Unmanned aerial vehicle swarm distributed array antenna scattering characteristic analysis method

Abstract

The invention discloses an unmanned aerial vehicle swarm distributed array antenna scattering characteristic analysis method, which comprises the following steps: obtaining infinitesimal dipole model parameters through geometric parameter equivalence of a single unmanned aerial vehicle, and calculating an initial excitation coefficient of each unmanned aerial vehicle; correcting the initial excitation coefficient of each unmanned aerial vehicle to obtain an unmanned aerial vehicle feature weight coefficient; constructing an attitude relation correction mutual coupling coefficient in an ideal state through translation and rotation when the configuration of the unmanned aerial vehicle array is changed; constructing a mutual coupling matrix, and obtaining an in-matrix excitation coefficient of each unmanned aerial vehicle under the consideration of a mutual coupling effect; and constructing and solving a balance equation, calculating an actual excitation coefficient considering a mutual coupling effect, calculating a total scattering field of the unmanned aerial vehicle array, and obtaining a radar cross section of the unmanned aerial vehicle array. According to the invention, the scattering characteristic analysis during the change of the array configuration of the unmanned aerial vehicle is realized, the problem of complex model scale in grid analysis is avoided, and the analysis efficiency is improved.

Description

Technical Field

[0001] The present invention belongs to the technical field of electromagnetic scattering, and in particular relates to a method for analyzing scattering characteristics of a swarm of distributed array antennas of unmanned aerial vehicles. Background Art

[0002] Drone swarms are widely used in the fields of communication, remote sensing and navigation. In actual working environments, factors such as wind load and vibration can cause changes in the array configuration of drone swarms. For scattering characteristics, changes in the array distribution will greatly affect the identifiable characteristics of the target, causing the target signal to be lost or exposed. At the same time, as the scale of drone arrays increases, how to accurately analyze the scattering performance of distributed drone arrays is a challenge.

[0003] Generally speaking, the existing methods for the scattering characteristics of deformed arrays can be divided into the following two categories. The first analysis strategy regards the entire array structure as a whole, and usually uses numerical methods such as the finite element method, the method of moments, and the finite difference time domain method to solve it. This type of method can achieve accurate analysis, but when the array is large or the unit structure is complex, it requires large computing resources and time costs, and it is difficult to apply to large-scale arrays. The second is to achieve approximate analysis by establishing a connection between the unit structure and the entire array. For example, the scattering pattern method, similar to the radiation pattern multiplication method, also expresses the array scattering as the product of the unit factor and the array factor, but because the mutual coupling effect between units is not considered, the analysis results of its scattering characteristics are not accurate. The active pattern method evaluates the scattering characteristics of large arrays by calculating or measuring small arrays multiple times. Although it can meet the needs of engineering applications, its mathematical representation is not complete and the actual operation is cumbersome. The subarray extrapolation method developed on this basis cannot handle the problem of array deformation. It can be seen that there is an urgent need for an analysis method that is low-cost and guarantees accuracy requirements.

[0004] The infinitesimal dipole model is a method that uses a set of infinitesimal dipoles to equivalently represent the electromagnetic characteristics of a target. The infinitesimal dipole model can be used not only to analyze the radiation performance of an antenna, but also to analyze scattering characteristics. The key lies in the characterization and analysis of the mutual coupling effect between scatterers. Based on the analysis of the radiation array using the infinitesimal dipole model, the researchers established an analysis method for the scattering characteristics of large arrays based on the infinitesimal dipole model. However, the aforementioned study only considered the scattering characteristics in the case of an ideal planar array, but did not consider the scattering characteristics when the array configuration changes under actual working conditions. Therefore, exploring the scattering performance when the array distribution changes based on the infinitesimal dipole model has important research significance for guiding the analysis and design of scattering performance in actual engineering projects. Summary of the invention

[0005] In order to solve the above-mentioned defects existing in the prior art, the purpose of the present invention is to provide a method for analyzing the scattering characteristics of a UAV swarm distributed array antenna, which avoids the scale problem of complex models in traditional grid analysis and improves the analysis efficiency.

