A calculation method for dynamic radar cross section of rotating blades

Abstract

This application provides a method for calculating the dynamic radar cross section (DRC) of a rotating blade, comprising: obtaining measured RCS data for the rotating blade; obtaining a modulation function based on the measured data; obtaining a multiplicative factor based on the measured data; constructing a calculation model based on the product of the RCS peak function of an ideal conductor model of the blade, the modulation function, and the multiplicative factor; obtaining dimensional parameters of the blade to be solved; and inputting the dimensional parameters into the calculation model to obtain the dynamic RCS. This method utilizes only measured data for a rotating blade of one size to rapidly calculate a formula for the dynamic RCS of a rotating blade. This formula can be used to rapidly calculate the dynamic RCS of similar rotating blades of various sizes. The calculated results are highly accurate and can provide data support for analyzing the statistical characteristics of the RCS of rotating blades.

Description

Technical Field

[0001] The invention belongs to the technical field of radar cross section calculation, and in particular relates to a method for calculating the dynamic radar cross section of a rotating blade. Background Art

[0002] In recent years, an increasing number of targets with rotating blades have appeared within radar surveillance ranges. In particular, with the rapid development of the wind power and consumer drone industries, the number of targets with rotating blades, such as wind turbines and rotary-wing drones, has increased year by year. Assessing the potential electromagnetic impact of wind farms and analyzing the target characteristics of rotary-wing drones often requires calculating the dynamic radar cross section of their rotating blades.

[0003] The main methods currently used to calculate the radar cross section (RCS) of rotating blades include field experimental measurements, scaled-down model measurements, electromagnetic calculations, and analytical models. Field experimental and scaled-down model measurements are cumbersome, often requiring multiple measurements to analyze the RCS of blades with varying dimensions. Electromagnetic calculations require modeling the blades and time-consuming computation using electromagnetic calculation software. These methods are not very convenient for engineering applications and require long computation cycles. While analytical models are highly convenient, they can only calculate the peak RCS of rotating blades and are unable to rapidly calculate the RCS data for the entire blade rotation process. Summary of the Invention

[0004] The object of the present invention is to provide a convenient calculation method for the dynamic radar cross section of a rotating blade to solve the problems raised in the above background technology.

[0005] To achieve the above-mentioned object, the present invention provides a method for calculating the dynamic radar cross section of a rotating blade, comprising the following steps: obtaining measured data of the radar cross section of a rotating blade; obtaining a modulation function based on the measured data; obtaining a multiplicative factor based on the measured data; constructing a calculation model based on the product of a radar cross section peak function of an ideal conductor model of the blade, the modulation function, and the multiplicative factor; obtaining dimensional parameters of the blade to be solved; and inputting the dimensional parameters into the calculation model to solve and obtain the dynamic radar cross section.

[0006] Preferably, the calculation model satisfies the following formula:

[0007] σ=k·σ peak (λ,L,l1,l2)·Y(θ) (1)

[0008] Where σ represents the dynamic radar cross section of the rotating blade, Y(θ) represents the complete modulation function, and σ peak(λ, L, l1, l2) represents the radar cross-section peak function of the ideal conductor model of the blade, k represents the multiplicative factor, the complete modulation function is a periodic function with θ as the independent variable, θ is the rotation angle of the rotating blade relative to the reference position, λ is the wavelength of the incident electromagnetic wave, L is the length of a single blade, l1 is half the chord length of the root of a single blade, l2 is half the maximum chord length of a single blade, and k is a positive real number.

[0009] Preferably, obtaining the modulation function according to the measured data specifically includes:

[0010] For a rotating blade with a known number of blades, length of a single blade, chord length at the root of a single blade, and maximum chord length of a single blade, a measured radar cross-section dataset of multiple rotating blades of the same model in a rotating state at different times is obtained;

[0011] The radar cross section dataset is divided into three different subsets according to the angle between the radar line of sight and the impeller rotation plane, wherein the three different subsets include: a subset in which the radar line of sight is parallel to the impeller rotation plane, a subset in which the radar line of sight is perpendicular to the impeller rotation plane, and a subset in an intermediate state;

