Lunar-based GNSS-R signal simulation and DDM generation method based on complete polarization layered scattering model

Abstract

The invention discloses a moon-based GNSS-R signal simulation and DDM generation method based on a complete polarization layered scattering model, and belongs to the technical field of deep space exploration and microwave remote sensing. The method comprises the following steps: firstly, based on a vector radiation transfer theory, constructing a complete polarization bistatic scattering coefficient model, comprehensively considering surface scattering, subsurface interface scattering, buried particle body scattering and multiple scattering mechanisms, and calculating polarization bistatic scattering coefficients of all points on the lunar surface through a Mueller matrix summation mode; and then taking the obtained scattering coefficient as an input parameter, performing delay and Doppler mapping on each space grid point in a scintillation region in combination with a Z-V model and an orbit geometrical relationship between a GNSS satellite and a moon-based receiver, and finally generating a high-fidelity DDM waveform through integral operation. Full-link forward modeling from a microscopic physical scattering mechanism to macroscopic observation data is realized, and the method has strong physical interpretability and high simulation precision.

Description

TECHNICAL FIELD

[0001] The application relates to the field of deep space exploration and microwave remote sensing, and particularly relates to a lunar-based GNSS-R signal simulation and DDM generation method based on a full-polarization layered scattering model. BACKGROUND

[0002] With the development of deep space exploration technology, the demand for fine perception of the lunar surface and subsurface structure is increasing. Traditional optical and infrared remote sensing means are limited by lighting conditions and penetration ability, and it is difficult to achieve all-weather and all-day observation with certain depth penetration. In contrast, microwave remote sensing has become an important tool for studying the lunar weathering layer structure, water ice distribution and geological structure due to its good penetration, sensitivity to medium dielectric properties and immunity to light.

[0003] In recent years, the technology of using global navigation satellite system reflected signals (GNSS-R) for remote sensing has gradually emerged. This technology uses existing GNSS signals as an external illumination source, and by receiving reflected signals on the ground or space platform, the surface environmental parameters are inverted, which has the advantages of being passive, low power consumption and global coverage. However, existing GNSS-R models mainly face earth application scenarios such as ocean height measurement and soil moisture inversion, and usually use simplified surface scattering models (such as Kirchhoff approximation or small slope approximation in Z-V model), ignoring volume scattering and layered structure effects.

[0004] The lunar surface is covered by loose weathering layer, with a typical thickness of several to tens of meters, and there is obvious vertical layered structure (such as surface fine-grained lunar soil, middle layer of rock debris, and bottom consolidated bedrock). In addition, water ice may be deposited in the permanent shadow area, which significantly changes the local dielectric properties. These factors result in the fact that the traditional GNSS-R model suitable for flat and uniform ground cannot accurately describe the complex bistatic scattering process of the lunar surface. Therefore, it is urgent to develop a physical scattering model that can reflect the layered structure and volume scattering characteristics of lunar soil, and integrate it into the GNSS-R system-level simulation framework to support future lunar-based remote sensing mission design and data interpretation.

[0005] Although existing research has attempted to apply radiative transfer theory to planetary surface scattering modeling, there is no work that combines vector radiative transfer (VRT) model with Z-V GNSS-R observation model to realize the complete forward simulation chain from micro-scattering mechanism to macro- DDM output. Especially under full polarization conditions, how to integrate multiple scattering mechanisms and maintain polarization information consistency is still a technical difficulty. SUMMARY

[0006] The application aims to provide a lunar GNSS-R signal simulation and DDM generation method based on a full polarization layered scattering model, which can be used for lunar surface geological structure detection, subsurface material identification and future lunar base site selection and other scientific research and engineering applications.

