Method and apparatus for determining electromagnetic scattering data of a test object

Abstract

The application discloses a kind of electromagnetic scattering data determination method and device of test target, belong to target electromagnetic scattering characteristic test field.The method comprises: constructing semi-empirical model of test target;First scattering geometric parameter known to test target and electromagnetic scattering characteristic data corresponding to first scattering geometric parameter are input into semi-empirical model, and the model parameter of semi-empirical model is obtained;Second scattering geometric parameter known to test target is input into semi-empirical model with determined model parameter, and the electromagnetic scattering characteristic data corresponding to second scattering geometric parameter is obtained;Wherein, the bistatic angle corresponding to second scattering geometric parameter is greater than the bistatic angle corresponding to first scattering geometric parameter.The present application can improve the accuracy and reliability of large bistatic angle test on rough ground (such as land, cement ground).

Description

Technical Field

[0001] This invention relates to the field of target electromagnetic scattering characteristic testing technology, and in particular to a method and apparatus for determining electromagnetic scattering data of a test target. Background Technology

[0002] In the testing of electromagnetic scattering characteristics of the horizontal field, the ground reflection path and the direct signal are coherently superimposed. In traditional methods, the ground is usually regarded as an ideal reflecting surface for strong scattering targets. However, the scattering characteristics of actual rough ground (such as soil and concrete) are complex, especially for weak scattering targets, where the measurement error caused by ground reflection has a significant impact.

[0003] Currently, most indoor testing in China involves targets with small bistatic angles. This is because when the bistatic angle becomes large enough, energy from the transmitting antenna leaks into the receiving antenna, overwhelming the actual received signal. In post-processing, software range gates are commonly used to eliminate clutter. However, due to the close antenna distance, range gates cannot effectively eliminate direct leakage from the transmitting antenna. Therefore, only measurements taken at small bistatic angles are accurate. Thus, there is an urgent need for a method and apparatus for determining the electromagnetic scattering data of the test target. Summary of the Invention

[0004] This invention provides a method and apparatus for determining electromagnetic scattering data of a test target. This method improves the accuracy and reliability of data measurement for targets with large bistatic angles. The technical solution is as follows:

[0005] On one hand, the present invention provides a method for determining electromagnetic scattering data of a test target, comprising:

[0006] Construct a semi-empirical model of the test target;

[0007] The known first scattering geometric parameters of the test target and the electromagnetic scattering characteristic data corresponding to the first scattering geometric parameters are input into the semi-empirical model to obtain the model parameters of the semi-empirical model.

[0008] The known second scattering geometric parameters of the test target are input into a semi-empirical model with determined model parameters to obtain electromagnetic scattering characteristic data corresponding to the second scattering geometric parameters; wherein the bistatic angle corresponding to the second scattering geometric parameters is greater than the bistatic angle corresponding to the first scattering geometric parameters.

[0009] Optionally, the semi-empirical model is determined by the following formula:

[0010]

[0011] Where, k b To test the specular reflection component of the incident wave on the target surface, kr To test the diffuse reflection component of the incident wave on the target surface, k d To test the power spectral components of the target surface, θ i ′, θ s ′, These are the incident angle, incident azimuth angle, scattering angle, and scattering azimuth angle, respectively. The scattering geometric parameters include the incident angle, incident azimuth angle, scattering angle, and scattering azimuth angle. This represents the electromagnetic scattering characteristics under the given scattering geometry parameters. Let k be the masking function. b k r k d a and b are both parameters of the model. For the coupling term of specular reflection and diffuse reflection, exp[b(1-cosγ] a ] is an approximate description of the Fresnel reflection function, a is the roughness component of the target surface at the incident wave frequency, and b is the dielectric property component of the target surface.

[0012] Optionally, the known first scattering geometric parameters of the test target and the electromagnetic scattering characteristic data corresponding to the first scattering geometric parameters are input into the semi-empirical model to obtain the model parameters of the semi-empirical model, including:

[0013] The first scattering geometric parameter and the electromagnetic scattering characteristic data corresponding to the first scattering geometric parameter are input into the semi-empirical model, and the model parameters are obtained by solving the model through a genetic algorithm.

[0014] The bistatic angle corresponding to the first scattering geometry parameter ranges from 0° to 60°.

