Method for lunar-based GNSS-R signal simulation and DDM generation based on full polarization layered scattering model

Abstract

The application discloses a lunar-based GNSS-R signal simulation and DDM generation method based on a full polarization layered scattering model, and belongs to the technical field of deep space exploration and microwave remote sensing. The method first constructs a full polarization bistatic scattering coefficient model based on a vector radiation transfer theory, comprehensively considers 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 a Mueller matrix summation method. Then, the obtained scattering coefficient is taken as an input parameter, a Z-V model is combined with an orbital geometric relationship between a GNSS satellite and a lunar-based receiver, delay and Doppler mapping is performed on each spatial grid point in a scintillation area, and finally, high-fidelity DDM waveforms are generated through integral operation. The application realizes full-link forward modeling from a microscopic physical scattering mechanism to macroscopic observation data, and has strong physical interpretability and high simulation accuracy.

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 there have been attempts 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.

[0008] The application provides a lunar GNSS-R signal simulation and DDM generation method based on a full polarization layered scattering model, comprising:

[0009] S1: obtaining lunar surface physical parameters, GNSS satellite orbit parameters and lunar base receiver orbit parameters;

[0010] S2: based on the lunar surface physical parameters, a full polarization bistatic scattering coefficient model is established by using vector radiation transfer (VRT) theory, the surface scattering mechanism contribution of the vacuum-weathering layer interface, the subsurface scattering mechanism contribution of the weathering layer-bedrock interface, the volume scattering mechanism contribution caused by the buried particles in the weathering layer, and the subsurface-particle high-order multiple scattering term are calculated respectively, the polarization response characteristics of each scattering mechanism are represented in the form of Mueller matrix, and the total Mueller matrix of the entire lunar surface at any scattering point under the given incident angle and scattering angle conditions is obtained by coherently superimposing the Mueller matrices of all mechanisms;

[0011] S3: based on the total Mueller matrix, the bistatic scattering coefficients corresponding to different transmitting and receiving polarization combinations are calculated by using the Stokes vector transformation relationship, and a spatially distributed scattering coefficient field is formed;

[0012] S4: based on the GNSS satellite orbit parameters and the lunar base receiver orbit parameters, the observation geometry relationship between the GNSS satellite and the lunar base receiver is determined;

[0013] S5: based on the observation geometry relationship, the area on the lunar surface that can effectively contribute to the received signal, i.e. the glint area, is calculated;

[0014] S6: the glint area is divided into a plurality of two-dimensional spatial grid units;

[0015] S7: the bistatic scattering coefficient is mapped to the spatial grid points in each two-dimensional spatial grid unit, so that each spatial grid point has corresponding scattering intensity and polarization properties;

[0016] S8: for each spatial grid point, according to its geographical position, the spatial positions and relative motion speeds of the GNSS satellite and the lunar base receiver are combined to calculate the time delay and Doppler frequency shift of the reflected signal relative to the direct signal generated by the spatial grid point;

[0017] S9: calling the autocorrelation function of the GNSS pseudo-random code and the reflected signal Doppler power spectrum as independent variables, and substituting the bistatic scattering coefficient of the corresponding spatial grid point in S7 as the local scattering intensity factor into the Z-V integral model, performing integral operation to obtain the integral result;

[0018] S10: discretizing the integral result according to delay τ and Doppler f_D into a two-dimensional matrix to generate the final delay Doppler map DDM, and completing the whole-link physical simulation of the lunar GNSS-R signal.

[0019] Optionally, the lunar surface physical parameters include dielectric constant, thickness, surface roughness, internal gravel 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.

[0020] Optionally, the expression of the total Mueller matrix is as follows:

[0021] ;

[0022] 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 caused by the buried particles in the weathering layer, denotes the subsurface-particle high-order multiple scattering term.

[0023] Optionally, the expression of the bistatic scattering coefficient is as follows:

[0024] ;

[0025] 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.

[0026] Optionally, the expression of the autocorrelation function of the GNSS pseudo-random code is as follows:

[0027] ;

[0028] wherein, represents the difference of Doppler shifts; represents the time delay received by the lunar receiver, represents the delay of the spatial grid point.

[0029] Optionally, the expression of the reflected signal Doppler power spectrum is as follows:

[0030] ;

[0031] wherein, represents the difference of Doppler shifts; represents the Doppler shift of the lunar receiver; represents the Doppler shift of the lunar surface spatial grid point.

