A method and apparatus for generating radar clutter signals based on scene simulation calculation.

Abstract

This invention discloses a radar clutter signal simulation method based on dynamic scene simulation, mainly addressing the problems of low computational efficiency and insufficient flexibility of traditional clutter simulation methods under conditions of large scenes, long time series, and multiple dynamic factors. The implementation scheme includes: constructing a digital simulation scene based on radar signal parameters and dynamic scene information to determine the clutter region to be simulated; discretizing the clutter region into a uniform basic grid in the range-azimuth plane, and then aggregating it into multiple independently processable clutter channels; calculating the amplitude, Doppler frequency, and phase parameters of the center point of each channel in parallel, constructing a two-dimensional convolution kernel reflecting spatial correlation, and using this convolution kernel to efficiently expand the center point parameters to the entire channel, generating a continuously distributed parameter field; and transmitting the parameter fields of each channel to a hardware logic unit to complete signal modulation and synthesis, outputting a high-fidelity radar clutter signal. This invention can achieve rapid, high-fidelity parameter generation from point to field, and significantly improves computational efficiency while strictly maintaining physical accuracy. It can be used for radar system simulation, electronic countermeasures testing, and radar performance evaluation.

Description

Technical Field

[0001] This invention relates to the field of radar signal processing technology, specifically to a method and system for generating radar clutter signals, which can be used for radar system simulation, electronic countermeasures testing, and radar performance evaluation. Background Technology

[0002] In radar system design, performance testing, and simulation evaluation, radar clutter simulation and generation is a crucial technology. Radar clutter refers to all useless echoes received by the radar, excluding the echoes from the target of interest. It is typically generated by scattering from natural background sources such as the ground, sea surface, and weather phenomena like rain and clouds. Realistic and efficient clutter simulation is of great value in verifying the radar's target detection, tracking, and identification capabilities in complex electromagnetic environments.

[0003] The essence of clutter signal simulation is to reconstruct the electromagnetic scattering characteristics of radar signals by distributed scatterers in the natural environment through mathematical modeling and algorithm simulation, and generate synthetic clutter data with specific statistical distribution, spatiotemporal correlation and physical authenticity.

[0004] Current mainstream methods can be divided into deterministic methods based on rigorous physical models and stochastic generation methods based on statistical models. Deterministic methods, such as unit scattering models based on electromagnetic calculations, can guarantee high physical accuracy, but their massive computational load results in extremely poor real-time performance, making them unsuitable for simulations of large-scale scenes and long time series. Statistical methods, such as stochastic process generation based on specific probability distributions and correlation functions, significantly improve generation speed by simplifying the model, but often struggle to accurately characterize the complex spatial correlations and time-varying non-stationary characteristics of clutter, resulting in limited fidelity. These two methods create an irreconcilable contradiction between accuracy and efficiency, making it difficult to meet the comprehensive requirements of modern radar systems for simulating complex dynamic clutter environments.

[0005] While existing technologies have proposed improvements to address the shortcomings of traditional methods, their flexibility and computational efficiency still face challenges when dealing with real-world non-uniform and dynamically changing scenarios.

[0006] Patent document CN120761985A discloses a method and apparatus for generating clutter. It treats the entire clutter scene as a collection of numerous discrete scattering units, synthesizing the final time-domain clutter signal by first calculating the frequency domain response of each unit, then convolving and superimposing these responses with the transmitted signal. This approach suffers from extremely high computational complexity due to the need to construct and convolve the transfer functions of a massive number of discrete scattering blocks one by one, making it difficult to meet the real-time or efficient simulation requirements of large-scale scenarios while maintaining physical accuracy.

[0007] Patent document CN121091227A discloses a method for modeling and suppressing small-sample non-uniform multimode clutter, which simulates the complex multimode clutter environment of shore-based radar through "range loop generation" and "multimode superposition". However, due to the assumption of "range loop", the implementation of this scheme is too simplified and therefore cannot accurately represent the complex spatial distribution and non-uniformity of scatterers in real-world scenarios.