[0006] The present invention is achieved through the following technical solutions.

[0007] In one aspect of the present invention, a method for analyzing scattering characteristics of a swarm of UAV distributed array antennas is provided, comprising the following steps:

[0008] According to the geometric parameters of a single UAV, the infinitesimal dipole model parameters are equivalently obtained, the infinitesimal dipole current is obtained, and the initial excitation coefficient of each UAV is calculated;

[0009] According to the actual position vector of each UAV, the initial excitation coefficient of each UAV is corrected to obtain the UAV characteristic weight coefficient;

[0010] The attitude relationship between the ideal state and the configuration change of the UAV array is constructed by translation and rotation, and the mutual coupling coefficient when the configuration change of the UAV array is corrected;

[0011] The mutual coupling matrix between the entire UAV swarm is constructed when the configuration of the UAV array changes, and the excitation coefficient of each UAV in the array is obtained considering the mutual coupling effect;

[0012] Construct and solve the equilibrium equation, calculate the actual excitation coefficient of each UAV in the array environment considering the mutual coupling effect, obtain the array factor of the entire array, calculate the total scattering field of the UAV array, and obtain the radar scattering cross section of the UAV array.

[0013] Preferably, the infinitesimal dipole model parameters are equivalently obtained according to the geometric parameters of a single UAV, including:

[0014] In a drone swarm array consisting of multiple identical single drones, the scattering field of a single drone is numerically approximated with the radiation field of a set of infinitesimal dipole models, and the quantum particle swarm algorithm is used to characterize the scattering characteristics of a single drone as multiple parameters of a set of infinitesimal dipoles;

[0015] The dipole current distribution is obtained according to multiple parameters of the infinitesimal dipole;

[0016] According to the initial position vector of each UAV, the initial excitation coefficient of each UAV is calculated.

[0017] Preferably, the initial excitation coefficient of each UAV is corrected to obtain the UAV characteristic weight coefficient, including:

[0018] According to the actual position vector of each UAV when the configuration of the UAV array changes, the initial excitation coefficient of each UAV is corrected;

[0019] According to the initial excitation coefficient of the UAV when the array configuration changes, the characteristic weight coefficient that characterizes the scattering characteristics of each UAV is obtained.

[0020] Preferably, the mutual coupling matrix between the entire drone swarm is constructed when the configuration of the drone array changes, and the excitation coefficient of each drone in the array considering the mutual coupling effect is obtained, including:

[0021] According to the equivalent infinitesimal dipole parameters, the mutual coupling coefficient is used to characterize the mutual coupling effect between any two UAVs. Combining the relationship between the position vector translation and the complex dipole moment rotation, the mutual coupling coefficient when the configuration of the UAV array changes is obtained.

[0022] According to the corrected mutual coupling coefficient, the mutual coupling matrix of the entire UAV array is constructed to obtain the actual excitation coefficient of each UAV considering the mutual coupling effect of the entire array.

[0023] Preferably, calculating the radar cross section of the drone array includes:

[0024] Construct the equilibrium equation considering the mutual coupling effect between UAV arrays;

[0025] Solve the equilibrium equation to obtain the array excitation coefficient of each UAV considering the mutual coupling effect in the array environment;

[0026] Based on the superposition theorem, the total scattering field of the UAV array is calculated, and the radar scattering cross section is calculated.