[0032] Optionally, the expression of the Z-V integral model is as follows:

[0033] ;

[0034] wherein, represents the power value of each pixel in the DDM, represents the GNSS satellite transmission power, represents the directional diagram of the GNSS satellite transmission antenna in the direction of the specular reflection point, represents the directional diagram of the lunar 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 lunar surface scattering point , represents the distance from the lunar receiver to the lunar surface 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.

[0035] Optionally, the bistatic scattering coefficient in S3 is in a full polarization form, supporting VR, HR, RR, LR four polarization combination outputs, for analyzing the scattering differences of the lunar surface material under different polarization channels.

[0036] Optionally, 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, and is applicable to the simulation of L1 or L2 frequency band signals of GPS and Beidou systems.

[0037] Optionally, the lunar-based 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-based GNSS-R load design and performance verification.

[0038] According to the specific embodiments provided in the application, the application has the following technical effects:

[0039] The application provides a lunar-based GNSS-R signal simulation and DDM generation method based on a full-polarization layered scattering model, and has the following beneficial effects:

[0040] Clear physical mechanism: for the first time, the VRT theory is combined with the Z-V model to establish a complete physical chain from the microstructure of lunar soil to the macroscopic observation signal, and the interpretability of the model is improved.

[0041] High simulation accuracy: the layered nature, volume scattering, and multiple scattering effects of lunar soil are fully considered, and the limitation of traditional models that are only applicable to thin layers or smooth surfaces is overcome.

[0042] Supports full-polarization simulation: the DDM of various polarization combinations such as VR, HR, RR, and LR can be output, which helps to identify key substances such as water ice and rubble.

[0043] Strong applicability: signal responses under different frequencies (L1 / L2), different observation geometries, and different lunar soil parameters can be simulated, serving the pre-mission simulation and inversion algorithm training.

[0044] Great practical value: the generated DDM can be directly used for inversion research of parameters such as lunar soil thickness, density, and water ice content, and can also be used as a signal characteristic evaluation basis for scenarios such as lunar rover navigation and lander obstacle avoidance. BRIEF DESCRIPTION OF DRAWINGS

[0045] In order to more clearly illustrate the technical solutions in the embodiments of the application or the prior art, the following will briefly introduce the drawings needed in the embodiments. Obviously, the drawings in the following description only constitute some embodiments of the application, and for those skilled in the art, other drawings can also be obtained without creative labor on the basis of these drawings.

[0046] Figure 1 A flowchart of a lunar-based GNSS-R signal simulation and DDM generation method based on a full-polarization layered scattering model according to an embodiment of the application is shown. DETAILED DESCRIPTION

[0047] With reference to the drawings and embodiments of the present application, the technical solutions in the embodiments of the present application will be described clearly and completely. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all the embodiments of the present application. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative effort belong to the scope of protection of the present application.

[0048] The above-mentioned purposes, features and advantages of the present application will be more apparent and understandable, and the present application will be further described in detail below with reference to the drawings and specific embodiments.

[0049] In an exemplary embodiment, as shown in Figure 1 A lunar-based GNSS-R signal simulation and DDM generation method based on a full polarization layered scattering model is provided, which is executed by a computer device, specifically, can be executed by a terminal or a server, or both the terminal and the server, and includes the following steps S1 to S10. Wherein:

[0050] S1: Obtain lunar surface physical parameters, GNSS satellite orbit parameters and lunar-based receiver orbit parameters.

[0051] The lunar surface physical parameters include the dielectric constant, thickness, surface roughness, internal gravel particle characteristics and underlying bedrock parameters of the lunar surface weathering layer; the GNSS satellite orbit parameters include the position, velocity and antenna pattern information of the GNSS satellite transmitting source; and the lunar-based receiver orbit parameters include the position, velocity and receiving antenna pattern information of the lunar-based receiver.

[0052] S2: Based on the lunar surface physical parameters, a full polarization bistatic scattering coefficient model is established using the vector radiative transfer (VRT) theory, the surface scattering mechanism contribution of the vacuum-weathering layer interface, the subsurface scattering mechanism contribution of the weathering layer-bedrock interface, the volume scattering mechanism contribution caused by the buried particles in the weathering layer, and the subsurface-particle high-order multiple scattering term are calculated respectively, the polarization response characteristics of each scattering mechanism are represented in the form of Mueller matrix, and the total Mueller matrix of the entire lunar surface at any scattering point under the given incident angle and scattering angle conditions is obtained by coherently superimposing the Mueller matrices of all mechanisms.