[0008] In summary, existing technologies cannot balance simulation accuracy and efficiency, especially when simulating clutter signals with large scenes, long time series, and multiple dynamic factors, which presents significant challenges. Summary of the Invention

[0009] The purpose of this invention is to address the shortcomings of the prior art by proposing a method and apparatus for rapid generation of radar clutter based on convolutional modeling, which can effectively reduce computational complexity while maintaining the statistical characteristics and spatial correlation of clutter, and achieve efficient simulation of large-scale clutter scenarios.

[0010] The technical approach to achieving the objective of this invention is as follows: based on a rigorous physical model, information of the central unit of the clutter channel is extracted, convolution kernels corresponding to each channel are generated using parallel computing, and multi-channel clutter parameters are efficiently synthesized using convolution operations. Radar clutter signals are directly generated by mapping software modeling parameters to hardware logic devices.

[0011] Based on the above ideas, the technical solution of the present invention includes:

[0012] 1. A method for generating radar clutter signals based on scene simulation calculation, characterized in that it includes:

[0013] (1) Obtain the dynamic information of the radar, construct a digital demonstration scene including radar position, velocity and radar antenna parameters according to the ECEF coordinate system, and calculate the generation range and range unit of clutter signal according to the radar antenna parameters.

[0014] (2) The clutter region is divided using range cells to obtain the clutter center point location and topographic information of each block. Based on the location and topographic information, the parameter information of the clutter center point is calculated, including amplitude, Doppler frequency and phase.

[0015] (3) Convolution kernels representing amplitude and Doppler frequency are constructed based on the parameter information of the clutter center point; parameter information of all clutter regions is calculated through convolution operation and clutter signal is generated.

[0016] Furthermore, step (3) involves constructing convolution kernels representing amplitude and Doppler frequency based on the parameter information of the clutter center point, which includes:

[0017] 3a) Construct Gaussian convolution kernels :

[0018] 3b) Constructing the Gaussian correlation function :

[0019] 3c) Based on Gaussian convolution kernel Gaussian correlation function Obtain convolution kernels that characterize amplitude and Doppler frequency. :

[0020] .

[0021] Furthermore, in step (3), the parameter information of all clutter regions is calculated and clutter signals are generated through convolution operations, which includes:

[0022] 3d) Based on the convolution kernel Calculate the clutter amplitude across the entire region :

[0023] 3e) Based on the convolution kernel Calculate the Doppler frequency of the entire region :

[0024] 3f) Based on clutter center point phase Calculate the phase of the entire region :

[0025] 3g) The amplitude, Doppler frequency, and phase parameters are input into the hardware logic device to generate radar clutter signals.

[0026] 2. A radar clutter signal generation device based on scene simulation calculation, characterized in that it comprises:

[0027] The scene initialization module is used to construct a digital demonstration scene that includes radar position, velocity, and radar antenna parameters;

[0028] The clutter region generation module is used to determine the clutter region to be simulated based on the digital scene.

[0029] The channel division module is used to calculate the range cell using radar parameter information and to divide the clutter region into multiple independent clutter processing channels using the range cell.

[0030] The parallel parameter generation module is used to generate the amplitude, Doppler frequency, and phase parameters for the entire clutter region.

[0031] The clutter signal generation module is used to input the amplitude, Doppler frequency, and phase parameters of the entire clutter region into the hardware logic device to generate radar clutter signals.

[0032] Compared with the prior art, the present invention has the following advantages:

[0033] Firstly, because the present invention strictly calculates the amplitude, Doppler frequency and phase of the center point of each clutter channel according to the electromagnetic physical model in the calculation process, it can ensure that the core physical characteristics of the generated clutter unit are accurate and real. Compared with the traditional statistical modeling method, it significantly improves the physical accuracy of clutter simulation and the ability to characterize non-stationary characteristics and spatial correlation.

[0034] Secondly, this invention uses a two-dimensional convolution kernel based on physical meaning to rapidly expand the center point parameters in space, and uses the clutter channel as the basic unit of parallel processing. Therefore, while ensuring high physical fidelity, it can improve the computational efficiency of clutter generation by leveraging the inherent parallelism of convolution operations and the block parallel architecture, effectively supporting the simulation requirements under large-scale and long-term conditions. Attached Figure Description

[0035] Figure 1 This is a flowchart illustrating the implementation of the radar clutter signal generation method based on scene simulation calculation of the present invention.