[0027] Another aspect of the present invention provides a scattering characteristic analysis device for a swarm of UAV distributed array antennas according to the method, comprising:

[0028] An acquisition module is used to obtain infinitesimal dipole model parameters based on the geometric parameters of a single UAV, obtain infinitesimal dipole currents, and calculate the initial excitation coefficients of each UAV;

[0029] A correction module is used to correct the initial excitation coefficient of each UAV according to the actual position vector of each UAV to obtain the UAV characteristic weight coefficient;

[0030] The mutual coupling coefficient calculation module is used to construct the attitude relationship between the ideal state and the configuration change of the drone array through translation and rotation, and correct the mutual coupling coefficient when the configuration change of the drone array;

[0031] The excitation coefficient calculation module is used to construct the mutual coupling matrix between the entire drone swarm when the drone array configuration changes, and obtain the excitation coefficient of each drone in the array considering the mutual coupling effect;

[0032] The scattering cross section calculation module is used to construct and solve the equilibrium equation, calculate the actual excitation coefficient of each UAV in the array environment considering the mutual coupling effect, obtain the array factor of the entire array, calculate the total scattering field of the UAV array, and obtain the radar scattering cross section of the UAV array.

[0033] Another aspect of the present invention provides an electronic device, including a processor and a memory;

[0034] The memory is used to store a computer program, wherein the computer program includes program instructions;

[0035] The processor is used to call the program stored in the memory to execute the scattering characteristics analysis method of the UAV swarm distributed array antenna.

[0036] The present invention adopts the above technical solution, which has the following beneficial effects:

[0037] The present invention first uses a group of infinitesimal dipoles to replace the drone units, and then refers to the idea of ​​analyzing the scattering characteristics of ideal planar arrays based on infinitesimal dipoles to realize the scattering characteristics analysis of distributed drone arrays. First, the initial excitation coefficient and characteristic weight coefficient of each drone when the drone array configuration changes are corrected, and the mutual coupling coefficient between drone swarms is corrected by translation and rotation. Finally, the array excitation coefficient of each unit of the drone array is obtained to realize the scattering characteristics analysis when the drone array configuration changes.

[0038] 1. The method of the present invention corrects the initial excitation coefficient of the configuration change of the drone array by translating and rotating the equivalent infinitesimal dipole, obtains the characteristic weight coefficient of the drone, and establishes the coupling relationship between a single drone and the entire distributed drone array. Finally, based on the superposition theorem, the radar scattering cross section of the entire drone swarm array is obtained, which is of great significance in practical engineering.

[0039] (2) Compared with the traditional array scattering characteristic analysis method, the method of the present invention avoids the scale problem of complex models in traditional grid analysis and improves the analysis efficiency because the entire drone is equivalent to an infinitesimal dipole model. At the same time, this method can also be used to analyze other arrays with similar unit characteristics. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] The drawings described herein are used to provide a further understanding of the present invention, constitute a part of the present application, and do not constitute an improper limitation of the present invention. In the drawings:

[0041] Figure 1 It is a flow chart of the scattering characteristics analysis method of the UAV swarm distributed array antenna of the present invention;

[0042] Figure 2It is a schematic diagram of the changes in the configuration mode of the drone array;

[0043] Figure 3 It is a schematic diagram of the change of the attitude and position of the drone unit;

[0044] Figure 4 This is a schematic diagram of the mutual coupling of the UAV array environment;

[0045] Figure 5 It is a schematic diagram of the structure of the drone unit;

[0046] Figure 6 It is a schematic diagram of the configuration changes of the drone array;

[0047] Figure 7 It is a comparison between the H-plane bistatic radar cross section (BiRCS) of a UAV array using the present invention and the method of moments;

[0048] Figure 8 It is a comparison between the UAV array E-plane BiRCS using the present invention and the moment method;

[0049] Fig. 9 It is a schematic diagram of a scattering characteristic analysis device for a drone swarm distributed array antenna shown in an embodiment of the present invention;

[0050] Fig.10 It is a schematic diagram of the structure of an electronic device shown in an embodiment of the present invention. DETAILED DESCRIPTION

[0051] The present invention will be described in detail below in conjunction with the accompanying drawings and specific embodiments. The exemplary embodiments and descriptions of the present invention are used to explain the present invention but are not intended to limit the present invention.

