Method for obtaining average RCS scattering model of migrating insect swarm based on insect radar

Abstract

The method for obtaining the average RCS scattering model of migratory insect swarms based on an insect radar according to the present disclosure inversely calculates the body length and orientation of migratory insect swarms through insect radar echo data; performs fitting processing on the body length inversion data and the orientation inversion data to obtain a unified body length inversion data distribution and an orientation inversion data distribution; constructs a body length-orientation joint distribution model of the migratory insect swarms according to the body length inversion data distribution and the orientation inversion data distribution; establishes an RCS database of individual targets of migratory insect swarms by using FEKO simulation software; and performs weighted summation on the body length-orientation joint distribution model and the RCS data of individual targets to obtain an average RCS scattering model of migratory insect swarms. It helps to achieve quantitative inversion of the density of large-scale migratory insect swarms and improve the accuracy of density inversion.

Description

Technical Field

[0001] The present invention belongs to the technical field of insect radar, and particularly relates to a method for obtaining an average RCS scattering model of migrating insect swarms based on insect radar. Background Art

[0002] At present, radar has become an effective means for detecting, tracking and researching migrating insects due to its advantages of all-weather and all-day monitoring. The emergence of insect radar provides a more powerful tool for the refined measurement of insect targets. The vertical observation insect radar can obtain biological parameters such as the body axis orientation, wingbeat frequency, and body size of insect targets. Applying these parameters to large-scale migration prediction is of great significance for establishing a scattering model of migrating insect swarms, completing quantitative inversion of swarm density, and realizing a warning system for migrating insect swarms.

[0003] Studying the scattering characteristics of individual insect targets is the basis for establishing a scattering model of migrating insect swarms. Existing research shows that the prolate spheroid target can better replicate the measured results of individual insect targets. When the influence of multiple scattering is not considered, the backscattering enhancement (RCS) of migrating insect swarms can be regarded as a simple superposition of the backscattering enhancement of individual insects. In 2012, Phillip et al. clarified through the analysis of radar scattering mechanism that there is a linear relationship between weather radar reflectivity, air animal density, and average RCS. Then, establishing an RCS scattering model of migrating insect swarms has become the key to large-scale migration density inversion.

[0004] A major difficulty in accurately obtaining the average RCS of insect swarms is how to simultaneously consider target biological parameters (such as body length distribution, orientation distribution) and radar observation parameters (such as incident angle). Currently, there is a lack of research on the RCS of insect swarm targets that can consider biological parameters and observation parameters. The previous methods for obtaining the RCS of insect swarm targets using joint observations cannot clarify the relationship between them and biological parameters and observation parameters, and have very large limitations in practical applications. In 2020, when Phillip et al. inverted the migration density of mayfly populations, although they simulated the RCS values at different incident angles with fixed biological parameters, they still did not take the incident angle as a variable but took the average value for the final inversion model. And they did not consider the influence of insect biological parameters (such as body length distribution, orientation distribution, etc.) on the average RCS. Summary of the Invention

[0005] The present invention overcomes one of the deficiencies of the prior art and provides a method for obtaining an average RCS scattering model of migrating insect swarms based on insect radar. By using a vertical observation radar to obtain the body length distribution and orientation distribution of migrating insects, and then combining with the RCS database of individual insect targets, the average RCS calculation based on the biological parameters of local insect swarm targets can be completed, which helps to realize the quantitative inversion of the density of large-scale migrating insect swarms and improve the accuracy of density inversion.

[0006] According to one aspect of the present disclosure, the present disclosure provides a method for obtaining an average RCS scattering model of migrating insect swarms based on an insect radar, the method comprising:

[0007] Inverting the body length and orientation of the migrating insect swarm based on the insect radar echo data; performing fitting processing on the body length inversion data and the orientation inversion data of the migrating insect swarm to obtain a unified body length inversion data distribution and orientation inversion data distribution of the migrating insect swarm;

[0008] Constructing a body length - orientation joint distribution model of the migrating insect swarm according to the body length inversion data distribution and the orientation inversion data distribution of the migrating insect swarm;

[0009] Establishing an individual target RCS database of the migrating insect swarm using FEKO simulation software;

[0010] Performing weighted summation on the body length - orientation joint distribution model of the migrating insect swarm and the RCS data of the individual target to obtain the average RCS scattering model of the migrating insect swarm.