[0036] Figure 2 This is a block diagram of the radar clutter signal generation device based on scene simulation calculation according to the present invention. Detailed Implementation

[0037] The embodiments of the present invention will be described in detail below with reference to the accompanying drawings.

[0038] Example 1: Radar clutter signal generation method based on scene simulation calculation.

[0039] Referring to Figure 1, the implementation steps of this example include the following:

[0040] Step 1: Construct a digital demonstration scenario.

[0041] 1.1) Obtain radar dynamic information files, that is, construct radar dynamic information files including radar position, velocity and antenna parameters based on the actual radar configuration parameters;

[0042] 1.2) Parse the radar dynamic information file:

[0043] The radar dynamic information file is stored in the preset system input directory. After the clutter signal simulation software is started, it reads the data file from the system input directory and parses its contents to extract the radar's original position, velocity and antenna parameters.

[0044] 1.3) Transform the parameters from the originally defined coordinate system to the unified ECEF coordinate system:

[0045] For the initial position of the radar defined in the geographic coordinate system, the radar's LLA coordinates are converted to ECEF coordinates according to the WGS84 Earth ellipsoid model.

[0046] For radar velocity and antenna parameters defined in the body axis coordinate system, the vectors in the body axis are first transformed to the local horizontal coordinate system. After obtaining the vectors in the local horizontal coordinate system, they are then transformed to the ECEF coordinate system through a rotation matrix.

[0047] 1.4) Constructing digital demonstration scenarios:

[0048] Based on the radar's initial position and maximum detection range in the ECEF coordinate system, define the spatial bounding box of the scene;

[0049] Based on the radar's velocity vector under ECEF, a kinematic model of the radar is established within the scene simulation time, generating a trajectory sequence of its position changing over time.

[0050] Based on the antenna pointing vector and beamwidth under ECEF, combined with the radar operating mode, the beam center axis equation is established to complete the construction of the digital demonstration scenario.

[0051] Step 2: Determine the clutter generation region.

[0052] 2.1) Calculate the nearest slant range corresponding to the beam projection onto the scene. With the farthest slope distance :

[0053] During the simulation, the stored radar position and radar antenna pointing are the results at the current moment. Based on the current results, the nearest slant range corresponding to the beam projection on the scene is calculated using the following formula. With the farthest slope distance :

[0054] ,

[0055] ,

[0056] Where h represents the radar altitude, and These represent the elevation angles at the near and far ends of the beam, respectively.

[0057] 2.2) Based on the nearest slope distance With the farthest slope distance Calculate the coordinates of the perigee separately. Coordinates of the apogee :

[0058] ,

[0059] ,

[0060] The coordinates of the radar vertical point, This is the normalized direction vector pointing from the radar vertical point to the beam center.

[0061] 2.3) Using the coordinates of the perigee Coordinates of the apogee The spatial line connecting the two points is the center line. Based on the azimuth beamwidth of the radar antenna, the beamwidth is extended by half to both sides of the center line to obtain the clutter generation area.

[0062] Step 3: Determine the clutter channel.

[0063] To address the low simulation efficiency in large-scale clutter regions, it is necessary to divide the clutter region into multiple clutter channels and utilize their independence for parallel computation, thereby significantly improving the simulation speed. The implementation is as follows:

[0064] 3.1) Calculate the range unit based on the radar signal bandwidth B. :

[0065] Where C is the speed of light;

[0066] 3.2) Using a side length of A standard square grid is used to fully cover the identified clutter region:

[0067] 3.2.1) In the ECEF coordinate system, the lower left corner of the clutter rectangular region is defined as the origin of the clutter region;

[0068] 3.2.2) Based on the coordinates of the perigee Coordinates of the apogee Calculate the total length of the clutter region in the range direction. :

[0069] ;

[0070] 3.2.3) Based on the nearest slope distance Farthest slant distance And the azimuth beamwidth of the radar antenna Calculate the total length of the clutter region in the azimuth direction. :

