A radar scattering cross section measurement method and device based on scale mapping and a medium

Abstract

The present application relates to the field of radar technology, in particular to a radar scattering cross section measurement method and device based on scale mapping and medium. The specific method is to confirm the category information of the prototype target detected by the radar; according to the prototype target category, the prototype target and the scale target radar scattering cross section mapping model are called; according to the scale target radar scattering cross section corresponding to the prototype target and the prototype target and the scale target radar scattering cross section mapping model, the prototype target radar scattering cross section σ A . The present application constructs the prototype target and the scale target radar scattering cross section mapping model for different prototype targets; through the mapping model and the measurable scale target radar scattering cross section, the prototype target radar scattering cross section σ A can be accurately calculated; it is suitable whether the surface is coated with application medium material or not.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of radar technology, in particular to a radar scattering cross section measurement method and device based on scale mapping and a medium. BACKGROUND

[0002] The rapid development of electromagnetic scale equivalent theory and technology leads to efficient modeling and upgrading of complex large targets, and a series of electromagnetic scale equivalent theories and technologies have been developed, such as Sinclair's classic electromagnetic similarity theory, three similarity laws of scale measurement of lossy targets, etc., which have been widely used in target electromagnetic scale target testing and experimental data statistical processing and analysis. Among them, Sinclair's classic electromagnetic similarity theory is mainly used for metal materials or pure dielectric (low loss dielectric is approximately satisfied), and the three similarity laws of scale measurement of lossy targets are mainly used for mirror scattering sources. On the other hand, based on advanced theoretical methods, foreign countries widely carry out scale and full-size vehicle test analysis platform, and also systematically develop and encapsulate evaluation technology system including interactive detection method, multi-scale deep neural network, analytic hierarchy process, multi-source information source data level, feature level, decision level and other multi-level fusion methods to support the iterative development of electromagnetic scale equivalent technology.

[0003] Currently, the domestic preliminary research on equivalent scale method of lossy dielectric materials has achieved some basic results. The currently mature theories mainly include approximate scale, equivalent surface impedance, and lossy scatterer scale factor. When the scale target is measured, the material of the model should be strictly limited to metal materials or low-loss dielectric materials. However, the metal surface coated with a wave-absorbing material is the most common means to reduce the radar scattering cross section of the target. In this case, the electrical conductivity and electromagnetic parameters of the material are not variable, which does not meet the electromagnetic similarity principle under ideal conditions. For the case of lossy dielectric, there is less research in China, but its application value is very considerable. SUMMARY

[0004] The present application discloses a radar scattering cross section measurement method and device based on scale mapping, which can measure the radar scattering cross section mapping model of the prototype target through the radar scattering cross section mapping model of the prototype target and the scale target, and can improve the accuracy of the radar scattering cross section measurement of the prototype target.

[0005] To achieve the above-mentioned target, on the one hand, a radar scattering cross section measurement method based on scale mapping is provided, characterized in that the specific method is as follows:

[0006] Confirm the category information of the prototype target detected by the radar;

[0007] According to the prototype target category, a prototype target and a scaled target radar cross section mapping model are called;

[0008] According to the scaled target radar cross section corresponding to the prototype target and the prototype target and scaled target radar cross section mapping model, the prototype target radar cross section σ A .

[0009] The embodiment has the advantages that the prototype target and scaled target radar cross section mapping model is constructed for different prototype targets; and the prototype target radar cross section σ A can be accurately calculated through the mapping model and the measurable scaled target radar cross section, and is applicable to whether the surface is coated with an application medium material or not.

[0010] Further, the construction method of the prototype target and scaled target radar cross section mapping model is as follows:

[0011] The scaled target made of metal and having an electromagnetic characteristic equivalent to that of the prototype target is constructed, and the scaled target has a similarity to the prototype target greater than a first threshold value;

[0012] The scaled target is detected in a microwave anechoic chamber at a first measurement wave band λ1, the scaled target radar cross section test and measurement are completed, and scaled target measurement data are acquired;

[0013] According to the scaled target measurement data, the prototype target and scaled target radar cross section mapping model is constructed.