[0007] To achieve the above-mentioned purpose, the application provides the following solutions. The application provides a lunar GNSS-R signal simulation and DDM generation method based on a full polarization layered scattering model, comprising: S1: obtaining lunar surface physical parameters, GNSS satellite orbit parameters and lunar base receiver orbit parameters; S2: based on the lunar surface physical parameters, a full polarization bistatic scattering coefficient model is established by using a vector radiation transfer (VRT) theory, surface scattering mechanism contribution of a vacuum-weathering layer interface, subsurface scattering mechanism contribution of a weathering layer-bedrock interface, body scattering mechanism contribution caused by a buried particle in the weathering layer, and a subsurface-particle high-order multiple scattering term are calculated respectively, polarization response characteristics of each scattering mechanism are represented in the form of a Mueller matrix, and a total Mueller matrix of the entire lunar surface under a given incident angle and scattering angle condition is obtained by coherently superimposing Mueller matrices of all mechanisms; S3: based on the total Mueller matrix, a bistatic scattering coefficient corresponding to different transmission and reception polarization combinations is calculated by using a Stokes vector transformation relationship, and a spatially distributed scattering coefficient field is formed; S4: based on the GNSS satellite orbit parameters and the lunar base receiver orbit parameters, an observation geometry relationship between the GNSS satellite and the lunar base receiver is determined; S5: based on the observation geometry relationship, a region on the lunar surface that can effectively contribute to the received signal, i.e., a glint region, is calculated; S6: the glint region is divided into a plurality of two-dimensional spatial grid units; S7: the bistatic scattering coefficient is mapped to spatial grid points in each two-dimensional spatial grid unit, so that each spatial grid point has corresponding scattering intensity and polarization properties; S8: for each spatial grid point, according to its geographical location, in combination with the spatial positions and relative motion speeds of the GNSS satellite and the lunar base receiver, a time delay and a Doppler frequency shift of a reflection signal generated by the spatial grid point relative to a direct signal are calculated; S9: taking the time delay and the Doppler frequency shift as independent variables, calling a self-correlation function of a GNSS pseudo-random code and a reflection signal Doppler power spectrum, and taking the bistatic scattering coefficient of the corresponding spatial grid point in S7 as a local scattering intensity factor, the Z-V integral model is substituted and integral operation is performed, and an integral result is obtained; S10: discretize the integration results into a two-dimensional matrix according to delay τ and Doppler f_D, generate a final delay-Doppler map DDM, and complete the whole-link physical simulation of the lunar GNSS-R signal.

[0008] Optionally, the lunar surface physical parameters include dielectric constant, thickness, surface roughness, internal stone particle characteristics and underlying bedrock parameters of the lunar surface weathering layer; the GNSS satellite orbit parameters include position, velocity and antenna pattern information of the GNSS satellite transmitting source; and the lunar receiver orbit parameters include position, velocity and receiving antenna pattern information of the lunar receiver.

[0009] Optionally, the expression of the total Mueller matrix is as follows: ; wherein, denotes the total Mueller matrix, denotes the zenith and azimuth angles of the scattered wave, denotes the zenith and azimuth angles of the incident wave, denotes the surface scattering mechanism contribution of the vacuum-weathering layer interface, denotes the subsurface scattering mechanism contribution of the weathering layer-bedrock interface, denotes the volume scattering mechanism contribution of the buried particles in the weathering layer, denotes the subsurface-particle high-order multiple scattering term.

[0010] Optionally, the expression of the bistatic scattering coefficient is as follows: ; wherein, denotes the bistatic scattering coefficient, denotes the zenith and azimuth angles of the scattered wave, denotes the zenith and azimuth angles of the incident wave, denotes the element in the total Mueller matrix.

[0011] Optionally, the expression of the autocorrelation function of the GNSS pseudo-random code is as follows: ; wherein, denotes the difference between Doppler frequency shifts; denotes the time delay received by the lunar receiver, denotes the delay of the spatial grid point.

[0012] Optionally, the expression of the reflected signal Doppler power spectrum is as follows: ; wherein, denotes the difference between Doppler frequency shifts; represents the Doppler shift of the lunar base receiver; represents the Doppler shift of the lunar surface space grid point.

[0013] Optionally, the expression of the Z-V integral model is as follows: wherein, represents the power value of each pixel in the DDM, represents the GNSS satellite transmitting power, represents the directional diagram of the GNSS satellite transmitting antenna in the direction of the specular reflection point, represents the directional diagram of the lunar base receiver antenna in the direction of the specular reflection point, represents the wavelength of the GNSS signal, represents the coherent integration time, represents the distance from the GNSS satellite to the ground scattering point , represents the distance from the lunar base receiver to the ground scattering point , represents the bistatic scattering coefficient at the lunar surface scattering point , represents the autocorrelation function of the GNSS pseudo-random code, represents the power spectrum of the Doppler shift, is the integral grid area.

[0014] Optionally, the bistatic scattering coefficient in S3 is in a full polarization form, supporting VR, HR, RR, and LR four polarization combination outputs, for analyzing the scattering differences of the lunar surface material under different polarization channels.