[0071] ;

[0072] 3.2.4) Based on the total length of the clutter region in the range direction and distance unit Calculate the number of grids that can be divided along the distance. :

[0073] ;

[0074] 3.2.5) Based on the total length of the clutter region in the range direction and distance unit Calculate the number of grids that can be divided in the azimuth direction. :

[0075] ;

[0076] 3.2.6) Discretize the entire region into an M×N basic square grid, where each basic element is called a basic scattering element;

[0077] 3.3) Divide clutter channels:

[0078] Define the aggregation parameter as k, which takes an odd value. Starting from the origin of the clutter region, slide a k × k window across the base mesh without overlap to divide the entire region into P × Q independent clutter processing channels. The index of the center point of each clutter channel is... ;

[0079] For regions whose edges are not divisible by k, zero padding is used to ensure that all channels are the same size.

[0080] Step 4: Calculate the amplitude at the center point of the clutter channel.

[0081] 4.1) Based on the coordinates of perigee Distance unit Index of clutter center point Calculate the coordinates of the clutter center point and clutter channel reflection area :

[0082] ,

[0083] ,

[0084] 4.2) Based on radar location information and clutter reach center point coordinates Calculate the distance between the radar and the clutter center point. :

[0085] ;

[0086] 4.3) Based on the aircraft heading angle Flight path angle ; Calculate the near-ground grazing angle between the radar and the clutter area. Scrubbing the corner of the ground at the far point :

[0087]

[0088] 4.4) Based on the terrain type and grazing angle at the center point of the clutter channel, query the preset reflection coefficient database to obtain the mean square value of the reflection coefficient under this condition. ;

[0089] 4.5) Calculate the reflection coefficient based on the mean square value of the reflection coefficient. :

[0090] ,

[0091] in, It is a function of the normal distribution;

[0092] 4.6) Based on the reflection coefficient clutter channel reflection area and the distance between the radar and the center point of the clutter area Calculate the amplitude at the clutter center point

[0093] ;

[0094] in, It is the beam gain of the transmitted signal. It is the beam gain of the receiving radar. This refers to the operating wavelength of the radar.

[0095] Step 5: Calculate the Doppler frequency at the center point of the clutter channel.

[0096] 5.1) Based on the terrain type and grazing angle at the center point of the clutter channel, query the preset clutter motion parameter database to obtain the base velocity under this condition. Speed ​​expansion Basic direction of motion ;

[0097] 5.2) Based on the base speed Speed ​​expansion Basic direction of motion Calculate the magnitude of the random motion velocity of the clutter scattering points respectively. and random motion velocity unit component :

[0098] ,

[0099] ,

[0100] in, It is a function of the normal distribution;

[0101] 5.3) Based on the magnitude of the random motion velocity of the clutter scattering point and random motion velocity unit component Calculate the Doppler frequency of the clutter scattering point. :

[0102] ;

[0103] in, This is the angle-to-radian conversion factor. At the speed of light, For radar carrier frequency;

[0104] 5.4) Based on the radar's basic parameter information and the Doppler frequency of the clutter scattering point Calculate the Doppler at the clutter center point :

[0105] ,

[0106] in, This is the normalized direction vector from the emission source to the observation point. This refers to the operating wavelength of the radar.

[0107] Step 6: Calculate the phase of the clutter channel center point.

[0108] 6.1) Based on the terrain type and grazing angle at the center point of the clutter channel, query the preset phase number database to obtain the mean square value of the phase under this condition. ;

[0109] 6.2) Based on the mean square value of the phase Calculate the phase of the scattering point :

[0110] ,

[0111] in, It is a uniform distribution of 0-1. It is the standard normal distribution function;

[0112] 6.3) Based on the phase of the scattering point Calculate the phase at the clutter center point :

[0113] ,

[0114] in, Represents the speed of light. Represents the radar radio frequency. This represents the initial phase of the radar.

[0115] Step 7: Calculate the convolution kernel for the clutter channel.