[0053] Specifically, the above-mentioned method in the present application is divided into two stages:

[0054] The first stage is to construct a full polarization lunar surface bistatic scattering coefficient model based on the vector radiative transfer (VRT) theory. The model regards the lunar weathering layer as a multi-layer non-uniform medium, and comprehensively considers the following four scattering mechanisms:

[0055] Surface scattering: Occurred at the interface between vacuum and regolith (z=0, representing the lunar surface level), caused by surface roughness;

[0056] Subsurface scattering: Occurred at the interface between regolith and bedrock (z=-d, representing the depth of d centimeters below the lunar surface level), controlled by interface undulation and dielectric jump;

[0057] Volume scattering: Originated from the scattering of incident wave by randomly distributed inhomogeneities such as stones and pores within the regolith;

[0058] Multiple scattering: Contained high-order interactions between surface and subsurface, volume scattering and other interfaces.

[0059] Each mechanism expresses its polarization scattering characteristics in the form of Mueller matrix. The total Mueller matrix is obtained by matrix addition, and then the bistatic scattering coefficients under the combination of transmit polarization p and receive polarization q are derived according to the Stokes vector transformation formula, forming a spatially continuous scattering field.

[0060] The expression of the total Mueller matrix is as follows:

[0061] ;

[0062] wherein, the total Mueller matrix, the zenith and azimuth of the scattered wave, the zenith and azimuth of the incident wave, the surface scattering mechanism contribution of the vacuum-regolith interface, the subsurface scattering mechanism contribution of the regolith-bedrock interface, the volume scattering mechanism contribution of the buried particles within the regolith, the subsurface-particle high-order multiple scattering term.

[0063] S3: Based on the total Mueller matrix, the bistatic scattering coefficients corresponding to different transmit and receive polarization combinations are calculated using the Stokes vector transformation relationship, forming a spatially distributed scattering coefficient field.

[0064] The expression of the bistatic scattering coefficient is as follows:

[0065] ;

[0066] wherein, the bistatic scattering coefficient, the zenith and azimuth of the scattered wave, the zenith and azimuth of the incident wave, denotes an element in the total Mueller matrix.

[0067] The bistatic scattering coefficient in the embodiment is a full polarization form, supporting VR, HR, RR, and LR polarization combination outputs, for analyzing scattering differences of lunar surface materials under different polarization channels.

[0068] Second stage: Constructing a DDM generation method based on the Z-V model. The output of the first stage is used as the input of the second stage. As the core input parameter, combined with the actual orbit parameters of the GNSS satellite and the lunar base receiver, the following operations are performed:

[0069] Calculate the observation geometry to determine the range of the "flickering area";

[0070] Divide the flickering area into a spatial grid, and map the bistatic scattering coefficient to each grid point;

[0071] Calculate the corresponding signal delay τ and Doppler shift for each grid point;

[0072] Using the Z-V integral formula, integrate the scattering coefficient, GNSS code autocorrelation function, and Doppler power spectrum to generate the final delay Doppler map (DDM), and the detailed steps are as follows:

[0073] S4: Based on the GNSS satellite orbit parameters and the lunar base receiver orbit parameters, determine the observation geometry relationship between the GNSS satellite and the lunar base receiver.

[0074] S5: Based on the observation geometry relationship, calculate the area on the lunar surface that can contribute effectively to the received signal, i.e., the flickering area.

[0075] S6: Divide the flickering area into a number of two-dimensional spatial grid elements.

[0076] S7: Map the bistatic scattering coefficient to the spatial grid points in each two-dimensional spatial grid element, so that each spatial grid point has a corresponding scattering intensity and polarization property.

[0077] S8: For each spatial grid point, according to its geographical location, combined with the spatial positions and relative motion speeds of the GNSS satellite and the lunar base receiver, calculate the time delay and Doppler shift of the reflected signal relative to the direct signal generated by the spatial grid point.

[0078] S9: Take the time delay and Doppler shift as independent variables, call the autocorrelation function of the GNSS pseudo-random code and the Doppler power spectrum of the reflected signal, and take the bistatic scattering coefficient of the corresponding spatial grid point in S7 as the local scattering intensity factor, substitute it into the Z-V integral model, and perform integral operation to get the integral result.

[0079] The expression of the Z-V integral model is as follows:

[0080] ;

[0081] 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 lunar surface scattering point represents the distance from the lunar base receiver to the lunar surface 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 integration grid area.