[0015] Optionally, the autocorrelation function of the GNSS pseudo-random code used in S9 adopts a theoretical autocorrelation model of C / A code or P(Y) code, and is suitable for signal simulation of L1 or L2 frequency bands of GPS and Beidou systems.

[0016] Optionally, the lunar base GNSS-R signal simulation and DDM generation method based on the full polarization layered scattering model further comprises, after step S10: based on the final delay Doppler map DDM, performing inversion modeling of lunar soil thickness, water ice content, and rubble abundance geological parameters, or serving as a simulation basis for lunar base GNSS-R load design and performance verification.

[0017] According to the specific embodiments provided in the application, the application has the following technical effects: The application provides a lunar base GNSS-R signal simulation and DDM generation method based on a full polarization layered scattering model, which has the following beneficial effects: ​Clear physical mechanism: For the first time, VRT theory is combined with Z-V model to establish a complete physical chain from the microstructure of lunar soil to the macroscopic observation signal, improving the interpretability of the model.

[0018] High simulation accuracy: Fully considering the stratification, volume scattering and multiple scattering effects of lunar soil, the limitations of traditional models that are only applicable to thin layers or smooth surfaces are overcome.

[0019] Supports full polarization simulation: Can output VR, HR, RR, LR and other polarization combinations of DDM, which helps to identify key substances such as water ice and debris.

[0020] Strong applicability: Can simulate signal responses under different frequencies (L1 / L2), different observation geometries, and different lunar soil parameters, serving pre-mission simulation and inversion algorithm training.

[0021] Great practical value: The generated DDM can be directly used for inversion research of lunar soil thickness, density, water ice content, etc., and can also be used as a basis for signal characteristic evaluation in scenarios such as lunar rover navigation and lander obstacle avoidance. BRIEF DESCRIPTION OF DRAWINGS

[0022] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the following will briefly introduce the drawings needed in the embodiments. Obviously, the drawings described below are only some embodiments of the present application, and for those skilled in the art, other drawings can also be obtained without creative labor on the basis of these drawings.

[0023] Figure 1 A flowchart of a lunar GNSS-R signal simulation and DDM generation method based on a full-polarization layered scattering model according to an embodiment of the present application. DETAILED DESCRIPTION

[0024] The technical solutions in the embodiments of the present application will be described in detail below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only some embodiments of the present application, not all embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor are within the scope of protection of the present application.

[0025] In order to make the above-mentioned purposes, features and advantages of the present application more obvious and easy to understand, the present application will be further described in detail below with reference to the drawings and specific embodiments.

[0026] In an exemplary embodiment, as Figure 1As shown, a method for simulating lunar-based GNSS-R signals and generating DDMs based on a fully polarized layered scattering model is provided. This method is executed by a computer device, specifically by a terminal or server alone, or by both a terminal and a server. In this embodiment, it includes the following steps S1 to S10. Wherein: S1: Obtain lunar surface physical parameters, GNSS satellite orbit parameters, and lunar-based receiver orbit parameters.

[0027] The lunar surface physical parameters include the dielectric constant, thickness, surface roughness, internal rock particle characteristics, and underlying bedrock parameters of the lunar regolith; the GNSS satellite orbital parameters include the position, velocity, and antenna pattern information of the GNSS satellite transmitter; and the lunar-based receiver orbital parameters include the position, velocity, and receiving antenna pattern information of the lunar-based receiver.

[0028] S2: Based on the physical parameters of the lunar surface, a fully polarized bistatic scattering coefficient model is established using the vector radiative transfer (VRT) theory. The contributions of the surface scattering mechanism at the vacuum-regolith interface, the subsurface scattering mechanism at the regolith-bedrock interface, the volume scattering mechanism caused by buried particles in the regolith, and the subsurface-particle higher-order multiple scattering terms are calculated. The polarization response characteristics of each scattering mechanism are represented in the form of a Mueller matrix. By coherently superimposing the Mueller matrices of all mechanisms, the total Mueller matrix of any scattering point on the entire lunar surface under given incident and scattering angles is obtained.