[0012] Arrange the data in the subset parallel to the radar line of sight and the impeller rotation plane in descending order to obtain a sorted first descending data sequence;

[0013] Normalizing the first descending data sequence so that a maximum value of the first descending data sequence is 0, and then fitting the normalized first descending data sequence using a polynomial fitting to obtain a fitting function;

[0014] Use the following formula to get the value of the modulation function in one cycle

[0015]

[0016] Among them, Y T (θ) represents the modulation function within one cycle; Y T / 2 (θ) represents the fitting function, N represents the number of leaves;

[0017] Performing period extension on the modulation function within the one period to obtain the complete modulation function;

[0018] The vertical subsets are arranged in descending order to obtain a sorted second data sequence, and the complete modulation function in a state where the radar line of sight is perpendicular to the impeller rotation plane is obtained.

[0019] Preferably, the radar cross-section dataset is divided into three different subsets: when the angle between the radar line of sight and the impeller rotation plane is between 0 degrees and 12.5 degrees, it is divided into two states: the radar line of sight is parallel to the impeller rotation plane; when the angle between the radar line of sight and the impeller rotation plane is between 77.5 degrees and 90 degrees, it is divided into two states: the radar line of sight is perpendicular to the impeller rotation plane; and when the angle between the radar line of sight and the impeller rotation plane is greater than 12.5 degrees and less than 77.5 degrees, it is divided into an intermediate state.

[0020] Preferably, the method for calculating the dynamic radar cross section of a rotating blade further includes the following steps: uniformly segmenting the first descending data sequence, and replacing the first descending data sequence with a new sequence composed of the median values ​​of each segment as the objective function of the polynomial fitting.

[0021] Preferably, the polynomial function used in the polynomial fitting is a cubic polynomial function that satisfies the following formula:

[0022] Y T / 2 (θ)=Aθ 3 +Bθ 2 +Cθ,θ∈[0,π / 2N) (3)

[0023] Among them, A, B, and C are the coefficients of the polynomial function used in polynomial fitting.

[0024] Preferably, the fitting function obtained from the measured data of a rotating blade and applicable to the calculation of dynamic radar cross sections of rotating blades of other sizes is:

[0025]

[0026] The value of θ ranges from 0 to π / 2N.

[0027] Preferably, the radar cross section peak function of the blade ideal conductor model is directly calculated by a peak radar cross section formula of an ideal conductor cylindrical multi-blade obtained based on the physical optics method.

[0028] Preferably, the calculation method of the radar cross section peak function of the ideal conductor model of the blades of different sizes satisfies the following formula:

[0029]

[0030] In formula (5), σ peak (λ, L, l1, l2) is the peak radar cross section function of the ideal conductor model of the blade, λ is the wavelength of the incident electromagnetic wave, L is the length of a single blade, l1 is half of the chord length of the root of a single blade, and l2 is half of the maximum chord length of a single blade.

[0031] Preferably, the multiplicative factor obtained according to the measured data satisfies the following formula:

[0032]

[0033] In formula (6), D KL (P||M) is the KL divergence, which is defined as

[0034]

[0035] Where P(x) is the probability density function of the measured radar cross section data set, and M(x) is the probability density function of the calculated radar cross section data.

[0036] Preferably, the multiplicative factor k obtained from the measured radar cross section data of a rotating blade and applicable to the calculation of the dynamic radar cross section of rotating blades of other sizes is:

[0037]

[0038] Compared with the prior art, the present invention has the following beneficial effects:

[0039] Using only measured radar cross-section data for a single size of rotating blade, a fast formula for calculating the dynamic radar cross-section of rotating blades is derived. This formula can be used to quickly calculate the dynamic radar cross-section of similar rotating blades of various sizes. The calculated results are highly accurate and provide data support for analyzing the statistical characteristics of rotating blade radar cross-sections. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] Figure 1 The present invention provides a flow chart of a method for calculating the dynamic radar cross section of a rotating blade.

[0041] Figure 2 This is a diagram showing the sorting results of measured radar cross-section data of a model of fan blades according to a method for calculating the dynamic radar cross-section of a rotating blade provided by the present invention.