[0014] Further, the prototype target and scaled target radar cross section mapping model includes a first mapping model and a second mapping model;

[0015] The first mapping model is a prototype target and scaled target radar cross section mapping model in a mirror / near mirror scattering case;

[0016] The second mapping model is a prototype target and scaled target radar cross section mapping model in a surface traveling wave and edge diffraction case.

[0017] The embodiment has the advantages that the prototype target and scaled target radar cross section mapping model is constructed for the two common cases of the prototype target surface, and the calculation accuracy of the prototype target radar cross section can be further improved.

[0018] Further, according to the current condition of the prototype target, the first mapping model or the second mapping model is selected.

[0019] Further, the first mapping model is constructed as follows:

[0020] Before and after the scaled-down target is coated with the application medium material, the first radar cross section σ O and the second radar cross section σ C of the scaled-down target are measured respectively.

[0021] A scaled-down target scaling factor S is calculated according to the ratio of a first measurement wave band λ1 and a second measurement wave band λ2; the first measurement wave band λ1 is an electromagnetic measurement wave band of the scaled-down target, and the second measurement wave band λ2 is a required measurement wave band λ2 of the prototype target;

[0022] A normalized equivalent surface impedance η s of the prototype target coated with the application medium material under the second measurement wave band λ2 is calculated respectively, and a normalized equivalent surface impedance η s of the scaled-down target coated with the application medium material under the first measurement wave band λ1 is calculated respectively.

[0023] The first mapping model formula is as follows:

[0024] σ A = s 2 · σ B

[0025] wherein,

[0026] wherein,

[0027] In the formula, σ A is a radar cross section of the prototype target, and σ B is a radar cross section of an ideal model.

[0028] The embodiment has the advantages that, for the mirror / near-mirror scattering case, the first radar cross section σ O and the second radar cross section σ C of the scaled-down target are measured respectively before and after the scaled-down target is coated with the application medium material, the electromagnetic changes before and after the scaled-down target is coated with the application medium material are considered in the first mapping model, the mapping relationship between the radar cross section of the scaled-down target and the radar cross section of the ideal model is constructed, the radar cross section of the ideal model is corrected through the target scaling factor, and the radar cross section of the prototype target is obtained; in the process, the changes of the surface coated with the application medium material, the changes of the normalized equivalent surface impedance, and the changes of the measurement wave band are considered and measured, and the calculation accuracy of the radar cross section of the prototype target is high.

[0029] Further, the second mapping model is a neural network model, and the construction method is as follows:

[0030] Test the scaled-down target and the prototype target to obtain training samples, the training samples including a scaling factor, a scaled-down target test frequency, a test angle, a prototype target radar absorbing material reflectivity, a scaled-down target radar absorbing material reflectivity, and prototype target radar cross section information;

[0031] The scaling factor is a ratio of a first measurement waveband λ1 and a second measurement waveband λ2; the first measurement waveband λ1 is an electromagnetic measurement waveband of the scaled-down target, and the second measurement waveband λ2 is a required measurement waveband λ2 of the prototype target;

[0032] The scaling factor, the scaled-down target test frequency, the test angle, the prototype target radar absorbing material reflectivity, and the scaled-down target radar absorbing material reflectivity in the training samples are taken as input information, and the prototype target radar cross section information is taken as output information;

[0033] A difference between the predicted prototype target radar cross section information and the prototype target radar cross section information in the training samples is taken as an error function;

[0034] The weights of each layer in the neural network are adjusted until the error is less than a preset range or the number of iterations is completed.

[0035] The embodiment has the advantage that, for the complex situation of surface traveling waves and edge diffraction, the neural network algorithm is used for automatic fitting, and as the number of training samples increases, the calculation accuracy of the prototype target radar cross section is higher and higher.

[0036] To achieve the above object, on the other hand, a radar cross section measuring and calculating device based on scaled-down mapping is provided, characterized in that it comprises an information acquisition module, a measuring and calculating module, and a mapping model construction module.

[0037] The information acquisition module confirms category information of a prototype target detected by a radar and a scaled-down target radar cross section corresponding to the prototype target.

[0038] The measuring and calculating module calls a prototype target and scaled-down target radar cross section mapping model according to the category of the prototype target, substitutes the scaled-down target radar cross section into the prototype target and scaled-down target radar cross section mapping model, and calculates a prototype target radar cross section σ A .