[0116] To deduce the parameter distribution covering the entire channel region from the calculated clutter channel center point parameters, a two-dimensional convolution kernel needs to be constructed for the channel. This two-dimensional convolution kernel is then used to convolve and spread the center point parameters, thereby generating the parameter information of the entire channel quickly and with high fidelity. The implementation includes:

[0117] 7.1) Construct Gaussian convolution kernels :

[0118] 7.1.1) Based on distance unit Calculate the relevant parameters of the distance dimension. :

[0119] ,

[0120] in, It is a dimensionless empirical coefficient, determined by querying a pre-set lookup table of geomorphological information;

[0121] 7.1.2) Based on the azimuth beamwidth of the radar antenna Calculate the relevant parameters of the directional dimension. :

[0122] ,

[0123] in, It is a dimensionless empirical coefficient, determined by querying a pre-set lookup table of geomorphological information;

[0124] 7.1.3) Based on the relevant parameters of the distance dimension Related parameters of direction dimension Calculate the Gaussian convolution kernel

[0125] ,

[0126] 7.2) Constructing the Gaussian correlation function :

[0127] ,

[0128] in, Represents the location of the central area;

[0129] 7.3) Based on Gaussian convolution kernel Gaussian correlation function Obtain convolution kernels that characterize amplitude and Doppler frequency. :

[0130] .

[0131] Step 8: Calculate the parameter information of the clutter channel.

[0132] 8.1) Based on the amplitude of the clutter channel center and convolution kernel Calculate the clutter amplitude in the clutter channel. :

[0133] ,

[0134] in, It is a Gaussian random noise with zero mean;

[0135] 8.2) Based on the Doppler frequency at the center of the clutter channel and convolution kernel Calculate the Doppler frequency of the clutter channel. :

[0136] ,

[0137] in, It is a Gaussian random noise with zero mean;

[0138] 8.3) Based on clutter center point phase Calculate clutter channel phase :

[0139] ,

[0140] in, This represents a Gaussian random noise with a mean of zero.

[0141] Step nine: Generate radar clutter signals.

[0142] 9.1) The parameter information of the entire clutter region is input into the designed hardware logic device. The hardware logic device summarizes the parameter information of each channel to obtain the clutter amplitude of the entire clutter region. Doppler frequency phase ;

[0143] 9.2) Generate white noise signal:

[0144] To simulate the inherent random fluctuation components in clutter, a baseband complex Gaussian white noise signal is first generated by summing and normalizing multiple independent uniformly distributed random sequences based on the central limit theorem. ;

[0145] ,

[0146] in, These are M independent random numbers that are uniformly distributed in the interval [0,1).

[0147] 9.3) Perform frequency domain Doppler modulation:

[0148] To simulate the average Doppler frequency shift caused by the relative motion of clutter cells, the baseband noise is spectral shifted based on the Doppler frequency of the clutter region. and baseband complex Gaussian white noise signal Calculate the result after frequency domain Doppler modulation :

[0149] ;

[0150] 9.4) Perform time-domain amplitude shaping:

[0151] To simulate the spatial correlation and specific distribution of clutter amplitudes, amplitude shaping is performed on the signal based on the amplitude of the clutter region. Results after frequency domain Doppler modulation Calculate the results after amplitude shaping :

[0152] ,

[0153] 9.5) Phase perturbation and fine-tuning:

[0154] To precisely control the phase characteristics and fine spectral structure of the synthesized signal, spatially varied phase modulation is introduced, based on the phase of the clutter region. and the result after amplitude shaping Calculate the result after phase modulation :

[0155] ,

[0156] Should That is, a synthesized clutter signal that meets the preset Doppler, amplitude, and phase characteristics.

[0157] It should be noted that the step numbers in the specification and claims of this invention are only for the purpose of clearly describing the embodiments of this invention and facilitating understanding, and their order is not limited.