[0015] Optionally, the objective function used in the genetic algorithm is obtained by the following method:

[0016] Determine the environmental parameters when obtaining the electromagnetic scattering characteristic data under the first scattering geometric parameters;

[0017] The scattering coefficient of the test target under the first scattering geometry parameter and the environmental parameter is calculated using the full-wave numerical method;

[0018] The target function value is obtained based on the scattering coefficient and the electromagnetic scattering characteristic data under the first scattering geometric parameters; the target function is determined by the following formula:

[0019]

[0020] Where F is the objective function value, σ s (i) is the scattering coefficient, f r(i) represents the electromagnetic scattering characteristic data under the given scattering geometry parameters, where i is the first scattering geometry parameter, Q is the total number of first scattering geometry parameters of the test target, and θ i The angle of incidence is denoted as .

[0021] Optionally, the known second scattering geometric parameters of the test target are input into a semi-empirical model with determined model parameters to obtain electromagnetic scattering characteristic data corresponding to the second scattering geometric parameters, including:

[0022] The second scattering geometric parameters of the test target are substituted into the semi-empirical model with the determined model parameters to calculate the electromagnetic scattering characteristics data under the second scattering geometric parameters; wherein the bistatic angle range corresponding to the second scattering geometric parameters is 60° to 130°.

[0023] Optionally, after the semi-empirical model with determined model parameters, and before obtaining the electromagnetic scattering characteristic data corresponding to the second scattering geometry parameters, the method further includes:

[0024] Based on the first scattering geometric parameters of the test target and the semi-empirical model with the determined model parameters, the simulated electromagnetic scattering characteristic data under the first scattering geometric parameters are calculated.

[0025] The simulated electromagnetic scattering characteristic data and the electromagnetic scattering characteristic data corresponding to the first scattering geometric parameters are compared to obtain the verification result; wherein, when the verification result is that the verification is passed, the electromagnetic scattering characteristic data corresponding to the second scattering geometric parameters is calculated according to the semi-empirical model with the determined model parameters.

[0026] On the other hand, an apparatus for determining electromagnetic scattering data of a test target is provided, the apparatus comprising:

[0027] Builder modules are used to build semi-empirical models of the test targets;

[0028] The extraction module inputs the known first scattering geometric parameters of the test target and the electromagnetic scattering characteristic data corresponding to the first scattering geometric parameters into the semi-empirical model to obtain the model parameters of the semi-empirical model;

[0029] The calculation module inputs the known second scattering geometric parameters of the test target into a semi-empirical model with determined model parameters to obtain electromagnetic scattering characteristic data corresponding to the second scattering geometric parameters; wherein the bistatic angle corresponding to the second scattering geometric parameters is greater than the bistatic angle corresponding to the first scattering geometric parameters.

[0030] On the other hand, the present invention provides a computer device including a memory and a processor, the memory being used to store a computer program, and the processor being used to execute the computer program stored in the memory to implement the target scattering data testing method with large bistatic angle as described above.

[0031] On the other hand, the present invention provides a computer-readable storage medium storing a computer program that, when executed by a processor, causes the computer to perform the electromagnetic scattering data determination method for the test target described in any of the preceding claims.

[0032] On the other hand, the present invention provides a computer program product, including a computer program that, when executed by a processor, implements the method for determining electromagnetic scattering data of the test target described in any of the preceding claims.

[0033] This invention provides a method and apparatus for determining electromagnetic scattering data of a test target. The method constructs a semi-empirical model of the target, then obtains model parameters based on precise data at small bistatic angles to determine the target model. Finally, electromagnetic scattering characteristic data at large bistatic angles are obtained through model inversion. Thus, this invention effectively overcomes the problem in traditional testing methods where, when the bistatic angle is large enough, the transmitting antenna energy leaks into the receiving antenna, drowning out the actual received signal. This significantly improves the accuracy and reliability of large bistatic angle testing on rough surfaces (such as soil and concrete). Attached Figure Description

[0034] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0035] Figure 1 This is a flowchart of a method for determining electromagnetic scattering data of a test target according to an embodiment of the present invention;

[0036] Figure 2 This is a comparison chart of simulated and measured bi-station angle data provided in an embodiment of the present invention;

[0037] Figure 3 This is a hardware architecture diagram of a computer device provided in an embodiment of the present invention;

[0038] Figure 4 This is a structural diagram of an electromagnetic scattering data determination device for a test target provided in an embodiment of the present invention. Detailed Implementation

[0039] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are some embodiments of the present invention, but not all embodiments. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without creative effort are within the scope of protection of the present invention.