[0082] ;

[0083] wherein, represents the difference of the Doppler shift; represents the time delay received by the lunar base receiver, represents the delay of the spatial grid point.

[0084] The expression of the reflected signal Doppler power spectrum is as follows:

[0085] ;

[0086] wherein, represents the difference of the Doppler shift; represents the Doppler shift of the lunar base receiver; represents the Doppler shift of the lunar surface spatial grid point.

[0087] S10: discretize the integration result into a two-dimensional matrix according to the time delay and the Doppler shift, generate a final delay Doppler map DDM, and complete the full-link physical simulation of the lunar GNSS-R signal.

[0088] 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: ​​​

[0089] Based on the final delay Doppler map DDM, the lunar soil thickness, water ice content, and rock abundance geological parameters are inversed and modeled, or used as simulation basis for the design and performance verification of lunar GNSS-R payloads.

[0090] Microwave remote sensing technology is an indispensable core means for deep space exploration, especially for lunar scientific research. Its importance mainly lies in its unique penetration, material identification, and all-weather and all-day working ability.

[0091] Firstly, microwave remote sensing has the ability to penetrate and detect the material of the lunar surface subsurface. 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, achieving "perspective" of the hidden geological structure under the surface layer. 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.

[0092] Secondly, this technology is one of the most effective methods for identifying and quantifying key material components. By analyzing the interaction between microwaves and materials (such as dielectric constant and scattering characteristics), we can effectively identify the composition and physical state of lunar surface materials. For example:

[0093] When applied to detecting water ice, the dielectric properties of water ice and lunar soil rock are significantly different. By analyzing the scattering intensity and polarization characteristics of microwave signals, we can infer the existence, distribution, and even purity of water ice in the permanent shadow crater, which is crucial for future lunar water resource utilization.

[0094] When applied to identifying rock abundance, surface and subsurface rocks are important geological units and landing risk sources. Microwave is very sensitive to rocks with a size similar to its wavelength, and its scattering signal can effectively invert the size, density, and distribution of rocks, providing scientific basis for lunar rover path planning and safe landing site selection.

[0095] Finally, microwave remote sensing is not limited by lighting conditions and can penetrate the extremely cold environment of the lunar night and possible dust interference for continuous observation, achieving truly all-weather and all-day continuous detection, which is a huge advantage that optical and infrared remote sensing cannot match.

[0096] 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 characteristics), but also a strategic direction for providing key technical support for future lunar base site selection, resource development and utilization, and long-term residence.

[0097] 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 of all, we need to clarify the key scientific basis:

[0098] 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 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, and the imaginary part is also large (loss is strong). Even if the water is frozen, the dielectric constant of the ice-lunar soil mixed medium will be significantly higher than that of dry lunar soil.

[0099] Scattering mechanism changes: Changes in 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 effects. Polarization characteristics (especially circular polarization RR / LR and circular linear polarization VR / HR) are very sensitive to surface roughness and subsurface non-uniformity (such as water ice clumps).

[0100] Among them, VR, HR, RR, LR represent the transmission polarization as RHCP, and the reception polarization as vertical (V), horizontal (H), RHCP and LHCP, respectively.

[0101] Based on the above, this application first constructs a full-polarization bistatic scattering coefficient model suitable for the structure of the lunar weathering layer based on the vector radiation transfer (VRT) theory, comprehensively considers the surface scattering, subsurface interface scattering, buried particle 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, taking the obtained scattering coefficient as the input parameter, combining the Zavorotny-Voronovich (Z-V) model, and under the known orbit geometry relationship between GNSS satellite and lunar base receiver, the delay and Doppler mapping of each spatial grid point in the fluctuation zone is carried out, and finally the high-fidelity DDM waveform is generated through integral operation. This application realizes the full-link forward modeling from the micro-physical scattering mechanism to the macro-observation data, has strong physical interpretability and high simulation accuracy, and can be used for lunar base GNSS-R task design, surface parameter inversion algorithm development and lunar resource exploration evaluation.

[0102] The technical features of the above embodiments can be combined in any way. 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, they should be considered as the scope of the description.

[0103] The principles and implementations of the present application are described in detail with specific examples in this paper, and the above examples are only used to help understand the method of the present application and its core idea; at the same time, for those skilled in the art, according to the idea of the present application, the specific implementation and application range will be changed. Therefore, 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-weathered 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 lunar surface. distance, Indicates the scattering point from the lunar-based receiver to the lunar surface. distance, Represents the scattering points on the lunar surface 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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