[0158] Example 2: Radar Clutter Signal Generation Device Based on Scene Simulation Calculation

[0159] Reference Figure 2 This example includes a scene initialization module 1, a clutter region generation module 2, a channel partitioning module 3, a parallel parameter generation module 4, and a clutter signal generation module 5. The parallel parameter generation module 4 includes a clutter amplitude generation submodule 41, a clutter Doppler frequency generation submodule 42, a clutter phase generation submodule 43, and a clutter parameter summarization submodule 44. The working principle of the entire device is as follows:

[0160] The scenario initialization module 1 is used to read and parse the radar dynamic information file from the system input directory, construct a digital demonstration scenario based on the radar position, velocity, and radar antenna parameters, and then transmit the digital simulation scenario to the clutter area generation module 2.

[0161] The clutter region generation module 2 is used to determine the clutter space region to be simulated through geometric calculation based on the radar position, antenna pointing and beamwidth parameters in the digital simulation scenario, and to transmit the clutter region to be simulated to the channel division module 3.

[0162] The channel partitioning module 3 is used to process the clutter region to be simulated. It discretizes the clutter region to be simulated into basic scattering units according to the distance unit, and aggregates multiple basic scattering units into independent clutter processing channels. Then, it transmits the partitioned multiple independent clutter processing channels to the parallel parameter generation module 4.

[0163] The parallel parameter generation module 4 is used to perform parallel calculations for each channel, and its internal sub-modules work collaboratively, wherein:

[0164] The clutter amplitude generation submodule 41 is used to calculate the amplitude value at the center point of the channel and construct the corresponding two-dimensional convolution kernel. It generates amplitude parameters covering the entire channel through convolution operation and inputs the calculation results into the clutter parameter aggregation submodule 44.

[0165] The clutter Doppler frequency generation submodule 42 is used to calculate the Doppler frequency value at the center point of the channel and construct the corresponding two-dimensional convolution kernel. It generates Doppler frequency parameters covering the entire channel through convolution operation and inputs the calculation results into the clutter parameter aggregation submodule 44.

[0166] The clutter phase generation submodule 43 is used to calculate the phase value at the center point of the channel, combine it with a Gaussian random perturbation field with zero mean, generate phase parameters covering the entire channel, and input the calculation results into the clutter parameter aggregation submodule 44.

[0167] The clutter parameter aggregation submodule 44 is used to aggregate the calculation results of the above three submodules by channel to obtain the amplitude, Doppler frequency and phase information of the entire clutter region, and transmit the amplitude, Doppler frequency and phase information of the entire clutter region to the clutter signal generation module 5.

[0168] The clutter signal generation module 5 is used to generate high-fidelity radar clutter signals from the amplitude, Doppler frequency, and phase parameters of the entire clutter region using hardware logic devices.

[0169] It should be noted that the scene initialization module 1, clutter region generation module 2, channel division module 3, and parallel parameter generation module 4, along with their internal submodules, are implemented in software. The clutter signal generation module 5 is implemented in hardware. When implemented in software, all components can be implemented as program instruction products. A program instruction product includes a set of program instructions. The process is generated when the program instructions are loaded and executed on a computer. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The program instructions can be stored in a computer-readable and writable storage medium or transferred from one computer's readable and writable storage medium to another.

[0170] In this embodiment, the direct coupling or communication connection between the modules can be indirectly achieved through intermediate interfaces such as application programming interfaces (APIs), hardware buses, or communication protocols. The functional modules and sub-modules in this embodiment can dynamically reside within a single processing unit, or each module can exist physically independently, or two or more modules can dynamically reside within a single processing unit. When these dynamic components are implemented as software functional modules and sold or used as independent products, they can also be stored in a computer-readable and writable storage medium. This storage medium can be a memory, disk, or optical disc, etc.

[0171] The above description is merely a specific example of the present invention and does not constitute any limitation on the present invention. Obviously, those skilled in the art, after understanding the content and principles of the present invention, may make various modifications and changes in form and detail without departing from the principles and structure of the present invention. For example, in addition to the Gaussian function used in this example, the convolution kernel function can also adopt other kernel functions that conform to the spatial statistical characteristics of clutter, such as exponential kernel functions, power-law kernel functions, or empirical kernel functions based on measured data fitting, while retaining its core function of representing spatial correlation and performing weighted expansion. Furthermore, in this example, the correlation length parameters of the range and azimuth dimensions in the convolution kernel can be obtained by looking up tables based on radar system parameters and terrain type, or can be dynamically calculated based on real-time environmental data, or an adaptive algorithm can be used for iterative optimization based on adjacent channel parameters. However, these modifications and changes based on the ideas of the present invention are still within the scope of protection of the claims of the present invention.