[0040] The following describes the specific implementation of the above concept.

[0041] Please refer to Figure 1 The present invention provides a method for determining electromagnetic scattering data of a test target, the method comprising:

[0042] Step 100: Construct a semi-empirical model of the test target;

[0043] Step 102: Input the known first scattering geometric parameters of the test target and the electromagnetic scattering characteristic data corresponding to the first scattering geometric parameters into the semi-empirical model to obtain the model parameters of the semi-empirical model;

[0044] Step 104: Input the known second scattering geometric parameters of the test target into the semi-empirical model with determined model parameters to obtain electromagnetic scattering characteristic data corresponding to the second scattering geometric parameters; wherein, the bistatic angle corresponding to the second scattering geometric parameters is greater than the bistatic angle corresponding to the first scattering geometric parameters.

[0045] In this invention, a semi-empirical model of the test target is first constructed. Then, model parameters are obtained based on precise data of small bistatic angles to determine the target model. Finally, electromagnetic scattering characteristic data under large bistatic angles are obtained through inversion of the target model. Thus, this invention effectively overcomes the problem in traditional testing methods where, when the bistatic angle is large enough, the transmitting antenna energy leaks into the receiving antenna, drowning out the actual received signal. This significantly improves the accuracy and reliability of large bistatic angle tests on rough surfaces (such as soil and concrete).

[0046] The following description Figure 1 The execution method of each step is shown.

[0047] First, in step 100, the semi-empirical model is determined by the following formula:

[0048]

[0049] Where, k b To test the specular reflection component of the incident wave on the target surface, k r To test the diffuse reflection component of the incident wave on the target surface, k dTo test the power spectral components of the target surface, θ i ′, θ s ′, These are the incident angle, incident azimuth angle, scattering angle, and scattering azimuth angle, respectively. The scattering geometry parameters include the incident angle, incident azimuth angle, scattering angle, and scattering azimuth angle. This represents the electromagnetic scattering characteristics under the given scattering geometry parameters. Let k be the masking function. b k r k d a and b are both model parameters. For the coupling term of specular reflection and diffuse reflection, exp[b(1-cosγ] a ] is an approximate description of the Fresnel reflection function, a is the roughness component of the target surface at the incident wave frequency, and b is the dielectric property component of the target surface.

[0050] In this invention, when the above five model parameters are determined, it can be located that electromagnetic waves of a specific frequency band irradiate a rough surface, and a semi-empirical model of a class of rough surface elements can be completed. Then, the amplitude of the scattering center of this class of rough surface elements can be directly calculated at any observation angle, which effectively improves the applicability and modeling efficiency of the scattering center model.

[0051] In step 102, the known first scattering geometric parameters of the test target and the electromagnetic scattering characteristic data corresponding to the first scattering geometric parameters are input into the semi-empirical model to obtain the model parameters of the semi-empirical model, including:

[0052] The first scattering geometric parameter and the corresponding electromagnetic scattering characteristic data are input into the semi-empirical model, and the model parameters are obtained by solving the model through a genetic algorithm; wherein, the range of the bistatic angle corresponding to the first scattering geometric parameter is 0° to 60°.

[0053] In a preferred embodiment, the objective function used in the genetic algorithm in step 102 is obtained by the following method:

[0054] Determine the environmental parameters for obtaining electromagnetic scattering characteristic data under the first scattering geometric parameters;

[0055] The scattering coefficient of the target under the first scattering geometric parameters and environmental parameters was calculated using the full-wave numerical method.

[0056] The objective function value is obtained based on the electromagnetic scattering characteristics data under the scattering coefficient and the first scattering geometric parameters; the objective function is determined by the following formula:

[0057]

[0058] Where F is the objective function value, σs (i) is the scattering coefficient, f r (i) represents the electromagnetic scattering characteristics under the given scattering geometry parameters, where i is the first scattering geometry parameter, Q is the total number of first scattering geometry parameters of the test target, and θ i The angle of incidence is denoted as .