[0052] The present invention provides a method for analyzing the scattering characteristics of a drone swarm distributed array antenna. The analysis process is as follows: Figure 1 As shown, the specific steps are as follows:

[0053] Step 1: Obtain the infinitesimal dipole model parameters based on the geometric parameters of a single UAV, calculate the infinitesimal dipole current distribution, and calculate the initial excitation coefficient of the UAV based on the initial position vector of the UAV.

[0054] (1a) A drone swarm array usually consists of multiple identical drones. The scattering field of a single drone is numerically approximated with the radiation field of a set of infinitesimal dipole models. The quantum particle swarm algorithm is used to further characterize the scattering characteristics of a single drone as seven parameters of a set of infinitesimal dipoles:

[0055]

[0056] Among them, χ iare the seven parameters that characterize the i-th infinitesimal dipole, M i is the dipole moment amplitude, is the dipole phase, α i is the angle between the infinitesimal dipole and the coordinate axis z, β i is the angle between the projection of the infinitesimal dipole on the xoy plane and the coordinate axis x; i ,y i ,z i is the position coordinate of the dipole in the rectangular coordinate system.

[0057] After obtaining the seven parameters of the infinitesimal dipole, the dipole current distribution is obtained.

[0058]

[0059] in, is the current distribution of the infinitesimal dipole, N d is the number of infinitesimal dipoles, γ is a unit complex number, is the complex dipole moment of the i-th infinitesimal dipole, is the initial position vector of the UAV, is the initial position vector of the i-th infinitesimal dipole.

[0060] (1b) First, according to the initial position vector of each UAV, the initial excitation coefficient of each UAV is calculated as

[0061]

[0062] Among them, V is the initial excitation coefficient of the UAV, is the initial excitation electric field of the UAV.

[0063] The initial excitation electric field of the UAV can be further written as

[0064]

[0065] Where E is the plane wave excitation intensity, is the polarization direction unit vector, γ is a unit complex number, k is the free space wave number, is the unit vector of the incident direction of the plane wave, is the drone position vector.

[0066] Step 2: According to the actual position vector of each UAV when the configuration of the UAV array changes, the initial excitation coefficient of each UAV is corrected to obtain the UAV characteristic weight coefficient.

[0067] For the entire UAV array structure, actual working conditions will cause each UAV to deviate from its initial position. Figure 2Take the UAV array as an example. During the flight, wind load or vibration will cause the configuration of the entire UAV array to change. Figure 3 As shown, for each UAV, the change in array configuration will cause position shift and attitude deflection of each UAV.

[0068] (2a) According to the actual position vector of each UAV when the configuration of the UAV array changes, the initial excitation coefficient of each UAV is corrected.

[0069] Since the configuration of the drone array changes at this time, from the perspective of a single drone, the drone has positional displacement and attitude deflection, which causes the infinitesimal dipole current distribution to change. At this time, the initial excitation coefficient of each drone is

[0070]

[0071] Among them, V′ is the corrected initial excitation coefficient of the UAV, Dipole current distribution when the UAV deflects, r′ is the position vector when the UAV array configuration changes, is the position vector of each infinitesimal dipole when the UAV is offset.

[0072] Then, the relationship between the current distribution when the UAV is deflected and the current distribution when there is no attitude deflection in the initial state can be established based on the Euler rotation matrix.

[0073]

[0074] Among them, T z , T y , T x They are the rotation matrices along the z, y, and x axes respectively.

[0075] The rotation matrix along the three rectangular coordinate axes can be expressed as

[0076]

[0077]

[0078] Among them, A, B, and C are the rotation angles along the three rectangular coordinate axes respectively.

[0079] (2b) According to the initial excitation coefficient of the UAV when the array configuration changes, the characteristic weight coefficient characterizing the scattering characteristics of each UAV is obtained.

[0080] At this time, the UAV characteristic weight coefficient when the array configuration changes is:

[0081]

[0082] in, is the unit scattered field calculated based on the equivalent infinitesimal dipole, This is the unit scattered field calculated by the software.