[0029] Specifically, the method described above in this application consists of two stages: Phase 1: Constructing a bistatic scattering coefficient model of the fully polarized lunar surface based on vector radiative transfer (VRT) theory. This model treats the lunar regolith as a multi-layered, non-homogeneous medium, comprehensively considering the following four scattering mechanisms: Surface scattering occurs at the interface between the vacuum and the regolith (z=0, representing the height of the lunar surface horizontal plane) and is caused by surface roughness. Subsurface scattering occurs at the interface between the weathered layer and the bedrock (z=-d, representing a depth of d centimeters below the lunar surface), and is controlled by interface undulations and dielectric transitions. Volume scattering: originates from the scattering of incident waves by randomly distributed inhomogeneous bodies such as gravel and pores within the weathered layer; Multiple scattering: includes higher-order interactions between surfaces and subsurfaces, and between volume scattering and other interfaces.

[0030] Each mechanism expresses its polarization scattering characteristics in the form of Mueller matrix, and the total Mueller matrix is obtained by matrix addition. Then, according to the Stokes vector transformation formula, the bistatic scattering coefficient under the combination of emission polarization p and reception polarization q is derived, and the spatially continuous scattering field is constructed.

[0031] wherein the expression of the total Mueller matrix is as follows: ; wherein, denotes the total Mueller matrix, denotes the zenith angle and the azimuth angle of the scattered wave, denotes the zenith angle and the azimuth angle of the incident wave, denotes the surface scattering mechanism contribution of the vacuum-weathering layer interface, denotes the subsurface scattering mechanism contribution of the weathering layer-bedrock interface, denotes the volume scattering mechanism contribution caused by the buried particles in the weathering layer, denotes the subsurface-particle high-order multiple scattering term.

[0032] S3: based on the total Mueller matrix, the bistatic scattering coefficients corresponding to different emission and reception polarization combinations are calculated by using the Stokes vector transformation relationship, and the spatially distributed scattering coefficient field is formed.

[0033] The expression of the bistatic scattering coefficient is as follows: ; wherein, denotes the bistatic scattering coefficient, denotes the zenith angle and the azimuth angle of the scattered wave, denotes the zenith angle and the azimuth angle of the incident wave, denotes the element in the total Mueller matrix.

[0034] The bistatic scattering coefficient in the embodiment is in the form of full polarization, supports VR, HR, RR and LR four polarization combination outputs, and is used for analyzing the scattering differences of the lunar surface material under different polarization channels.

[0035] The second stage is to construct a DDM generation method based on the Z-V model. The output of the first stage is taken as the core input parameter, combined with the actual orbit parameters of the GNSS satellite and the lunar base receiver, and the following operations are performed: calculate the observation geometry to determine the range of the “flickering area”; divide the flickering area into spatial grids, and map the to each grid point; calculate the signal delay τ and the Doppler frequency shift of each grid point​ ; Using the ZV integral formula, the scattering coefficient, GNSS code autocorrelation function, and Doppler power spectrum are jointly integrated to generate the final delayed Doppler map (DDM). The detailed steps are as follows: S4: Based on the orbital parameters of the GNSS satellite and the orbital parameters of the lunar-based receiver, determine the observation geometric relationship between the GNSS satellite and the lunar-based receiver.

[0036] S5: Calculate the region on the lunar surface that can effectively contribute to the received signal, i.e., the scintillation region, based on the observed geometric relationship.

[0037] S6: Divide the flashing area into several two-dimensional spatial grid units.

[0038] S7: Map the bistatic scattering coefficients to the spatial grid points in each two-dimensional spatial grid unit, so that each spatial grid point has the corresponding scattering intensity and polarization properties.

[0039] S8: For each spatial grid point, based on its geographical location and combined with the spatial position and relative motion velocity of the GNSS satellite and the lunar-based receiver, calculate the time delay and Doppler shift of the reflected signal generated by the spatial grid point relative to the direct signal.

[0040] S9: Using the time delay and Doppler frequency shift as independent variables, call the autocorrelation function of the GNSS pseudo-random code and the Doppler power spectrum of the reflected signal, and substitute the bistatic scattering coefficient of the corresponding spatial grid point in S7 as the local scattering intensity factor into the ZV integral model, perform the integration operation, and obtain the integration result.

[0041] The expression for the ZV integral model is as follows: ; in, This represents the power value of each pixel in the DDM. Indicates the GNSS satellite transmit power. This represents the radiation pattern of the GNSS satellite transmitting antenna in the direction of the mirror reflection point. This shows the radiation pattern of the lunar-based receiver antenna in the direction of the specular reflection point. Indicates the wavelength of the GNSS signal. Indicates the coherent integration time. Indicates the scattering point from GNSS satellites to the Earth's surface. distance, Indicates the point of scattering from the lunar-based receiver to the Earth's surface. distance, Represents the surface scattering points of the moon. The bistatic scattering coefficient at that location, autocorrelation function of GNSS pseudo-random code, power spectrum of Doppler shift, is the integral grid area.