[0042] Figure 3 One of the schematic diagrams of the ideal conductive cylinder model of a fan blade for calculating the dynamic radar cross section of a rotating blade provided by the present invention.

[0043] Figure 4 The second schematic diagram of the ideal conductive cylinder model of a fan blade for calculating the dynamic radar cross section of a rotating blade provided by the present invention.

[0044] Figure 5 This is a comparison between the wind turbine dynamic radar cross-section change function calculated by the present invention and the measured data.

[0045] in:

[0046] 1-first blade; 2-second blade; 3-third blade; a-measured result of a state close to parallel; b-measured result of a state close to vertical; c-calculated result of this method of a state close to parallel; d-calculated result of this method of a state close to vertical. DETAILED DESCRIPTION

[0047] A method for calculating the dynamic radar cross section of a rotating blade provided by the present invention is described in detail below with reference to the accompanying drawings and specific embodiments.

[0048] Figure 1 The present invention provides a flow chart of a method for calculating the dynamic radar cross section of a rotating blade, comprising the following steps:

[0049] Step S101: obtaining measured data of a radar cross section of a rotating blade;

[0050] Step S102: obtaining a modulation function according to the measured data;

[0051] Step S103: obtaining a multiplication factor according to the measured data;

[0052] Step S104: constructing a calculation model according to the product of the radar cross section peak function of the blade ideal conductor model, the modulation function and the multiplication factor;

[0053] Step S105: obtaining the size parameters of the blade to be solved;

[0054] Step S106: inputting the size parameters into the calculation model to solve and obtain the dynamic radar cross section.

[0055] The above calculation model is derived by utilizing only measured radar cross-section (RCS) data for a single rotor blade size. This model can rapidly calculate the dynamic RCS of similar rotor blades of varying sizes. The resulting results are highly accurate, shorten the calculation cycle, and improve computational convenience. This model can provide data support for analyzing the statistical characteristics of rotor blade RCS.

[0056] The following takes the dynamic radar cross section estimation of the rotating blades of a large horizontal axis wind turbine as an example for explanation.

[0057] The calculation model satisfies the following formula:

[0058] σ=k·σ peak (λ,L,l1,l2)·Y(θ) (1)

[0059] Where σ represents the dynamic radar cross section of the rotating blade, Y(θ) represents the complete modulation function, and σ peak (λ, L, l1, l2) represents the radar cross-section peak function of the ideal conductor model of the blade, k represents the multiplicative factor, the complete modulation function is a periodic function with θ as the independent variable, θ is the rotation angle of the rotating blade relative to the reference position, λ is the wavelength of the incident electromagnetic wave, L is the length of a single blade, l1 is half the chord length of the root of a single blade, l2 is half the maximum chord length of a single blade, and k is a positive real number.

[0060] The large horizontal axis wind turbine mentioned above usually contains three blades. The dynamic radar cross section σ of the rotating blade is the modulation function Y(θ), the peak radar cross section function σ of the blade ideal conductor model peak The product of three parts (λ, L, l1, l2) and the multiplicative factor k.

[0061] The state of one blade in a vertically upward position is recorded as the reference position, which can be recorded as "0". The rotation angle of the rotating blade relative to the reference position is recorded as θ. The modulation function is a periodic function with θ as the independent variable. In this case, the number of blades connected to the hub is N = 3, and the period T of the modulation function Y(θ) is π / 3. The radar cross-section peak function σ of the blade ideal conductor model peak (λ, L, l1, l2) is a function of the wavelength λ of the incident electromagnetic wave, the length L of a single blade, half the root chord length l1 of a single blade, and half the maximum chord length l2 of a single blade. The multiplicative factor k is a positive real number.

[0062] Furthermore, a modulation function is obtained according to the measured data, which specifically includes the following steps:

[0063] Step 1: For a rotating blade with known number of blades, length of a single blade, root chord length of a single blade, and maximum chord length of a single blade, obtain a measured radar cross-section dataset of multiple rotating blades of the same model in a rotating state at different times;

[0064] Step 2: Divide the radar cross section dataset from step 1 into three different subsets based on the angle between the radar line of sight and the impeller rotation plane. The three different subsets include: a subset where the radar line of sight is parallel to the impeller rotation plane, a subset where it is perpendicular to the impeller rotation plane, and a subset where it is in the intermediate state.