[0011] In a possible implementation manner, the performing fitting processing on the body length inversion data and the orientation inversion data of the migrating insect swarm to obtain a unified body length inversion data distribution and orientation inversion data distribution of the migrating insect swarm includes:

[0012] Respectively removing the outliers from the body length inversion data and the orientation inversion data of the migrating insect swarm;

[0013] Performing histogram statistics on the body length inversion data and the orientation inversion data of the migrating insect swarm after removing the outliers respectively;

[0014] Using basis functions to respectively fit the body length inversion data and the orientation inversion data of the migrating insect swarm after histogram statistics;

[0015] Respectively retaining or removing the fitting results of the body length inversion data and the orientation inversion data of the migrating insect swarm according to the determination coefficients of the fitting results, to obtain a unified body length inversion data distribution and orientation inversion data distribution of the migrating insect swarm.

[0016] In a possible implementation manner, the constructing a body length - orientation joint distribution model of the migrating insect swarm according to the body length inversion data distribution and the orientation inversion data distribution of the migrating insect swarm includes:

[0017] Performing discrete normalization processing on the body length inversion data distribution of the migrating insect swarm to obtain the orientation vector P of the migrating insect swarm θ ;

[0018] Performing discrete normalization processing on the orientation inversion data distribution of the migrating insect swarm to obtain the body length vector P of the migrating insect swarm l ;

[0019] Transpose the orientation vector P of the migratory insect swarm θ and multiply it by the body length vector P of the migratory insect swarm l to obtain the body length - orientation joint distribution model of the migratory insect swarm.

[0020] In a possible implementation,

[0021] the average RCS scattering model of the migratory insect swarm

[0022] where P θ,l is the number of body length - orientation joint distribution vectors of the migratory insect swarm, σ θ,l is the individual target RCS data of the migratory insect swarm, and θ is the insect radar data (incident angle).

[0023] In a possible implementation, the coefficient of determination of the fitting result is 0.8.

[0024] The method for obtaining the average RCS scattering model of migratory insect swarms based on insect radar according to the present disclosure inversely calculates the body length data and orientation data of the migratory insect swarm based on the insect radar data to obtain the body length inversion data and orientation inversion data of the migratory insect swarm; performs fitting processing on the body length inversion data and orientation inversion data of the migratory insect swarm to obtain a unified body length inversion data distribution and orientation inversion data distribution of the migratory insect swarm; constructs the body length - orientation joint distribution model of the migratory insect swarm according to the body length inversion data distribution and orientation inversion data distribution of the migratory insect swarm; establishes an RCS database of individual targets of the migratory insect swarm using FEKO simulation software; and performs weighted summation of the body length - orientation joint distribution model of the migratory insect swarm and the RCS data of the individual target to obtain the average RCS scattering model of the migratory insect swarm. It helps to achieve quantitative inversion of the density of large - scale migratory insect swarms and improve the accuracy of density inversion. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] The drawings are used to provide further understanding of the technical solutions of the present application or the prior art and constitute a part of the specification. Among them, the drawings showing the embodiments of the present application, together with the embodiments of the present application, are used to explain the technical solutions of the present application, but do not constitute a limitation to the technical solutions of the present application.

[0026] Figure 1 Shows a flowchart of a method for obtaining the average RCS scattering model of migratory insect swarms based on insect radar according to an embodiment of the present disclosure;

[0027] Figure 2 Shows a flowchart of a method for the inversion data distribution model of migratory insect swarms based on insect radar according to an embodiment of the present disclosure;

[0028] Figure 3 Shows a schematic diagram of the body length - orientation joint distribution model of migratory insect swarms based on an insect radar according to an embodiment of the present disclosure;

[0029] Figure 4 Shows a schematic diagram of the simulation of individual target RCS data of migratory insect swarms based on an insect radar according to an embodiment of the present disclosure;

[0030] Figure 5 Shows a schematic diagram of the average RCS scattering model of migratory insect swarms based on an insect radar according to an embodiment of the present disclosure. Detailed implementation manners

[0031] The following will combine the accompanying drawings and embodiments to detail the implementation manners of the present invention, so as to fully understand how the present invention uses technical means to solve technical problems and the implementation process of achieving corresponding technical effects and implement accordingly. Each feature in the embodiments of this application and the embodiments can be combined with each other on the premise of not conflicting, and the formed technical solutions are all within the protection scope of the present invention.