Claims

1. A method for generating radar clutter signals based on scene simulation calculation, characterized in that, include: (1) Obtain the dynamic information of the radar, construct a digital demonstration scene including radar position, velocity and radar antenna parameters according to the ECEF coordinate system, and calculate the generation range and range unit of clutter signal according to the radar antenna parameters. (2) The clutter region is divided using range cells to obtain the clutter center point location and topographic information of each block. Based on the location and topographic information, the parameter information of the clutter center point is calculated, including amplitude, Doppler frequency and phase. (3) Convolution kernels representing amplitude and Doppler frequency are constructed based on the parameter information of the clutter center point; parameter information of all clutter regions is calculated through convolution operation and clutter signal is generated.

2. The method according to claim 1, characterized in that, The digital demonstration scenario constructed according to the ECEF coordinate system in (1) includes radar position, velocity, and radar antenna parameters, and its implementation includes: 1a) The dynamic information of the radar is transmitted into the clutter signal simulation software in the form of a file for analysis to obtain the original position, velocity and antenna parameters of the radar, and these parameters are transformed from the original coordinate system to the unified ECEF coordinate system. 1b) Based on the transformed radar position, define the three-dimensional spatial range of the digital demonstration scene in the ECEF coordinate system, and based on the radar speed, antenna pointing and radar working mode, initialize the platform motion state and beam illumination geometry of the radar in the digital demonstration scene to complete the construction of the digital demonstration scene.

3. The method according to claim 1, characterized in that, The calculation of the clutter signal generation range and range unit based on the radar antenna parameters in (1) includes the following: 1c) Based on the current pointing of the radar antenna, calculate the nearest slant range corresponding to the beam projection in the scene. With the farthest slope distance : ， ， Where h represents the radar altitude, and These represent the elevation angles at the near and far ends of the beam, respectively. 1d) Based on the nearest slant distance With the farthest slope distance Calculate the perigee Coordinates of the apogee : ， ， in, The coordinates of the radar vertical point, This is the normalized direction vector pointing from the radar vertical point to the beam center. 1e) Using the coordinates of the perigee Coordinates of the apogee The spatial line between them is the center line. Based on the azimuth beamwidth of the radar antenna, the beamwidth is extended by half to both sides of the center line to determine the coverage range of the clutter area in the azimuth direction. 1f) Calculate the range unit based on the radar signal bandwidth B. : ， Where C is the speed of light.

4. The method according to claim 1, characterized in that, The calculation of the clutter center point amplitude based on the clutter center point location and topographic information of each block in (2) includes the following implementation: 2a) Based on the aircraft heading angle Flight path angle ; Calculate the near-ground grazing angle between the radar and the clutter area. Scrubbing the corner of the ground at the far point : ； 2b) Find the mean square value of the reflection coefficient based on the terrain and rubbing angle information. ; 2c) Calculate the reflection coefficient based on the mean square value of the reflection coefficient. : ， in, It is a function of the normal distribution; 2d) Based on perigee coordinates Distance unit Index of clutter center point Calculate the coordinates of the clutter center point and clutter channel reflection area : ， ， 2e) Based on radar location information and clutter channel center point coordinates Calculate the distance norm between the radar and the clutter center point: ； 2f) Based on the reflection coefficient The distance norm between the radar and the clutter center point is used to calculate the amplitude at the clutter center point. , ； in, It is the beam gain of the transmitted signal. It is the beam gain of the receiving radar. This refers to the operating wavelength of the radar.