[0059] In this invention, the genetic algorithm can reduce the cost of manual trial and error, greatly improve computational efficiency, and effectively improve the accuracy of the obtained model parameters.

[0060] In step 104, the known second scattering geometric parameters of the test target are input into the semi-empirical model with determined model parameters to obtain electromagnetic scattering characteristic data corresponding to the second scattering geometric parameters; wherein the bistatic angle corresponding to the second scattering geometric parameters is greater than the bistatic angle corresponding to the first scattering geometric parameters, including:

[0061] The second scattering geometric parameters of the test target are substituted into the semi-empirical model with determined model parameters to calculate the electromagnetic scattering characteristics data under the second scattering geometric parameters; wherein, the bistatic angle range corresponding to the second scattering geometric parameters is 60° to 130°.

[0062] In a preferred embodiment, step 104 further includes:

[0063] Based on the first scattering geometric parameters of the test target and the semi-empirical model with determined model parameters, the simulated electromagnetic scattering characteristics data under the first scattering geometric parameters are calculated.

[0064] The electromagnetic scattering characteristic data of the simulation and the electromagnetic scattering characteristic data corresponding to the first scattering geometric parameters are compared to obtain the verification results. When the verification result is that the verification is passed, the electromagnetic scattering characteristic data corresponding to the second scattering geometric parameters is calculated according to the semi-empirical model with the determined model parameters.

[0065] Specifically, the verification result is determined using the following formula:

[0066]

[0067] Where error is the fitting error value, y 1i Let y be the electromagnetic scattering characteristic data of the i-th first scattering geometric parameter. 2i Let N be the simulated electromagnetic scattering characteristic data of the i-th first scattering geometric parameter, and N be the total number of first scattering geometric parameters.

[0068] In one specific implementation, taking 5GHz, VV polarization test data in the C-band as an example, the polarization test is conducted on a concrete surface. Electromagnetic scattering characteristic data (i.e., real data) within the bistatic angle range of 0° to 60° is used. With the minimum root mean square error as the objective function, the genetic algorithm in step 102 is used to estimate five unknown model parameters, namely k... b =2.9000, k r =0.0164, k d =-3.5178, a=3.9212, b=0.7940*10 -4 Substituting these five model parameters into the semi-empirical model of parameters in step 100, the target model is obtained. The first scattering geometric parameters corresponding to bistatic angles of 0° to 60° are then substituted into the target model to calculate the simulated electromagnetic scattering characteristic data under these parameters. Next, the simulated electromagnetic scattering characteristic data and the actual data are compared using the above formula for calculating the fitting error. A fitting error value of 0.0019 is obtained. If this fitting error value is less than the preset error threshold, the verification result is considered successful, indicating the accuracy of the model parameters and the model fitting algorithm. It should be noted that if the fitting error value is not less than the preset error threshold, the verification result is considered unsuccessful, and the process must return to step 102 to re-extract the model parameters.

[0069] In this invention, the root mean square error is used to evaluate the fitting effect, proving the accuracy of the model parameter estimation and the model fitting algorithm.

[0070] In step 104, the known second scattering geometric parameters of the test target are input into a semi-empirical model with determined model parameters to obtain electromagnetic scattering characteristic data corresponding to the second scattering geometric parameters; wherein, the bistatic angle corresponding to the second scattering geometric parameters is greater than the bistatic angle corresponding to the first scattering geometric parameters, including:

[0071] Substitute the target's second scattering geometric parameters into the target model to calculate the electromagnetic scattering characteristics data under the second scattering geometric parameters.

[0072] In one specific implementation, following the previous example, the parameters obtained in step 102 are substituted into the semi-empirical model of step 100 to obtain electromagnetic scattering characteristic data under the second scattering geometric parameters. This data is then compared with the results calculated using the full-wave numerical method to analyze the error. When the bistatic angle exceeds 60°, the fitting error increases, reaching 1.986 dB at 90°, which is still acceptable.

[0073] In this invention, when the bistatic angle exceeds 90°, the fitting error increases rapidly, and after 110°, the error becomes unacceptable, making it impossible for the test site to provide accurate measurement data. Therefore, calculating the electromagnetic scattering characteristics at large bistatic angles (60°–130°), especially for angles greater than 90°, using a semi-empirical model is crucial. Figure 2 Estimated data for bistatic angles from 0° to 130° are provided, with the estimated data for bistatic angles greater than 90° being more accurate than the test data.