[0039] Further, the mapping model construction module further comprises a mapping model construction module, constructs the scaled-down target made of metal and equivalent to electromagnetic characteristics of the prototype target, the scaled-down target has a similarity greater than a first threshold to the prototype target, a first measurement waveband λ1 is used to detect the scaled-down target in a microwave darkroom, the scaled-down target radar cross section test and measurement are completed, scaled-down target measurement data are obtained, and the prototype target and scaled-down target radar cross section mapping model is constructed according to the scaled-down target measurement data.

[0040] To achieve the above object, in another aspect, a storage medium stores a plurality of instructions suitable for being loaded by a processor to execute the method described above.

[0041] Other advantages, objects, and features of the application will be apparent from the following specification, claims, and accompanying drawings. BRIEF DESCRIPTION OF DRAWINGS

[0042] The drawings illustrating the present application are as follows.

[0043] Figure 1 Mapping diagram of scaled target, ideal model and prototype target in Example 1.

[0044] Figure 2 Structure diagram of neural network model in Example 2.

[0045] Figure 3 Flow diagram of Example 1.

[0046] Figure 4 Flow diagram of Example 2. DETAILED DESCRIPTION

[0047] The present application will be further described below in conjunction with the drawings and examples.

[0048] Example 1:

[0049] A radar scattering cross section measurement method based on scaled mapping, as shown in Figure 4 The specific method is as follows:

[0050] S1, confirming the category information of the prototype target detected by the radar;

[0051] In this example, the prototype target is an airplane, and its surface belongs to mirror / near mirror scattering.

[0052] S2, constructing a first mapping model of the radar scattering cross section of the prototype target and the scaled target; the first mapping model is a radar scattering cross section mapping model of the prototype target and the scaled target under mirror / near mirror scattering;

[0053] S21, constructing the scaled target made of metal and equivalent to the electromagnetic characteristics of the prototype target, and the scaled target has a similarity greater than 99% with the prototype target in shape;

[0054] S22, detecting the scaled target in a microwave anechoic chamber with a first measurement waveband λ1, completing the scaled target radar cross section test and measurement, and obtaining scaled target measurement data;

[0055] S23, constructing a radar cross section mapping model of the prototype target and the scaled target according to the scaled target measurement data.

[0056] S231, respectively measuring a first radar cross section σ O and a second radar cross section σ C of the scaled target before and after coating the surface of the scaled target with an application medium material.

[0057] S232, calculating a scaled factor S of the scaled target according to a ratio of the first measurement waveband λ1 and the second measurement waveband λ2; the first measurement waveband λ1 is an electromagnetic measurement waveband of the scaled target, and the second measurement waveband λ2 is a measurement waveband λ2 required by the prototype target;

[0058] S233, respectively calculating a normalized equivalent surface impedance η s of the prototype target coated with the application medium material under the second measurement waveband λ2, and a normalized equivalent surface impedance η s of the scaled target coated with the application medium material under the first measurement waveband λ1.

[0059] S234, calculating an ideal model radar cross section, as shown in the following formula: Figure 1

[0060]

[0061] wherein,

[0062] In the formula, σ A is a radar cross section of the prototype target, and σ B is an ideal model radar cross section.

[0063] S3, calculating a radar cross section σ A of the prototype target according to the radar cross section of the scaled target corresponding to the prototype target and the mapping model of the radar cross section of the prototype target and the scaled target.

[0064] σ A = s 2 · σ B

[0065] Embodiment 2:

[0066] A radar cross section measurement method based on scaled mapping, as shown in the following formula, is specifically as follows: Figure 4

[0067] ​​S1, confirming the category information of the prototype target detected by the radar;

[0068] In this embodiment, the prototype target is an airplane, and the surface thereof belongs to the surface traveling wave and edge diffraction case.

[0069] S2, constructing a second mapping model of the radar scattering cross section of the prototype target and the scaled target; the second mapping model is a mapping model of the radar scattering cross section of the prototype target and the scaled target in the surface traveling wave and edge diffraction case.