[0083] Step 3, use the mutual coupling coefficient to characterize the mutual coupling effect between any two UAVs, establish the attitude relationship between the UAV array in the ideal state and when the configuration changes through translation and rotation, so as to obtain the mutual coupling coefficient of the UAV array when the configuration changes, and then construct the mutual coupling matrix between the entire UAV swarm when the UAV array configuration changes, and obtain the excitation coefficient of each UAV in the array considering the mutual coupling effect.

[0084] Specifically:

[0085] (3a) According to the equivalent infinitesimal dipole parameters obtained in step (1), the mutual coupling coefficient is used to characterize the mutual coupling effect between any two UAVs. Combining the relationship between the position vector translation and the complex dipole moment rotation, based on the electromagnetic reaction theorem, the mutual coupling coefficient when the UAV array configuration changes is obtained.

[0086] After obtaining the corrected initial excitation coefficient, the mutual coupling effect between the UAV array is considered. The mutual coupling effect between any two UAVs m and n can be characterized based on the reaction theorem:

[0087]

[0088] Among them, C mn is the mutual coupling coefficient between the two UAV array elements m and n, ω is the free space angular frequency, and μ is the magnetic permeability. is the free space dyadic Green's function, is the position vector of the i-th dipole of array element m, is the position vector of the jth dipole of array element n. is the complex dipole moment of the jth dipole of element n, is the complex dipole moment of the ith dipole of element m.

[0089] like Figure 3 As shown in the figure, when the configuration of the drone array changes, the relative position and posture between any two drones will change. We decompose the configuration change of the drone array into the translation and rotation of the drones, and construct the position change relationship between the configuration change of the drone array and the ideal state according to the position offset vector.

[0090]

[0091] in, It is the position offset vector when the unmanned vehicle configuration changes.

[0092] The relationship between the dipole moment change when the configuration of the drone array changes and the ideal state is constructed based on the Euler rotation matrix

[0093]

[0094] in is the complex dipole moment after rotation.

[0095] The corrected mutual coupling coefficient is

[0096]

[0097] Among them, C′ mn is the corrected mutual coupling coefficient, which characterizes the mutual coupling effect between UAV m and UAV n when the configuration of the UAV array changes. γ is a unit complex number, ω is the angular frequency of free space, μ is the magnetic permeability, is the dyadic Green's function when the configuration of the UAV array changes, is the complex dipole moment of the jth dipole of element n when the array configuration changes, is the complex dipole moment of the i-th dipole of element m when the array configuration changes.

[0098] Based on the mutual coupling coefficient between any two UAVs, a mutual coupling matrix is ​​constructed to characterize the mutual coupling effect of the entire UAV swarm. Figure 4 As shown in the figure, each UAV is affected by the scattered fields of other UAVs around it in addition to its own initial excitation.

[0099] (3b) Based on the corrected mutual coupling coefficient, the mutual coupling matrix of the entire UAV array is constructed to obtain the excitation coefficient of each UAV array considering the mutual coupling effect of the entire array.

[0100] Assuming that the total number of array elements of the UAV array is M, the total scattered electric field on UAV m is

[0101]

[0102] in, is the total scattered electric field of UAV m, is the initial incident electric field of UAV m, is the scattered electric field of UAV m from other UAVs in the entire array.

[0103] The array excitation coefficient of UAV m in the array environment is

[0104]

[0105] Among them, V m ′ is the array excitation coefficient of UAV m in the array environment, Fig. 2 is the current distribution of UAV m when the array configuration changes.

[0106] Simultaneous scattering of electric field Can be characterized as

[0107]

[0108] Among them, V n ′ is the initial excitation coefficient of UAV n, β n ′ is the characteristic weight coefficient of UAV n, is the electric field of UAV n.

[0109] Combining formulas (16) to (18), we can obtain the array excitation coefficient considering the mutual coupling effect of the entire array:

[0110]

[0111] Among them, V m ′ is the actual excitation coefficient of UAV m, is the initial excitation coefficient of UAV m.