[0042] ; wherein, is the difference of Doppler shift; is the time delay received by the lunar receiver, is the delay of the spatial grid point.

[0043] The expression of the reflected signal Doppler power spectrum is as follows: ; wherein, is the difference of Doppler shift; is the Doppler shift of the lunar receiver; is the Doppler shift of the lunar surface spatial grid point.

[0044] S10: discretize the integral results into a two-dimensional matrix according to time delay and Doppler shift to generate a final delay Doppler map DDM, and complete the full-link physical simulation of the lunar GNSS-R signal.

[0045] In another embodiment of the present application, in order to detect water ice and identify the abundance of stones and rocks, the above-mentioned method in the present application further comprises: Based on the final delay Doppler map DDM, the inversion modeling of lunar soil thickness, water ice content and rock abundance geological parameters is carried out, or it is used as a simulation basis for lunar GNSS-R load design and performance verification.

[0046] Microwave band remote sensing technology is an indispensable core means in deep space exploration, especially in lunar scientific research. Its importance mainly lies in its unique penetration, material identification and all-weather working ability.

[0047] Firstly, microwave remote sensing has the ability to penetrate the lunar surface subsurface material. Unlike optical remote sensing which can only detect surface information in the visible light band, electromagnetic waves of specific wavelengths (such as P-band and L-band) can effectively penetrate the loose weathering layer (Regolith) of several to tens of meters thick on the lunar surface, realizing the "perspective" of the hidden geological structure under the shallow surface. This enables scientists to detect key information hidden by lunar soil, such as lava tube structure, ancient geological structure, and different stratigraphic interfaces, providing direct evidence from the underground for studying the geological evolution history of the moon.

[0048] Second, this technique is one of the most effective methods for identifying and quantifying key material components. By analyzing the interaction of microwaves with matter (such as dielectric constant, scattering characteristics), we can effectively identify the composition and physical state of lunar surface materials. For example: When applied to the detection of water ice scenarios: there is a significant difference in the dielectric properties of water ice and lunar soil rocks. By analyzing the scattering intensity and polarization characteristics of microwave signals, we can infer the presence, distribution, and even purity of water ice in permanently shadowed craters, which is crucial for future lunar water resource utilization.

[0049] When applied to the identification of boulder and rock abundance scenarios: surface and subsurface boulders are important geological units and landing risk sources. Microwaves are very sensitive to boulders with sizes similar to their wavelengths, and their scattering signals can effectively invert the size, density, and distribution of boulders, providing scientific basis for lunar rover path planning and safe landing site selection.

[0050] Finally, microwave remote sensing is not limited by lighting conditions, neither dependent on sunlight nor able to penetrate the extremely cold lunar night environment and possible dust interference for continuous observation, achieving truly continuous detection day and night, which is a huge advantage that optical and infrared remote sensing cannot match.

[0051] Therefore, developing advanced lunar microwave remote sensing technology is not only a necessary requirement for deepening lunar scientific research (such as geological structure, water ice distribution, and lunar soil properties), but also a strategic direction for providing key technical support for future lunar base site selection, resource development and utilization, and long-term residence.

[0052] The core of the problem presented in this application is how to use the difference in dielectric properties to detect water ice through microwave scattering signals, which is a very classic and important remote sensing detection principle. Specifically, first, we need to clarify the key scientific basis: Dielectric constant difference: In the microwave frequency band, the relative dielectric constant of pure water ice is about 3.1-3.2 (real part), and the loss tangent is very small (imaginary part is small), which is a "transparent" weak scattering medium. The real part of the dielectric constant of dry lunar soil / rock is lower, about 1.5-2.5, and the loss is also very small. However, once the lunar soil contains water ice, even a small amount, the dielectric constant will change significantly. This is because the relative dielectric constant of liquid water is as high as 80 in the real part, and the imaginary part is also large (loss is strong). Even if the water is frozen, the dielectric constant of the ice-lunar soil mixture will be significantly higher than that of dry lunar soil.

[0053] Scattering mechanism variation: The change of dielectric constant will directly change the scattering characteristics of the lunar surface material. Higher dielectric constant usually means stronger reflection (backscattering) and more obvious dielectric interface effect. Polarization characteristics (especially circular polarization RR / LR and circular linear polarization VR / HR) are very sensitive to the roughness of the surface and the non-uniformity of the subsurface (such as water-ice clumps).