[0032] In addition, the steps shown in the flowchart of the accompanying drawings can be executed in a computer such as a set of computer - executable instructions. And although the logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in a different order than here.

[0033] Establishing a realistic target scattering model of migratory insect swarms is a prerequisite for accurately inverting the density, and an accurate individual target scattering model is a prerequisite for establishing the target scattering model of insect swarms. Research shows that the prolate - spheroid target can better replicate the measured results of insect individual targets, so the present invention uses the prolate - spheroid as the shape of the insect target.

[0034] According to Mie theory, an ellipsoidal target of any shape can be transformed into a spherical target with a radius of 1 m through coordinate scale transformation, and the scattering cross - section formula of the ellipsoidal target for any incident angle θ0 can be obtained.

[0035]

[0036] Among them, E0 represents the incident electric field, E” sθ” and represent the scattered fields after two - time coordinate scale transformation, r represents the distance from the incident point to the center of the sphere, and d is a quantity related to the incident angle θ0 and the three semi - axes a, b, c of the ellipsoid. When θ = π - θ0, the radar backscattering cross - section (RCS) is obtained.

[0037] The relationship between the weather radar reflectivity η and the particle density N bio and the average radar backscattering cross - section σ ave (RCS) is expressed as:

[0038]

[0039] Combined with formulas (1) and (2), the overall RCS of the swarm target is expressed as shown in formula (3). Due to the sensitivity of the ellipsoidal target to the incident angle and body size parameters, when calculating the average RCS of the swarm target, the target orientation parameter θ0 and body size parameter r need to be taken into account to establish a swarm target scattering model that better fits the actual migration situation.

[0040]

[0041] The present invention mainly includes two parts: modeling the joint probability distribution model of "body length - orientation" of an insect radar and modeling the average RCS scattering model of a swarm target.

[0042] Figure 1 The flowchart of a method for obtaining an average RCS scattering model of a migrating swarm of insects based on an insect radar according to an embodiment of the present disclosure is shown. As Figure 1 shown, the method may include:

[0043] Step S1: Inverting the body length and orientation of the migrating swarm of insects based on the insect radar echo data,

[0044] The high - resolution fully polarized vertical observation insect radar can complete the inversion of the body length and orientation parameters of insect targets. In this example, the high - resolution fully polarized vertical observation insect radar is installed in Dongying, Shandong. By using the high - resolution fully polarized insect radar for long - term observation, a total of 69 days of insect migration body size parameter inversion data from June 14, 2021 to August 21, 2021 is obtained.

[0045] Parameter Value Operating frequency band Ku band Center frequency 16.2 GHz Synthesized bandwidth 800 MHz Polarization mode Full polarization

[0046] Table 1 Insect radar parameters

[0047] Step S2: Performing fitting processing on the body length inversion data and orientation inversion data of the migrating swarm of insects to obtain the unified body length inversion data distribution and orientation inversion data distribution of the migrating swarm of insects.

[0048] In an example, this step may include:

[0049] Step S21: Removing the outliers from the body length inversion data and orientation inversion data of the migrating swarm of insects respectively;

[0050] Step S22: Performing histogram statistics on the body length inversion data and orientation inversion data of the migrating swarm of insects after removing the outliers respectively;

[0051] Step S23: Using basis functions to fit the body length inversion data and orientation inversion data of the migrating swarm of insects after histogram statistics respectively;

[0052] Step S24: Retain or eliminate the fitting results of the body length inversion data and the orientation inversion data of the migratory insect swarm respectively according to the determination coefficients of the fitting results, so as to obtain the unified distribution of the body length inversion data and the orientation inversion data of the migratory insect swarm. Among them, the determination coefficient of the fitting result can be 0.8, or can be set to other values as needed, which is not limited here.

[0053] Figure 2 The flowchart of the method for the inversion data distribution model of the migratory insect swarm based on the insect radar according to an embodiment of the present disclosure is shown.