[0070] The second mapping model is a neural network model for predicting the radar scattering cross section of the prototype target, and the training manner is as follows:

[0071] S21, constructing the scaled target made of metal and equivalent to the electromagnetic characteristics of the prototype target, and the scaled target has a similarity greater than 99% to the shape of the prototype target;

[0072] S22, detecting the scaled target in a first measurement waveband λ1 in a microwave darkroom to complete the radar scattering cross section test and measurement of the scaled target and obtain the measurement data of the scaled target;

[0073] S23, measuring the first radar scattering cross section σ O and the second radar scattering cross section σ C of the scaled target respectively before and after the surface of the scaled target is coated with an application medium;

[0074] S23, calculating the scaled factor S of the target according to the ratio of the first measurement waveband λ1 and the second measurement waveband λ2; the first measurement waveband λ1 is the electromagnetic measurement waveband of the scaled target, and the second measurement waveband λ2 is the measurement waveband λ2 required by the prototype target;

[0075] S234, obtaining training samples, and the training samples include the scaled factor, the test frequency of the scaled target, the test angle, the reflectivity of the prototype target, the reflectivity of the scaled target, and the radar scattering cross section information of the prototype target;

[0076] S235, taking the scaled factor, the test frequency of the scaled target, the test angle, the reflectivity of the prototype target, and the reflectivity of the scaled target in the training samples as input information, and taking the radar scattering cross section information of the prototype target as output information;

[0077] taking the difference between the predicted radar scattering cross section information of the prototype target and the radar scattering cross section information of the prototype target in the training samples as an error function;

[0078] adjusting the weights of each layer in the neural network until the error is less than a preset range or the number of iterations is completed, as shown in formula (3). Figure 2

[0079] ​S3, taking the scaling factor, the scaling target test frequency, the test angle, the prototype target radar absorbing material reflectivity, and the scaled target radar absorbing material reflectivity as input information, predicting the prototype target radar cross section through the second mapping model.

[0080] Those skilled in the art will understand that embodiments of the present application can be provided as methods, systems, or computer program products. Accordingly, the present application can take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present application can take the form of a computer program product on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROMs, optical storage devices, etc.) embodying computer readable program code.

[0081] The present application is described in reference to the flowchart and / or block diagrams of the methods, apparatus (systems) and computer program products according to embodiments of the present application. It should be understood that each flow and / or block in the flowchart and / or block diagrams, and combinations of flows and / or blocks in the flowchart and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart and / or block diagram block or blocks. Figure 1 one or more flows and / or blocks Figure 1 means for carrying out the function specified in the flowchart block or blocks.

[0082] These computer program instructions can also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instructions means which implement the function specified in the flowchart and / or block diagram block or blocks. Figure 1 one or more flows and / or blocks Figure 1 means for carrying out the function specified in the flowchart block or blocks.

[0083] These computer program instructions can also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the function specified in the flowchart and / or block diagram block or blocks. Figure 1 one or more flows and / or blocks Figure 1 means for carrying out the function specified in the flowchart block or blocks.

[0084] It should be pointed out finally that the above embodiments are only used to illustrate the technical solutions of the present application but not to limit it. Although the present application has been described in detail with reference to the above embodiments, it should be understood by those skilled in the art that the specific embodiments of the present application can be modified or replaced equivalently without departing from the spirit and scope of the present application, and any modification or equivalent replacement should be covered in the protection scope of the claims of the present application.

Claims

1. A method for calculating radar cross section based on scaled mapping, characterized in that, The specific method is as follows: Confirm the category information of the prototype target detected by the radar; Retrieve the radar cross section mapping model of the prototype target and the scaled-down target according to the prototype target category; Based on the radar cross section of the scaled-down target corresponding to the prototype target and the mapping model between the radar cross sections of the prototype target and the scaled-down target, the radar cross section of the prototype target is calculated. ; The method for constructing the radar cross section mapping model of the prototype target and the scaled-down target is as follows: Construct a scaled-down target made of metal with electromagnetic characteristics equivalent to the prototype target, wherein the scaled-down target has a shape similarity to the prototype target greater than a first threshold. In a microwave anechoic chamber, using the first measurement band Detect scaled-down targets, complete radar cross section tests and measurements of the scaled-down targets, and acquire measurement data of the scaled-down targets; Based on the measurement data of the scaled-down target, a radar cross section mapping model between the prototype target and the scaled-down target is constructed; The radar cross section mapping model between the prototype target and the scaled-down target includes a first mapping model and a second mapping model; The first mapping model is a radar cross section mapping model of the prototype target and the scaled-down target under specular / near-spectral scattering conditions; The second mapping model is a radar cross section mapping model of the prototype target and the scaled-down target under the conditions of surface traveling wave and edge diffraction; The method for constructing the first mapping model is as follows: Before and after coating the scaled-down target surface with the applied dielectric material, the first radar cross section of the scaled-down target was measured respectively. Second radar cross section ; According to the first measurement band Second measurement band The target scaling factor S is calculated proportionally; the first measurement band Electromagnetic measurement band for scaled-down targets, second measurement band Measurement bands required for the prototype target ; Calculate the second measurement band separately Normalized equivalent surface impedance of the prototype target coated with the dielectric material and the first measurement band Normalized equivalent surface impedance of scaled-down target of the coating application medium material ; The formula for the first mapping model is: in, in, In the formula, The radar cross section of the prototype target. The radar cross section is for an ideal model.