[0074] like Figure 3 , Figure 4 As shown, embodiments of the present invention provide a device for determining electromagnetic scattering data of a test target. This device can be implemented in software, hardware, or a combination of both. From a hardware perspective, as... Figure 3 The diagram shown is a hardware architecture diagram of a computing device containing a test target electromagnetic scattering data determination device provided in an embodiment of the present invention, except for... Figure 3 In addition to the processor, memory, network interface, and non-volatile memory shown, the computing device in the embodiment may also include other hardware, such as a forwarding chip responsible for processing packets. Taking software implementation as an example, such as... Figure 4 As shown, as a logical device, it is formed by the CPU of its computing device reading the corresponding computer program from non-volatile memory into memory and running it. The electromagnetic scattering data determination device for the test target provided in this embodiment includes:

[0075] Module 400 is used to build a semi-empirical model of the test target;

[0076] The extraction module 402 is used to input the known first scattering geometric parameters of the test target and the electromagnetic scattering characteristic data corresponding to the first scattering geometric parameters into the semi-empirical model to obtain the model parameters of the semi-empirical model.

[0077] The calculation module 404 is used to input the known second scattering geometric parameters of the test target into a semi-empirical model with determined model parameters to obtain electromagnetic scattering characteristic data corresponding to the second scattering geometric parameters; wherein, the bistatic angle corresponding to the second scattering geometric parameters is greater than the bistatic angle corresponding to the first scattering geometric parameters.

[0078] In some specific implementations, the construction module 400 can be used to perform the above step 100, the extraction module 402 can be used to perform the above step 102, and the calculation module 404 can be used to perform the above step 104.

[0079] In some specific implementations, the construction module 400 is also used to perform the following operations:

[0080] The semi-empirical model is determined by the following formula:

[0081]

[0082] Where, k b To test the specular reflection component of the incident wave on the target surface, k r To test the diffuse reflection component of the incident wave on the target surface, k d To test the power spectral components of the target surface, θ i ′, θ s ′, These are the incident angle, incident azimuth angle, scattering angle, and scattering azimuth angle, respectively. The scattering geometry parameters include the incident angle, incident azimuth angle, scattering angle, and scattering azimuth angle. This represents the electromagnetic scattering characteristics under the given scattering geometry parameters. Let k be the masking function. b k r k d a and b are both model parameters. For the coupling term of specular reflection and diffuse reflection, exp[b(1-cosγ] a ] is an approximate description of the Fresnel reflection function, a is the roughness component of the target surface at the incident wave frequency, and b is the dielectric property component of the target surface.

[0083] In some specific implementations, the extraction module 402 is also used to perform the following operations:

[0084] The first scattering geometric parameter and the corresponding electromagnetic scattering characteristic data are input into the semi-empirical model, and the model parameters are obtained by solving the model through a genetic algorithm; wherein, the range of the bistatic angle corresponding to the first scattering geometric parameter is 0° to 60°.

[0085] In some specific implementations, the extraction module 402 is also used to perform the following operations:

[0086] Determine the environmental parameters for obtaining electromagnetic scattering characteristic data under the first scattering geometric parameters;

[0087] The scattering coefficient of the target under the first scattering geometric parameters and environmental parameters was calculated using the full-wave numerical method.

[0088] The objective function value is obtained based on the electromagnetic scattering characteristics data under the scattering coefficient and the first scattering geometric parameters; the objective function is determined by the following formula:

[0089]

[0090] Where F is the objective function value, σ s (i) is the scattering coefficient, fr (i) represents the electromagnetic scattering characteristics under the given scattering geometry parameters, where i is the first scattering geometry parameter, Q is the total number of first scattering geometry parameters of the test target, and θ i The angle of incidence is denoted as .

[0091] In some specific implementations, the arithmetic module 404 is also used to perform the following operations:

[0092] The second scattering geometric parameters of the test target are substituted into the semi-empirical model with determined model parameters to calculate the electromagnetic scattering characteristics data under the second scattering geometric parameters; wherein, the bistatic angle range corresponding to the second scattering geometric parameters is 60° to 130°.