[0065] Step 3: Arrange the data in the subset where the radar line of sight is parallel to the impeller rotation plane in descending order to obtain a sorted first descending data sequence;

[0066] Step 4: normalize the first descending data sequence so that the maximum value of the first descending data sequence is 0, and then use polynomial fitting to fit the normalized first descending data sequence to obtain a fitting function;

[0067] Step 5: Use the following formula to get the value of the modulation function in one cycle

[0068]

[0069] Among them, Y T (θ) represents the modulation function within one cycle; Y T / 2 (θ) represents the fitting function, N represents the number of leaves;

[0070] Step 6: Extend the modulation function within a period to obtain a complete modulation function;

[0071] Step 7: Arrange the vertical subsets in descending order to obtain a sorted second data sequence. Follow the same method as steps 4 to 6 to obtain a complete modulation function when the radar line of sight is perpendicular to the impeller rotation plane.

[0072] In the calculation formula of formula (1), the radar cross-section peak function σ of the ideal conductor model of the blade is peak (λ, L, l1, l2) is directly calculated from the peak radar cross section formula of an ideal conductor cylindrical multi-blade based on the physical optics method. The modulation function Y(θ) and the multiplication factor k are first estimated from the measured data of a rotating blade. The modulation function Y(θ) and the multiplication factor k obtained from the measured data of the rotating blade are then combined with the peak function σ calculated by the formula peak (λ, L, l1, l2) Calculate the dynamic radar cross section of rotating blades of other sizes.

[0073] The following uses measured radar cross-section data from a Siemens SWT-2.3-108 wind turbine blade, collected by a WSR-88D weather radar, as an example to illustrate a method for estimating the modulation function Y(θ) from this data. The basic parameters of the wind turbine blade and the WSR-88D weather radar are shown in Tables 1 and 2.

[0074] Table 1 Parameters of the first blade

[0075]

[0076] Table 2 Radar parameters

[0077]

[0078] A method for estimating a modulation function Y(θ) from measured data of a rotating blade comprises the following steps performed in sequence:

[0079] In step 1, for a Siemens SWT-2.3-108 wind turbine with 3 hub-connected blades, a single blade length of 54 m, a single blade root chord length of 2.4 m, and a single blade maximum chord length of 4 m, a dataset S of measured radar cross sections (RSCs) of multiple different rotating blades of this model at different times while rotating is collected.

[0080] In step 2, the measured radar cross-section dataset S collected in step 1 is divided into three different subsets S1, S2, and S3 according to the angle between the radar line of sight and the impeller rotating plane: parallel, perpendicular, and intermediate states between the radar line of sight and the impeller rotating plane.

[0081] The radar cross-section dataset is divided into three different subsets: when the angle between the radar line of sight and the impeller rotation plane is between 0 and 12.5 degrees, it is classified as parallel to the impeller rotation plane; when the angle between the radar line of sight and the impeller rotation plane is between 77.5 and 90 degrees, it is classified as perpendicular to the impeller rotation plane; and when the angle between the radar line of sight and the impeller rotation plane is greater than 12.5 and less than 77.5 degrees, it is classified as an intermediate state.

[0082] Among them, the radar line of sight is parallel to the impeller rotating surface, which can be nearly parallel. In this state, the angle between the radar line of sight and the impeller rotating surface is between 0 degrees and 12.5 degrees; the radar line of sight is perpendicular to the impeller rotating surface, which can be nearly perpendicular to the impeller rotating surface. In this state, the angle between the radar line of sight and the impeller rotating surface is between 77.5 degrees and 90 degrees.

[0083] In step 3, the data in the measured data subset S1 where the radar line of sight is parallel to the impeller rotation plane are sorted in descending order to obtain the sorted data sequence R1(x). The radar cross-section data of blades of multiple different wind turbines of Siemens SWT-2.3-108 wind turbines are measured. After all the data are aggregated, a total of n data are obtained. The sorted R1(x) is as follows: Figure 2 shown.