[0112]

[0113] in is the current distribution of UAV m.

[0114] Step 4: Construct and solve the equilibrium equation, calculate the actual excitation coefficient of each UAV in the array environment considering the mutual coupling effect, obtain the array factor of the entire array, calculate the total scattering field of the UAV array, and calculate the radar scattering cross section of the UAV array.

[0115] Specifically:

[0116] (4a) Construct the equilibrium equation considering the mutual coupling effect between UAV arrays.

[0117] According to the actual excitation coefficient represented by formula (19), the actual excitation array composed of the actual excitation coefficient of the entire UAV array is constructed, that is, the balance equation considering the mutual coupling effect between the UAV arrays is:

[0118]

[0119] in, is the actual excitation array of the entire UAV array composed of actual excitation coefficients, is the initial excitation matrix of the entire UAV array composed of the initial excitation coefficients, C is the mutual coupling matrix, the elements of which are composed of the mutual coupling coefficients between any two UAVs, and K is the matrix composed of the characteristic weight coefficients of each UAV.

[0120]

[0121] Where V1′ is the actual excitation coefficient of the first UAV array element, and so on. The superscript T represents the transposition operation.

[0122]

[0123] Among them, V1 0 is the initial excitation coefficient of the first UAV array element, and so on.

[0124]

[0125] Among them, the elements in the matrix represent the coupling coefficients of any two drones in the entire drone array.

[0126]

[0127] Among them, β1′ is the characteristic weight coefficient of the first UAV array element, and so on.

[0128] (4b) Solve the equilibrium equation to obtain the actual excitation coefficient of each UAV in the array environment considering the mutual coupling effect, obtain the array factor of the entire array, calculate the total scattering field of the UAV array, and calculate the radar scattering cross section of the UAV array.

[0129] Solve the balance equation of formula (20) to obtain the actual excitation coefficient of each UAV in the array environment:

[0130]

[0131] Where U is the identity matrix and the superscript -1 indicates the matrix inversion operation.

[0132] After obtaining the actual excitation of each UAV, the array factor of the entire UAV array can be represented as

[0133]

[0134] Where P is the array factor of the UAV array.

[0135] Therefore, the total scattered field of the entire drone swarm array can be calculated based on the superposition theorem

[0136]

[0137] in, is the total scattering field of the entire UAV array, and F is the array composed of the scattering fields of each UAV array.

[0138]

[0139] in is the scattered field of a single UAV, is a space unit vector.

[0140] According to the total scattering field of the entire UAV array, the radar scattering cross section of the UAV array is:

[0141]

[0142] Where σ is the radar cross section, R is the far field distance, and E s is the scattered field of the entire array, E inc is the initial incident field of the entire array.

[0143] Taking the drone array as an example, the following simulation case is used to further illustrate.

[0144] 1. Simulation parameters

[0145] like Figure 5 The following is a simplified schematic diagram of the UAV structure and structural parameters. Figure 6 The figure shows a simulation model of a 7*7 saddle array composed of UAV units arranged in a square. The deformation displacement in the z direction is The maximum deformation in the z direction is 0.5m, and the maximum deflection angle is 30°. The spacing of the drone array is 0.5m, the plane wave excitation amplitude is 1V / m, and the excitation azimuth is θ=0°. The calculation frequency is 1 GHz.

[0146] 2. Simulation content and results

[0147] Figure 7 It is a comparison between the H-plane bistatic radar cross section (RCS) of the UAV array using the present invention and the method of moments;

[0148] Figure 8 It is a comparison between the E-plane dual-station RCS of the UAV array using the present invention and the moment method;

[0149] from Figures 7-8 It can be seen that the scattering characteristics analysis method of the UAV swarm distributed array antenna of the present invention can accurately analyze the scattering field of the UAV array, which is basically consistent with the analysis result of the moment method, verifying the effectiveness of the method of the present invention.