2. The radar cross section calculation method based on scaled mapping as described in claim 1, characterized in that, Based on the current status of the prototype target, select either the first mapping model or the second mapping model.

3. The radar cross section calculation method based on scaled mapping as described in claim 1, characterized in that, The second mapping model is a neural network model, and its construction method is as follows; Experiments were conducted on scaled-down targets and prototype targets to obtain training samples, which included scaled-down target test frequency, test angle, reflectivity of the absorbing material of the prototype target, reflectivity of the absorbing material of the scaled-down target, and radar cross section information of the prototype target. The scaling factor is the first measurement band. Second measurement band The ratio; the first measurement band Electromagnetic measurement band for scaled-down targets, second measurement band Measurement bands required for the prototype target ; The scaling factor, scaling target test frequency, test angle, and reflectivity of the prototype target absorbing material and the scaling target absorbing material in the training samples are used as input information. The prototype target's radar cross section information is used as the output information; The difference between the predicted prototype target radar cross section information and the prototype target radar cross section information in the training samples is used as the error function; Adjust the weights of each layer in the neural network until the error is less than the preset range or the number of iterations is completed.

4. A radar cross section calculation device based on scaled mapping, characterized in that, include: Information acquisition module, measurement module, and mapping model construction module; The information acquisition module confirms the category information of the prototype target detected by the radar and the radar cross section of the scaled-down target corresponding to the prototype target. The calculation module retrieves the radar cross section mapping model between the prototype target and the scaled-down target based on the prototype target category, substitutes the radar cross section of the scaled-down target into the prototype target-scaled-down target radar cross section mapping model, and calculates the radar cross section of the prototype target. ; It also includes a mapping model construction module to construct a scaled-down target made of metal with electromagnetic characteristics equivalent to the prototype target, wherein the scaled-down target has a shape similarity to the prototype target greater than a first threshold; and the measurement is performed in a microwave anechoic chamber using a first measurement band. Detect a scaled-down target, conduct radar cross section tests and measurements on the scaled-down target, and acquire measurement data of the scaled-down target; based on the measurement data of the scaled-down target, construct a radar cross section mapping model between the prototype target and the scaled-down target; The radar cross section mapping model between the prototype target and the scaled-down target includes a first mapping model and a second mapping model; The first mapping model is a radar cross section mapping model of the prototype target and the scaled-down target under specular / near-spectral scattering conditions; The second mapping model is a radar cross section mapping model of the prototype target and the scaled-down target under the conditions of surface traveling wave and edge diffraction; The method for constructing the first mapping model is as follows: Before and after coating the scaled-down target surface with the applied dielectric material, the first radar cross section of the scaled-down target was measured respectively. Second radar cross section ; According to the first measurement band Second measurement band The target scaling factor S is calculated proportionally; the first measurement band Electromagnetic measurement band for scaled-down targets, second measurement band Measurement bands required for the prototype target ; Calculate the second measurement band separately Normalized equivalent surface impedance of the prototype target coated with the dielectric material and the first measurement band Normalized equivalent surface impedance of scaled-down target of the coating application medium material ; The formula for the first mapping model is: in, in, In the formula, The radar cross section of the prototype target. The radar cross section is for an ideal model.

5. A storage medium, characterized in that, The storage medium stores a plurality of instructions which are adapted for loading by a processor to execute the method according to any one of claims 1 to 3.

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