[0084] In step 4, R1(x) is used as the reference value of the periodic modulation function Y(θ) from 0 to π / 6 within half a period when the radar line of sight is parallel to the impeller rotation plane, using dB as the unit.

[0085] In this step, the first descending data sequence is evenly segmented, and a new sequence composed of the median of each segment is used to replace the first descending data sequence as the objective function of the polynomial fitting. R1(x) is evenly segmented, and a new sequence composed of the median of each segment is used to replace R1(x) as the objective function of the polynomial fitting, which can improve the calculation accuracy of the modulation function Y(θ) estimation.

[0086] The polynomial function used in polynomial fitting is a cubic polynomial function that satisfies the following formula:

[0087] Y T / 2 (θ)=Aθ 3 +Bθ 2 +Cθ,θ∈[0,π / 2N) (3)

[0088] Normalize R1(x) to make its maximum value 0dB, then use polynomial fitting to fit the normalized R1(x) to obtain the fitting function Y T / 2 (θ), where θ ranges from 0 to π / 6.

[0089] Y T / 2 (θ) is used as the basic unit of the modulation function. The polynomial function used in the polynomial fitting is a cubic polynomial function with a constant term of 0.

[0090] The Y obtained by fitting is sorted by the measured radar cross section data of the blades of Siemens SWT-2.3-108 wind turbine. T / 2 (θ) is shown in the following formula:

[0091] Y T / 2 (θ)=-615θ 3 +437θ 2 -135θ,θ∈[0,π / 6) (4)

[0092] Because the radar cross section of the rotating blades changes periodically, for the wind turbine, when the rotation angle θ of the rotating blades relative to the reference position is between 0 and π / 6, the radar cross section changes monotonically. Due to the randomness of the sampling time of the measured radar cross section data, it can cover various states of the rotating blades. Therefore, the basic unit Y of the modulation function can be fitted by the data sequence R1(x) after the measured data is sorted. T / 2 (θ).

[0093] Use the following formula to get the value of the modulation function Y(θ) from 0 to π / 3 in one cycle

[0094]

[0095] The data in the measured data subset S2 where the radar line of sight is perpendicular to the impeller rotation plane are arranged in descending order to obtain a sorted data sequence R2(x).

[0096] Follow the same method as steps 4 to 6 to obtain the Y value within one cycle when the radar sight line is perpendicular to the impeller rotation plane. T / 2 (θ) and the complete modulation function Y(θ) obtained by periodic extension.

[0097] The above process, based on the measured radar cross section data of a Siemens SWT-2.3-108 wind turbine blade, can be used to calculate the dynamic radar cross section of rotating blades of other sizes. The basic unit of the debugging function is:

[0098]

[0099] Radar cross section peak function σ of the ideal conductor model of the blade peak (λ, L, l1, l2) is a function of the wavelength λ of the incident electromagnetic wave, the length L of a single blade, half the chord length of the root of a single blade l1, and half the maximum chord length of a single blade l2. peak The calculation method of (λ,L,l1,l2) is:

[0100]

[0101] The formula is obtained by the following process. Simplify the blade into a cylindrical conductor and establish a cylindrical conductor blade model, such as Figure 3 and Figure 4 As shown. It is known that the analytical formula for solving the radar cross section of a cylinder using physical optics is as follows

[0102]

[0103] When the radar line of sight is parallel to the impeller rotation plane, Figure 4 As shown, the first blade 1 is perpendicular to the radar line of sight, and the second blade 2 and the third blade 3 correspond to The radar cross-sections of the second and third blades 2 and 3 are much smaller than those of the first blade 1, and their influence can be ignored. When the radar line of sight is perpendicular to the impeller's rotating plane, all three blades are perpendicular to the radar line of sight, and the radar cross-sections of the three blades are equal.

[0104] The method for estimating the multiplicative factor k from the measured radar cross section data of a rotating blade is as follows: let P(x) be the probability density function of the measured radar cross section data set, M(x) be the probability density function of the calculated radar cross section data, and the multiplicative factor k be estimated by the following optimization problem.