[0150] like Fig. 9 As shown, the present invention provides a UAV swarm distributed array antenna scattering characteristics analysis device 100 of the method, comprising:

[0151] The acquisition module 110 is used to obtain infinitesimal dipole model parameters based on the geometric parameters of a single UAV, obtain infinitesimal dipole current, and calculate the initial excitation coefficient of each UAV;

[0152] The correction module 120 is used to correct the initial excitation coefficient of each drone according to the actual position vector of each drone to obtain the drone characteristic weight coefficient;

[0153] The mutual coupling coefficient calculation module 130 is used to construct the attitude relationship between the ideal state and the configuration change of the drone array through translation and rotation, and correct the mutual coupling coefficient when the configuration change of the drone array;

[0154] The excitation coefficient calculation module 140 is used to construct the mutual coupling matrix between the entire drone swarm when the drone array configuration changes, and obtain the excitation coefficient of each drone in the array considering the mutual coupling effect;

[0155] The scattering cross section calculation module 150 is used to construct and solve the equilibrium equation, calculate the actual excitation coefficient of each drone in the array environment considering the mutual coupling effect, obtain the array factor of the entire array, calculate the total scattering field of the drone array, and obtain the radar scattering cross section of the drone array.

[0156] like Fig.10 As shown, the present invention provides an electronic device 200 for implementing a method for analyzing scattering characteristics of a swarm of unmanned aerial vehicles (UAVs) distributed array antennas, comprising: an acquisition card 210 , a memory 220 , a communication bus 230 and a processor 240 .

[0157] The computer device includes a processor 240 and a memory 220, wherein the memory 220 is used to store a computer program, wherein the computer program includes program instructions, and the processor 240 is used to execute the program instructions stored in the computer storage medium. The processor may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components, etc. It is the computing core and control core of the terminal, which is suitable for implementing one or more instructions, and is specifically suitable for loading and executing one or more instructions to implement the corresponding method flow or corresponding function; the processor described in the embodiment of the present invention can be used to implement the operation of a method for analyzing the scattering characteristics of a swarm of unmanned aerial vehicles distributed array antennas.

[0158] In one embodiment of the present invention, a method for analyzing scattering characteristics of a swarm of unmanned aerial vehicles distributed array antennas can be stored in a computer-readable storage medium if it is implemented in the form of a software functional unit and sold or used as an independent product. Based on this understanding, the present invention implements all or part of the process in the above-mentioned embodiment method, and can also be completed by instructing the relevant hardware through a computer program. The computer program can be stored in a computer-readable storage medium, and the computer program can implement the steps of the above-mentioned method embodiments when executed by the processor. Among them, the computer program includes computer program code, and the computer program code can be in source code form, object code form, executable file or some intermediate form. Computer-readable storage media include permanent and non-permanent, removable and non-removable media, and information storage can be implemented by any method or technology. Information can be computer-readable instructions, data structures, program modules or other data.

[0159] Computer storage media can be any available media or data storage devices that can be accessed by a computer, including but not limited to magnetic storage (such as floppy disks, hard disks, magnetic tapes, magneto-optical disks (MO), etc.), optical storage (such as CD, DVD, BD, HVD, etc.), and semiconductor storage (such as ROM, EPROM, EEPROM, non-volatile memory (NANDFLASH), solid-state drives (SSD)), etc.

[0160] The present invention is not limited to the above-mentioned embodiments. On the basis of the technical solution disclosed in the present invention, technicians in this field can make some substitutions and deformations to some technical features therein according to the disclosed technical content without creative labor, and these substitutions and deformations are all within the protection scope of the present invention.

