altimeter of the entire single-photon laser altimeter system. （32） In equation (32), The echo received by the entire single-photon laser altimeter system. For signal echo, This is background noise from the sun. For dark counting noise, the noise is synthesized into ; After passing through the filter, the laser light is further transmitted to the single-photon detector, which then... Detected within each time slot The probability of a photon is represented by a Poisson distribution: （33） The detection of a laser beam after passing through atmospheric turbulence involves two stochastic processes: atmospheric turbulence and Poisson detection by the detector. The stochastic process of atmospheric turbulence affecting photons influences the parameter N in the Poisson stochastic process of photon detection by the detector. Using Mandel's equation, the probability density of laser detection after passing through atmospheric turbulence is: （34） The probability that no photon detection occurs within a single time slot is: （35） If the detection of a photon within a single time slot is complementary to the absence of a photon detection event within a single time slot, then the probability of detecting a photon event within a single time slot is: （36） Considering the effect of the dead zone, the detection probability of a single-photon detector in the i-th time slot is the probability that no photon detection occurs during the dead zone duration and the probability that the i-th time slot is detected without considering the dead zone: （37）。 6. The method for comprehensive simulation of three-dimensional terrain mapping data from a spaceborne array lidar according to claim 1, characterized in that, The method for evaluating the quality of spaceborne array laser simulation data under different parameter configurations includes: S31. Calculate the photon point cloud noise rate, whereby the point cloud noise rate is defined as the number of noise photon events recorded by a single pixel of the array laser altimeter per unit time: （38） In equation (38), The noise rate defined in this paper, This represents the number of noise records made in 50 detections for a single pixel. For window height, The noise is the total number of photons within 50 beams minus the signal identified by the built-in filtering algorithm. The speed of light; S32. Calculate the average signal photon count, which is defined as the average number of signal photon events recorded per pixel in a single detection: （39） In equation (39), The average number of signal photons. The total number of signal photons recorded in 50 detections per pixel; S33. Calculate the detection probability, which is defined as the probability that a single pixel can detect the target in a single detection: （40） In equation (39), Indicates the detection probability. This indicates the number of signal photons recorded out of 50 detections; S34. Calculate the signal-to-noise ratio (SNR). Define the SNR of altimeter data as the logarithm of the ratio of signal photons to noise within a 1m elevation range: （41） In equation (41), SNR is the signal-to-noise ratio of the point cloud. The number of noises within the range. .

7. The method for comprehensive simulation of three-dimensional terrain mapping data from a spaceborne array lidar according to claim 2, characterized in that, The method for calculating the object-side three-dimensional coordinates of the array laser detector pixels in step S11 includes: calculating the two-dimensional coordinates of the laser detector pixels in the array lidar coordinate system and the pixel pointing vector based on the altimeter parameters; calculating the object-side three-dimensional coordinates by combining the satellite attitude and orbit parameters with the ground reference terrain; calculating the atmospheric refraction correction using atmospheric pressure, temperature, and humidity parameters to obtain the actual distance information; calculating the object-side three-dimensional coordinates based on the geometric model of the spaceborne array laser altimeter; and obtaining the object-side three-dimensional coordinates with additional offset by comprehensively considering the tidal correction and the influence of optical aberration.

8. A comprehensive simulation system for three-dimensional terrain mapping data from a spaceborne array lidar, used to implement the comprehensive simulation method for three-dimensional terrain mapping data from a spaceborne array lidar as described in any one of claims 1-7, characterized in that, include: Spaceborne Single-Photon Array Laser Altimetry Simulation Link Subsystem: Used to establish a spaceborne single-photon array laser altimetry simulation link; Integrated simulation model construction subsystem: used to construct a comprehensive simulation model of spaceborne lasers and generate a simulation dataset of spaceborne array lasers; The array laser data quality evaluation subsystem is used to evaluate the quality of spaceborne array laser simulation data under different parameter configurations using multiple evaluation indicators such as noise rate, average signal photon count, detection probability, signal-to-noise ratio, and elevation accuracy.

9. A computer device, the computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the program, it implements the steps of the integrated simulation method for three-dimensional terrain mapping data of spaceborne array lidar as described in any one of claims 1-7.

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