[0054] In an example, as Figure 2 shown, perform the distribution statistics of the body length and orientation of the migratory insect swarm target according to the body length and orientation inversion results detected by the insect radar, and perform data processing on the distribution statistics results of the body length and orientation of the migratory insect swarm target. First, eliminate the outliers of the body length and orientation inversion data of the migratory insect swarm, then perform histogram statistics, select a suitable basis function to fit the normalized histogram statistics results, and retain the fitting results with a determination coefficient greater than 0.8. Finally, eliminate the outliers and average the parameters of the retained fitting results to obtain a unified discrete insect body length distribution and orientation distribution that can be applied to actual migration, and then fit with a model of the sum of two Gaussian distributions. The final body length distribution model is expressed as Equation (4).

[0055] For the orientation distribution, use a Gaussian distribution model for fitting, and the final orientation distribution model is expressed as Equation (5).

[0056]

[0057]

[0058] Among them, D represents the body length of the individual target of the migratory insect swarm, w is the orientation of the individual target of the migratory insect swarm, and α is the angle where the peak of the orientation distribution of the individual target of the migratory insect swarm is located.

[0059] Step S3: Construct a body length-orientation joint distribution model of the migratory insect swarm according to the body length inversion data distribution and the orientation inversion data distribution of the migratory insect swarm.

[0060] Figure 3 The schematic diagram of the body length-orientation joint distribution model of the migratory insect swarm based on the insect radar according to an embodiment of the present disclosure is shown.

[0061] The incident angle of the insect individual target is jointly determined by the radar emission wave angle and the insect orientation. When the radar emission wave parameters are fixed, the change in the target incident angle is only related to the orientation of the migrating insect swarm. For example, the body length distribution range of the migrating insect swarm is set to 2 mm - 26 mm, the step size is 1, the peak value of the orientation distribution of the migrating insect swarm is 90°, and 9 angles are taken on each side of the peak value of the orientation distribution, with a step size of 10°. Then, when converting the target orientation peak value w max into the incident angle peak value θ max , 9 values are taken on each side of θ max with Δθ = 10°, and the discrete normalization processing is performed on the body length inversion data distribution of the migrating insect swarm to obtain the body length vector P l of the migrating insect swarm, as shown in Equation (8); the discrete normalization processing is performed on the orientation inversion data (incident angle) distribution of the migrating insect swarm to obtain the orientation vector P θ of the migrating insect swarm, as shown in Equation (7).

[0062] P θ = [p θ1 , p θ2 , p θ3 …… p θ19 (4)

[0063] P l = [p l2 , p l3 , p l4 …… p l26 (5)

[0064] Transpose the orientation vector P θ of the migrating insect swarm and multiply it by the body length vector P l of the migrating insect swarm to obtain the "body length - orientation" joint probability distribution model P Figure 3 of the migrating insect swarm as shown in

[0065]

[0066] After establishing the "body length - orientation" joint probability distribution model of the migrating insect swarm, the RCS data of each body length and orientation of the migrating insect swarm are required to complete the average RCS scattering modeling of the insect swarm target. Therefore, the FEKO electromagnetic simulation software is used to model the individual targets (insects) of the migrating insect swarm within the distribution range to obtain the RCS database of the insect individual targets.

[0067] Step S4: Use the FEKO simulation software to establish the RCS database of the individual targets of the migrating insect swarm.

[0068] Figure 4 shows the simulation schematic diagram of the RCS data of the individual targets of the migrating insect swarm based on the insect radar according to an embodiment of the present disclosure.

[0069] For example, using the measurement results of the darkroom experiment of the team on 183 insects of 22 species, the average body axis ratio of the measured individual insect targets is 3.8599. To further simplify the simulation modeling, the body axis ratio of the ellipsoidal insect model is set to 4:1. The FEKO software is used to simulate the ellipsoidal targets with a body length range of 2 mm - 26 mm and a step size of 1 mm. The simulation schematic diagram is as shown in Figure 4 shown, and the simulation settings are shown in Table 2.

[0070] Parameter Value Polarization mode HH polarization Frequency 2.8 GHz Incident angle One revolution around the body axis

[0071] Table 2 Simulation Settings of Individual Targets in Migratory Insect Swarms

[0072] Step S5: Weighted sum the body length - orientation joint distribution model of the migratory insect swarm and the RCS data of the individual targets to obtain the average RCS scattering model of the migratory insect swarm.