[0054] wherein, VR, HR, RR, LR represent the transmit polarization is RHCP, and the receive polarization is vertical (V), horizontal (H), RHCP and LHCP respectively.

[0055] In summary, the present application firstly constructs a full-polarization bistatic scattering coefficient model suitable for the lunar weathering layer structure based on the vector radiative transfer (VRT) theory, comprehensively considers the surface scattering, subsurface interface scattering, buried particle body scattering and multiple scattering mechanisms, and calculates the polarization bistatic scattering coefficient of each point on the lunar surface through the Mueller matrix summation method; then takes the obtained scattering coefficient as an input parameter, combines the Zavorotny-Voronovich (Z-V) model, and performs delay and Doppler mapping on each spatial grid point in the fluctuation zone under the known orbital geometric relationship of the GNSS satellite and the lunar receiver, and finally generates a high-fidelity DDM waveform through integral operation. The present application realizes the full-link forward modeling from the microscopic physical scattering mechanism to the macroscopic observation data, has strong physical interpretability and high simulation accuracy, and can be used for lunar GNSS-R task design, surface parameter inversion algorithm development and lunar resource exploration evaluation.

[0056] The technical features of the above embodiments can be combined in any manner. To make the description concise, not all possible combinations of the technical features in the above embodiments are described, but as long as the combinations of the technical features do not exist contradictions, they should be considered as the scope of the present application.

[0057] The principles and implementation modes of the present application are described by specific examples in this paper, and the above embodiment descriptions are only used to help understand the method and its core idea of the present application; at the same time, for those skilled in the art, according to the idea of the present application, the specific implementation mode and application range will be changed. In summary, the content of the specification should not be understood as a limitation of the present application.

Claims

1. A method for simulating lunar-based GNSS-R signals and generating DDM based on a fully polarized layered scattering model, characterized in that, Includes the following steps: S1: Acquire lunar surface physical parameters, GNSS satellite orbit parameters, and lunar-based receiver orbit parameters; S2: Based on the physical parameters of the lunar surface, a fully polarized bistatic scattering coefficient model is established using the vector radiative transfer (VRT) theory. The contributions of the surface scattering mechanism at the vacuum-regolith interface, the subsurface scattering mechanism at the regolith-bedrock interface, the volume scattering mechanism caused by buried particles in the regolith, and the subsurface-particle higher-order multiple scattering terms are calculated. The polarization response characteristics of each scattering mechanism are represented in the form of Mueller matrices. By coherently superimposing the Mueller matrices of all mechanisms, the total Mueller matrix of any scattering point on the entire lunar surface under given incident and scattering angles is obtained. S3: Based on the total Mueller matrix, the bistatic scattering coefficients corresponding to different combinations of transmitting and receiving polarizations are calculated using the Stokes vector transformation relationship, forming a spatially distributed scattering coefficient field; S4: Based on the GNSS satellite orbit parameters and the lunar base receiver orbit parameters, determine the observation geometric relationship between the GNSS satellite and the lunar base receiver; S5: Calculate the region on the lunar surface that can effectively contribute to the received signal based on the observed geometric relationship, i.e., the scintillation region; S6: Divide the flashing area into several two-dimensional spatial grid units; S7: Map the bistatic scattering coefficients to the spatial grid points in each two-dimensional spatial grid unit, so that each spatial grid point has the corresponding scattering intensity and polarization properties; S8: For each spatial grid point, based on its geographical location and combined with the spatial position and relative motion velocity of the GNSS satellite and the lunar-based receiver, calculate the time delay and Doppler shift of the reflected signal generated by the spatial grid point relative to the direct signal; S9: Using the time delay and Doppler frequency shift as independent variables, call the autocorrelation function of the GNSS pseudo-random code and the Doppler power spectrum of the reflected signal, and use the bistatic scattering coefficient of the corresponding spatial grid point in S7 as the local scattering intensity factor, substitute it into the ZV integral model, perform the integration operation, and obtain the integration result; S10: Discretize the integration result into a two-dimensional matrix according to the time delay and Doppler frequency shift to generate the final Delayed Doppler Map (DDM) and complete the full-link physical simulation of the lunar-based GNSS-R signal.