[0105]

[0106] Where D KL (P||M) is the KL divergence, which is defined as

[0107]

[0108] Where M(x) is obtained by calculating the dynamic radar cross section using the modulation function of a rotating blade of known size, the corresponding ideal conductor model radar cross section peak function value, and the assumed multiplication factor according to equation (1). In this embodiment, Y is obtained from the measured data of the Siemens SWT-2.3-108 wind turbine blade. T / 2 (θ), the size parameters and radar wavelength parameters of the fan blade are substituted into formula (7) to obtain the peak function value of the radar cross section of the ideal conductor model of the blade. Then, according to the assumed multiplication factor value, according to formula (1), and Y T / 2 (θ) is used as Y(θ) in equation (1), and the dynamic radar cross-section value within half a period of the corresponding modulation function can be obtained. From the periodicity of the complete modulation function Y(θ), it can be seen that the probability density function of the radar cross-section value within half a period is the same as the probability density function of the complete time. Therefore, the probability density function M(x) can be directly calculated from the dynamic radar cross-section value within half a period of the corresponding modulation function.

[0109] The multiplicative factor k that can be used to calculate the dynamic radar cross section of rotating blades of other sizes is obtained using the above method based on the measured radar cross section data of a Siemens SWT-2.3-108 wind turbine blade:

[0110]

[0111] Now we have obtained the formula for calculating the dynamic radar cross section of rotating blades of other sizes. In formula (1), the modulation function Y(θ) is calculated by formula (6) and Y is calculated according to formula (5). T (θ), and then periodically extended to obtain the multiplicative factor k is obtained by formula (11).

[0112] When calculating the dynamic radar cross section of rotating blades of other sizes, for example, the dynamic radar cross section of the rotating blades of Siemens-Gamesa SG3.4-132 wind turbine, the size parameters are shown in Table 3. The peak radar cross section function σ of the ideal conductor model of the blade of this type of wind turbine can be obtained from formula (7): peak (λ, L, l1, l2). Substituting it into equation (1) we can get the dynamic radar cross section of the rotating blades of this type of wind turbine.

[0113] Table 3 Parameters of the second blade

[0114]

[0115] The dynamic radar cross section of the SG 3.4-132 fan obtained by the calculation method of the dynamic radar cross section of the rotating blade provided by the present invention is compared with the measured data within half a cycle, that is, within the rotation angle range corresponding to the basic unit of the modulation function. Figure 5 , where a represents the measured result of the state close to parallel, b represents the measured result of the state close to vertical, c represents the calculated result of the method of the state close to parallel, and d represents the calculated result of the method of the state close to vertical. The quantitative comparison of the results is shown in Table 4. Figure 5 As can be seen from Table 4, the results calculated by the method of the present invention have good accuracy compared with the measured data.

[0116] Table 4 Comparison of the calculation results of the calculation method in this application with the measured data

[0117]

Claims

1. A method for calculating the dynamic radar cross section of a rotating blade, characterized by: include: Obtaining measured data of the radar cross section of a rotating blade; Obtaining a modulation function according to the measured data; Obtaining a multiplicative factor according to the measured data; Constructing a calculation model according to the product of the radar cross section peak function of the blade ideal conductor model, the modulation function and the multiplicative factor; Obtaining the size parameters of the rotating blade to be solved; Inputting the size parameters into the calculation model to solve for a dynamic radar cross section; The calculation model satisfies the following formula: σ=k·σ peak (λ,L,l1,l2)·Y(θ) (1) Where σ represents the dynamic radar cross section of the rotating blade, Y(θ) represents the complete modulation function, and σ peak (λ, L, l1, l2) represents the radar cross-section peak function of the ideal conductor model of the blade, k represents the multiplicative factor, the complete modulation function is a periodic function with θ as the independent variable, θ is the rotation angle of the rotating blade relative to the reference position, λ is the wavelength of the incident electromagnetic wave, L is the length of a single blade, l1 is half the chord length of the root of a single blade, l2 is half the maximum chord length of a single blade, and k is a positive real number; The obtaining of the modulation function according to the measured data specifically includes: For a rotating blade with a known number of blades, length of a single blade, chord length at the root of a single blade, and maximum chord length of a single blade, a measured radar cross-section dataset of multiple rotating blades of the same model in a rotating state at different times is obtained; The radar cross section dataset is divided into three different subsets according to the angle between the radar line of sight and the impeller rotation plane, wherein the three different subsets include: a subset in which the radar line of sight is parallel to the impeller rotation plane, a subset in which the radar line of sight is perpendicular to the impeller rotation plane, and a subset in an intermediate state; Arrange the data in the subset parallel to the radar line of sight and the impeller rotation plane in descending order to obtain a sorted first descending data sequence; Normalizing the first descending data sequence so that a maximum value of the first descending data sequence is 0, and then fitting the normalized first descending data sequence using a polynomial fitting to obtain a fitting function; Use the following formula to get the value of the modulation function in one cycle Among them, Y T (θ) represents the modulation function within one cycle; Y T / 2 (θ) represents the fitting function, N represents the number of leaves; Performing period extension on the modulation function within the one period to obtain the complete modulation function; The vertical subsets are arranged in descending order to obtain a sorted second data sequence, and the complete modulation function in a state where the radar line of sight is perpendicular to the impeller rotation plane is obtained.