5. The method according to claim 1, characterized in that, The calculation of the Doppler frequency of the clutter center point based on the clutter center point location and topographic information of each block in (2) includes the following: 2g) Based on terrain and rubbing angle information, find the base speed. Speed ​​expansion Basic direction of motion ; 2h) Based on the base speed Speed ​​expansion Basic direction of motion Calculate the magnitude of the random motion velocity of the clutter scattering points respectively. and random motion velocity unit component : ， ， in It is a function of the normal distribution; 2i) Based on the magnitude of the random motion velocity of the clutter scattering point and random motion velocity unit component Calculate the Doppler frequency of the clutter scattering point. : ， in, This is the angle-to-radian conversion factor. At the speed of light, For radar carrier frequency; 2j) Based on the radar's basic parameter information and the Doppler frequency of the clutter scattering point Calculate the Doppler at the clutter center point : ； in, This is the normalized direction vector from the emission source to the observation point. This refers to the operating wavelength of the radar.

6. The method according to claim 1, characterized in that, The calculation of the clutter center point phase based on the clutter center point location and topographic information of each block in (2) includes the following implementation: 2k) Find the phase mean square value based on terrain and grazing angle information. ; 2l) According to the mean square value of the phase Calculate the phase of the scattering point : ； in, It is a uniform distribution of 0-1. It is the standard normal distribution function; 2m) Based on the phase of the scattering point Calculate the phase at the clutter center point : ； in, Represents the speed of light. Represents the radar radio frequency. This represents the initial phase of the radar.

7. The method according to claim 1, characterized in that, The step (3) involves constructing convolution kernels representing amplitude and Doppler frequency based on the parameter information of the clutter center point. Its implementation includes: 3a) Construct Gaussian convolution kernels : ， in, Represents the relevant length parameter of the distance dimension. The length parameters represent the orientation dimension, and x and y represent the coordinate indices inside the convolution kernel. 3b) Constructing the Gaussian correlation function : ， in, Represents the location of the central area; 3c) Based on Gaussian convolution kernel Gaussian correlation function Obtain convolution kernels that characterize amplitude and Doppler frequency. : 。 8. The method according to claim 1, characterized in that, In step (3), parameter information for all clutter regions is calculated and clutter signals are generated through convolution operations, including: 3d) Based on the convolution kernel Calculate the clutter amplitude across the entire region : ， in, Represents the magnitude of the central area. This represents a Gaussian random noise with a mean of zero. 3e) Based on the convolution kernel Calculate the Doppler frequency of the entire region : ， in, The magnitude of the Doppler frequency in the central region, This represents a Gaussian random noise with a mean of zero. 3f) Based on clutter center point phase Calculate the phase of the entire region : ， in, This represents a Gaussian random noise with a mean of zero. 3g) The amplitude, Doppler frequency, and phase parameters are input into the hardware logic device to generate radar clutter signals.

9. A radar clutter signal generation device based on scene simulation calculation, characterized in that, include: The scene initialization module is used to construct a digital demonstration scene that includes radar position, velocity, and radar antenna parameters; The clutter region generation module is used to determine the clutter region to be simulated based on the digital scene. The channel division module is used to calculate the range cell using radar parameter information and to divide the clutter region into multiple independent clutter processing channels using the range cell. The parallel parameter generation module is used to generate the amplitude, Doppler frequency, and phase parameters for the entire clutter region. The clutter signal generation module is used to input the amplitude, Doppler frequency, and phase parameters of the entire clutter region into the hardware logic device to generate radar clutter signals.

10. The system according to claim 9, characterized in that, The parallel parameter generation module includes: The clutter amplitude generation submodule is used to calculate the amplitude and two-dimensional convolution kernel at the center point of each clutter processing channel, and generate the amplitude parameters of the channel based on the amplitude and two-dimensional convolution kernel at the center point of the channel. The clutter Doppler frequency generation submodule is used to calculate the Doppler frequency and two-dimensional convolution kernel at the center point of each clutter processing channel, and generate the Doppler frequency parameters of the channel based on the Doppler frequency and two-dimensional convolution kernel at the center point of the channel. The clutter phase generation submodule is used to calculate the phase of the center point of each clutter processing channel, and generate the phase parameters of the channel based on the phase of the center point of the channel and a Gaussian random noise with a mean of zero. The clutter parameter aggregation submodule is used to aggregate the parameters generated by each clutter channel submodule to obtain parameter information for the entire clutter region.

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