2. The method for simulating lunar-based GNSS-R signals and generating DDMs based on a fully polarimetric layered scattering model according to claim 1, characterized in that, The physical parameters of the lunar surface include the dielectric constant, thickness, surface roughness, internal gravel particle characteristics, and parameters of the underlying bedrock of the lunar regolith. The GNSS satellite orbit parameters include: the position, velocity, and antenna pattern information of the GNSS satellite transmitter; the lunar-based receiver orbit parameters include: the position, velocity, and receiving antenna pattern information of the lunar-based receiver.

3. The method for simulating lunar-based GNSS-R signals and generating DDMs based on a fully polarized layered scattering model according to claim 1, characterized in that, The expression for the total Mueller matrix is ​​as follows: ； in, Represents the total Mueller matrix, Indicates the zenith angle and azimuth angle of the scattered wave. Indicates the zenith angle and azimuth angle of the incident wave. This indicates the contribution of surface scattering mechanisms at the vacuum-weathering layer interface. This indicates the contribution of the subsurface scattering mechanism at the weathered layer-bedrock interface. This indicates the contribution of volume scattering mechanism caused by particles buried within the weathering layer. This represents the higher-order multiple scattering term of the subsurface-particle scattering.

4. The method for simulating lunar-based GNSS-R signals and generating DDMs based on a fully polarized layered scattering model according to claim 1, characterized in that, The expression for the bistatic scattering coefficient is as follows: ； in, Indicates the bistatic scattering coefficient. Indicates the zenith angle and azimuth angle of the scattered wave. Indicates the zenith angle and azimuth angle of the incident wave. This represents an element in the total Mueller matrix.

5. The method for simulating lunar-based GNSS-R signals and generating DDMs based on a fully polarized layered scattering model according to claim 1, characterized in that, The expression for the autocorrelation function of the GNSS pseudo-random code is as follows: ； in, This represents the difference in Doppler frequency shift; This indicates the time delay received by the lunar-based receiver. Indicates the delay of spatial grid points.

6. The method for simulating lunar-based GNSS-R signals and generating DDMs based on a fully polarimetric layered scattering model according to claim 1, characterized in that, The expression for the Doppler power spectrum of the reflected signal is as follows; ； in, This represents the difference in Doppler frequency shift; Indicates the Doppler frequency shift of the lunar-based receiver; This represents the Doppler frequency shift of spatial grid points on the lunar surface.

7. The method for simulating lunar-based GNSS-R signals and generating DDMs based on a fully polarized layered scattering model according to claim 1, characterized in that, The expression for the ZV integral model is as follows: ； in, This represents the power value of each pixel in the DDM. Indicates the GNSS satellite transmit power. This represents the radiation pattern of the GNSS satellite transmitting antenna in the direction of the mirror reflection point. This shows the radiation pattern of the lunar-based receiver antenna in the direction of the specular reflection point. Indicates the wavelength of the GNSS signal. Indicates the coherent integration time. Indicates the scattering point from GNSS satellites to the Earth's surface. distance, Indicates the point of scattering from the lunar-based receiver to the Earth's surface. distance, Represents the surface scattering points of the moon. The bistatic scattering coefficient at that location, The autocorrelation function of GNSS pseudo-random codes, The power spectrum representing the Doppler frequency shift; This represents the area of ​​the integral grid.

8. The method for simulating lunar-based GNSS-R signals and generating DDMs based on a fully polarized layered scattering model according to claim 1, characterized in that, The bistatic scattering coefficient in S3 is in a fully polarized form, supporting four polarization combinations: VR, HR, RR, and LR, which are used to analyze the scattering differences of lunar surface materials under different polarization channels.

9. The method for simulating lunar-based GNSS-R signals and generating DDMs based on a fully polarized layered scattering model according to claim 1, characterized in that, The autocorrelation function of the GNSS pseudo-random code used in S9 adopts the theoretical autocorrelation model of C / A code or P(Y) code, which is suitable for the simulation of L1 or L2 frequency band signals of GPS and Beidou systems.

10. The method for simulating lunar-based GNSS-R signals and generating DDMs based on a fully polarimetric layered scattering model according to claim 1, characterized in that, The lunar-based GNSS-R signal simulation and DDM generation method based on the fully polarized layered scattering model further includes, after step S10: performing inversion modeling of geological parameters such as lunar soil thickness, water ice content, and gravel abundance based on the final delayed Doppler image DDM, or using it as a simulation basis for lunar-based GNSS-R payload design and performance verification.

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