[0093] In some specific embodiments, the device further includes a verification module, which performs the following operations:

[0094] Based on the first scattering geometric parameters of the test target and the semi-empirical model with determined model parameters, the simulated electromagnetic scattering characteristics data under the first scattering geometric parameters are calculated.

[0095] The electromagnetic scattering characteristic data of the simulation and the electromagnetic scattering characteristic data corresponding to the first scattering geometric parameters are compared to obtain the verification results. When the verification result is that the verification is passed, the electromagnetic scattering characteristic data corresponding to the second scattering geometric parameters is calculated according to the semi-empirical model with the determined model parameters.

[0096] It is understood that the structures illustrated in the embodiments of the present invention do not constitute a specific limitation on the target scattering data testing device for large bistatic angles. In other embodiments of the present invention, the target scattering data testing device for large bistatic angles may include more or fewer components than illustrated, or combine some components, or split some components, or have different component arrangements. The illustrated components may be implemented in hardware, software, or a combination of software and hardware.

[0097] The information interaction and execution process between the modules in the above-mentioned device are based on the same concept as the method embodiment of the present invention, and the specific details can be found in the description of the method embodiment of the present invention, and will not be repeated here.

[0098] This invention also provides a computing device, including a memory and a processor. The memory stores a computer program, and when the processor executes the computer program, it implements the method for determining electromagnetic scattering data of a test target according to any embodiment of this invention.

[0099] This invention also provides a computer-readable storage medium storing a computer program. When executed by a processor, the computer program causes the processor to perform the electromagnetic scattering data determination method for a test target according to any embodiment of this invention.

[0100] Embodiments of this application also provide a computer program product, which includes a computer program. A processor of a computer device reads the computer program from a computer-readable storage medium and executes the computer program, causing the computer device to perform the electromagnetic scattering data determination method for any of the test targets described in the above embodiments.

[0101] Specifically, a system or apparatus equipped with a storage medium may be provided, on which software program code implementing the functions of any of the embodiments described above is stored, and the computer (or CPU or MPU) of the system or apparatus may read and execute the program code stored in the storage medium.

[0102] In this case, the program code read from the storage medium can itself implement the function of any of the above embodiments, and therefore the program code and the storage medium storing the program code constitute part of the present invention.

[0103] Examples of storage media used to provide program code include floppy disks, hard disks, magneto-optical disks, optical disks (such as CD-ROM, CD-R, CD-RW, DVD-ROM, DVD-RAM, DVD-RW, DVD+RW), magnetic tapes, non-volatile memory cards, and ROMs. Alternatively, program code can be downloaded from a server computer via a communication network.

[0104] Furthermore, it should be clear that not only can the program code read by the computer be executed, but also the operating system or other components operating on the computer can be instructed based on the program code to perform some or all of the actual operations, thereby realizing the function of any of the embodiments described above.

[0105] Furthermore, it is understood that the program code read from the storage medium is written to the memory set in the expansion board inserted into the computer or to the memory set in the expansion module connected to the computer. Then, based on the instructions of the program code, the CPU or other components installed on the expansion board or expansion module execute some and all of the actual operations, thereby realizing the function of any of the above embodiments.

[0106] It should be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element.

[0107] Those skilled in the art will understand that all or part of the steps of the above method embodiments can be implemented by hardware related to program instructions. The aforementioned program can be stored in a computer-readable storage medium. When the program is executed, it performs the steps of the above method embodiments. The aforementioned storage medium includes various media that can store program code, such as ROM, RAM, magnetic disk, or optical disk.

[0108] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for determining electromagnetic scattering data of a test target, characterized in that, include: A semi-empirical model of the test target is constructed, and the semi-empirical model is determined by the following formula: in, To test the specular reflection component of the incident wave on the target surface, To test the diffuse reflection component of the incident wave on the target surface, To test the power spectrum components of the target surface, These are the incident angle, incident azimuth angle, scattering angle, and scattering azimuth angle, respectively. The scattering geometry parameters include the incident angle, incident azimuth angle, scattering angle, and scattering azimuth angle. f r ( This represents the electromagnetic scattering characteristics under the given scattering geometry parameters. For the masking function, , , , a and b All of these are model parameters. This is the coupling term between specular reflection and diffuse reflection. This is an approximate description of the Fresnel reflection function. a This represents the surface roughness component of the target at the incident wave frequency. b The dielectric property component of the target surface; The known first scattering geometric parameters of the test target and the electromagnetic scattering characteristic data corresponding to the first scattering geometric parameters are input into the semi-empirical model to obtain the model parameters of the semi-empirical model. The known second scattering geometric parameters of the test target are input into a semi-empirical model with determined model parameters to obtain electromagnetic scattering characteristic data corresponding to the second scattering geometric parameters; wherein the bistatic angle corresponding to the second scattering geometric parameters is greater than the bistatic angle corresponding to the first scattering geometric parameters.