2. The method for calculating the dynamic radar cross section of a rotating blade according to claim 1, characterized in that: The radar cross-section dataset is divided into three different subsets: when the angle between the radar line of sight and the impeller rotation plane is between 0 degrees and 12.5 degrees, the radar line of sight is parallel to the impeller rotation plane; when the angle between the radar line of sight and the impeller rotation plane is between 77.5 degrees and 90 degrees, the radar line of sight is perpendicular to the impeller rotation plane; and when the angle between the radar line of sight and the impeller rotation plane is greater than 12.5 degrees and less than 77.5 degrees, the radar line of sight is in an intermediate state.

3. The method for calculating the dynamic radar cross section of a rotating blade according to claim 1, characterized in that: The following steps are also included: The first descending data sequence is evenly segmented, and a new sequence composed of the median values ​​of each segment is used to replace the first descending data sequence as the objective function of the polynomial fitting.

4. The method for calculating the dynamic radar cross section of a rotating blade according to claim 1, wherein: The polynomial function used in polynomial fitting is a cubic polynomial function that satisfies the following formula: Y T / 2 (θ)=Aθ 3 +Bθ 2 +Cθ, θ∈[0,π / 2N) (3) Among them, A, B, and C are the coefficients of the polynomial function used in polynomial fitting.

5. The method for calculating the dynamic radar cross section of a rotating blade according to claim 1, characterized in that: The fitting function obtained from the measured radar cross section data of a rotating blade and applicable to the calculation of dynamic radar cross sections of rotating blades of other sizes is: The value of θ ranges from 0 to π / 2N.

6. The method for calculating the dynamic radar cross section of a rotating blade according to any one of claims 1 to 5, characterized in that: The radar cross section peak function of the blade ideal conductor model is directly calculated by the peak radar cross section formula of the ideal conductor cylindrical multi-blade obtained based on the physical optics method.

7. The method for calculating the dynamic radar cross section of a rotating blade according to claim 6, characterized in that: The calculation method of the radar cross section peak function of the ideal conductor model of the blades of different sizes satisfies the following formula: In formula (5), σ peak (λ, L, l1, l2) is the peak radar cross section function of the ideal conductor model of the blade, λ is the wavelength of the incident electromagnetic wave, L is the length of a single blade, l1 is half of the chord length of the root of a single blade, and l2 is half of the maximum chord length of a single blade.

8. The method for calculating the dynamic radar cross section of a rotating blade according to any one of claims 1 to 5, characterized in that: The multiplicative factor obtained according to the measured data satisfies the following formula: In formula (6), D KL (P||M) is the KL divergence, which is defined as Where P(x) is the probability density function of the measured radar cross section data set, and M(x) is the probability density function of the calculated radar cross section data.

9. The method for calculating the dynamic radar cross section of a rotating blade according to claim 8, characterized in that: The multiplicative factor k obtained from the measured radar cross section data of a rotating blade and applicable to the calculation of dynamic radar cross sections of rotating blades of other sizes is:

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