[0073] Weighted sum the probabilities of each point in the "body length - orientation" joint probability distribution model of the migratory insect swarm obtained in step S3 and the corresponding RCS data of the insect individual targets in the migratory insect swarm obtained in step S4 to obtain the average individual RCS scattering model of the swarm target (formula (6)).

[0074]

[0075] Figure 5 shows a schematic diagram of the average RCS scattering model of migratory insect swarms based on insect radar according to an embodiment of the present disclosure.

[0076] For example, the average RCS data of the migratory insect swarm obtained based on the above steps is shown in Table 3,

[0077]

[0078]

[0079] Table 3

[0080] Taking the peak of the incident angle as the independent variable and the average RCS of the insect individual target as the dependent variable, perform least - squares fitting based on the cosine function. The result is shown in formula (11), and the cosine curve of the average RCS scattering model of the migratory insect swarm is as shown in Figure 5 shown.

[0081] σ ave (θ) = 1.42 + 0.22×cos(0.03θ) Formula (11).

[0082] The present invention is a method for obtaining the average RCS scattering model of migrating insect swarms based on an insect radar, which can be applied to the precise inversion of actual migrating insect swarms, providing an effective means for accurately obtaining the average RCS of migrating insect swarms. Compared with previous average RCS scattering models, this model takes into account biological parameters (such as body length distribution, orientation distribution) and radar observation parameters (such as incident angle), making the average RCS result of migrating insect swarms more in line with reality, thereby improving the accuracy of density inversion.

[0083] Although the embodiments disclosed in the present invention are as above, the content described is only an embodiment adopted for the convenience of understanding the present invention and is not intended to limit the present invention. Any person skilled in the art within the technical field to which the present invention pertains may make any modifications and changes in the form of implementation and details without departing from the spirit and scope disclosed by the present invention. However, the scope of patent protection of the present invention shall still be subject to the scope defined by the appended claims.

Claims

1. A method for obtaining an average RCS scattering model of migratory insect swarms based on an insect radar, characterized in that The method includes: Based on the insect radar echo data, inversely calculate the body length and orientation of the migrating insect swarm, and perform fitting processing on the body length inversion data and orientation inversion data of the migrating insect swarm to obtain a unified body length inversion data distribution and orientation inversion data distribution of the migrating insect swarm; Construct a body length-orientation joint distribution model of the migrating insect swarm according to the body length inversion data distribution and orientation inversion data distribution of the migrating insect swarm; Use FEKO simulation software to establish an RCS database of individual targets of the migrating insect swarm; Perform weighted summation on the body length-orientation joint distribution model of the migrating insect swarm and the RCS data of the individual targets to obtain the average RCS scattering model of the migrating insect swarm.

2. The method for obtaining the average RCS scattering model of a migratory insect swarm according to claim 1, characterized in that The performing fitting processing on the body length inversion data and orientation inversion data of the migrating insect swarm to obtain a unified body length inversion data distribution and orientation inversion data distribution of the migrating insect swarm includes: Respectively remove the outliers from the body length inversion data and orientation inversion data of the migrating insect swarm; Perform histogram statistics on the body length inversion data and orientation inversion data of the migrating insect swarm after removing the outliers respectively; Use basis functions to respectively fit the body length inversion data and orientation inversion data of the migrating insect swarm after histogram statistics; According to the determination coefficient of the fitting result, respectively retain or remove the fitting results of the body length inversion data and orientation inversion data of the migrating insect swarm to obtain a unified body length inversion data distribution and orientation inversion data distribution of the migrating insect swarm.

3. The method for obtaining the average RCS scattering model of a migrating insect swarm according to claim 1, characterized in that, The constructing a body length-orientation joint distribution model of the migrating insect swarm according to the body length inversion data distribution and orientation inversion data distribution of the migrating insect swarm includes: The discrete normalization process is performed on the body length inversion data distribution of the migratory insect swarm to obtain the body length vector P of the migratory insect swarm l ; The orientation inversion data distribution of the migratory insect swarm is discretely normalized to obtain the orientation vector P of the migratory insect swarm θ ; Transpose the orientation vector P of the migratory insect swarm θ and multiply it with the body length vector P of the migratory insect swarm l to obtain the body length-orientation joint distribution model of the migratory insect swarm.

4. The method for obtaining the average RCS scattering model of a migrating insect swarm according to claim 2, wherein The determination coefficient of the fitting result is 0.8.

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