2. The method as described in claim 1, characterized in that, The known first scattering geometric parameters of the test target and the electromagnetic scattering characteristic data corresponding to the first scattering geometric parameters are input into the semi-empirical model to obtain the model parameters of the semi-empirical model, including: The first scattering geometric parameter and the electromagnetic scattering characteristic data corresponding to the first scattering geometric parameter are input into the semi-empirical model, and the model parameters are obtained by solving the model through a genetic algorithm; wherein, the range of the bistatic angle corresponding to the first scattering geometric parameter is 0° to 60°.

3. The method as described in claim 2, characterized in that, The objective function used in the genetic algorithm is obtained through the following method: Determine the environmental parameters when obtaining the electromagnetic scattering characteristic data under the first scattering geometric parameters; The scattering coefficient of the test target under the first scattering geometry parameter and the environmental parameter is calculated using the full-wave numerical method; The target function value is obtained based on the scattering coefficient and the electromagnetic scattering characteristic data under the first scattering geometric parameters; the target function is determined by the following formula: in, F The objective function value is... The scattering coefficient is... f r ( i This represents the electromagnetic scattering characteristics under the given scattering geometry parameters. i The first scattering geometric parameter, Q The total number of the first scattering geometric parameters of the test target. θ i The angle of incidence is denoted as .

4. The method as described in claim 1, characterized in that, The known second scattering geometric parameters of the test target are input into a semi-empirical model with determined model parameters to obtain electromagnetic scattering characteristic data corresponding to the second scattering geometric parameters, including: The second scattering geometric parameters of the test target are substituted into the semi-empirical model with the determined model parameters to calculate the electromagnetic scattering characteristics data under the second scattering geometric parameters; wherein the bistatic angle range corresponding to the second scattering geometric parameters is 60° to 130°.

5. The method according to any one of claims 1 to 4, characterized in that, After the semi-empirical model with determined model parameters, and before obtaining the electromagnetic scattering characteristic data corresponding to the second scattering geometric parameters, the method further includes: Based on the first scattering geometric parameters of the test target and the semi-empirical model with the determined model parameters, the simulated electromagnetic scattering characteristic data under the first scattering geometric parameters are calculated. The simulated electromagnetic scattering characteristic data and the electromagnetic scattering characteristic data corresponding to the first scattering geometric parameters are compared to obtain the verification result; wherein, when the verification result is that the verification is passed, the electromagnetic scattering characteristic data corresponding to the second scattering geometric parameters is calculated according to the semi-empirical model with the determined model parameters.

6. A device for determining electromagnetic scattering data of a test target, characterized in that, The apparatus, used in the method of any one of claims 1-5, comprises: Builder modules are used to build semi-empirical models of the test targets; The extraction module is used to input the known first scattering geometric parameters of the test target and the electromagnetic scattering characteristic data corresponding to the first scattering geometric parameters into the semi-empirical model to obtain the model parameters of the semi-empirical model; The calculation module is used to input the known second scattering geometric parameters of the test target into a semi-empirical model with determined model parameters to obtain electromagnetic scattering characteristic data corresponding to the second scattering geometric parameters; wherein the bistatic angle corresponding to the second scattering geometric parameters is greater than the bistatic angle corresponding to the first scattering geometric parameters.

7. A computer device, characterized in that, The computer device includes a memory and a processor. The memory is used to store computer programs, and the processor is used to execute the computer programs stored in the memory to implement the steps of the method according to any one of claims 1-5.

8. A computer-readable storage medium, characterized in that, The storage medium stores a computer program, which, when executed by a processor, implements the steps of the method described in any one of claims 1-5.

9. A computer program product, characterized in that, Includes a computer program, which, when executed by a processor, implements the steps of the method according to any one of claims 1-5.

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