Claims

1. A method for analyzing scattering characteristics of UAV swarm distributed array antennas, characterized in that: The steps include: According to the geometric parameters of a single UAV, the infinitesimal dipole model parameters are equivalently obtained, the infinitesimal dipole current is obtained, and the initial excitation coefficient of each UAV is calculated; According to the actual position vector of each UAV, the initial excitation coefficient of each UAV is corrected to obtain the UAV characteristic weight coefficient; The attitude relationship between the ideal state and the configuration change of the UAV array is constructed by translation and rotation, and the mutual coupling coefficient when the configuration change of the UAV array is corrected; The mutual coupling matrix between the entire UAV swarm is constructed when the configuration of the UAV array changes, and the excitation coefficient of each UAV in the array is obtained considering the mutual coupling effect; Construct and solve the equilibrium equation, calculate the actual excitation coefficient of each UAV in the array environment considering the mutual coupling effect, obtain the array factor of the entire array, calculate the total scattering field of the UAV array, and obtain the radar scattering cross section of the UAV array.

2. The method for analyzing scattering characteristics of UAV swarm distributed array antennas according to claim 1 is characterized in that: According to the geometric parameters of a single UAV, the infinitesimal dipole model parameters are equivalent, including: In a drone swarm array consisting of multiple identical single drones, the scattering field of a single drone is numerically approximated with the radiation field of a set of infinitesimal dipole models, and the quantum particle swarm algorithm is used to characterize the scattering characteristics of a single drone as multiple parameters of a set of infinitesimal dipoles. The dipole current distribution is obtained according to multiple parameters of the infinitesimal dipole; According to the initial position vector of each UAV, the initial excitation coefficient of each UAV is calculated.

3. The method for analyzing scattering characteristics of UAV swarm distributed array antennas according to claim 2 is characterized in that: The initial excitation coefficient of the drone is: Among them, V′ is the initial excitation coefficient when the UAV has position deviation and attitude deflection, is the dipole current distribution when the UAV deflects its attitude. is the initial plane wave excitation of the UAV, N d is the number of infinitesimal dipoles, is the position vector of the i-th infinitesimal dipole, T x 、T y 、T z are the Euler rotation matrices in the rectangular coordinate system, This is the initial dipole current distribution when the UAV does not deflect its attitude.

4. The method for analyzing scattering characteristics of UAV swarm distributed array antennas according to claim 1, characterized in that: Correct the initial excitation coefficient of each UAV to obtain the UAV characteristic weight coefficient, including: According to the actual position vector of each UAV when the configuration of the UAV array changes, the initial excitation coefficient of each UAV is corrected; According to the initial excitation coefficient of the UAV when the array configuration changes, the characteristic weight coefficient that characterizes the scattering characteristics of each UAV is obtained.

5. The method for analyzing scattering characteristics of UAV swarm distributed array antennas according to claim 4 is characterized in that: Correct the initial incentive coefficient of each drone to: Among them, V′ is the corrected initial excitation coefficient of the UAV, Dipole current distribution when the UAV deflects, r′ is the position vector when the UAV array configuration changes, is the position vector of each infinitesimal dipole when the UAV is offset, is the initial plane wave excitation for the UAV; The characteristic weight coefficient β′ of each UAV scattering characteristic is: Among them, V′ is the initial excitation coefficient when the UAV has position deviation and attitude deflection, is the unit scattered field calculated based on the equivalent infinitesimal dipole, This is the unit scattered field calculated by the software.

6. The method for analyzing scattering characteristics of UAV swarm distributed array antennas according to claim 1, characterized in that: The mutual coupling matrix between the entire drone swarm when the drone array configuration changes is constructed, and the excitation coefficient of each drone in the array considering the mutual coupling effect is obtained, including: According to the equivalent infinitesimal dipole parameters, the mutual coupling coefficient is used to characterize the mutual coupling effect between any two UAVs. Combining the relationship between the position vector translation and the complex dipole moment rotation, the mutual coupling coefficient when the configuration of the UAV array changes is obtained. According to the corrected mutual coupling coefficient, the mutual coupling matrix of the entire UAV array is constructed to obtain the actual excitation coefficient of each UAV considering the mutual coupling effect of the entire array.

7. The method for analyzing scattering characteristics of UAV swarm distributed array antennas according to claim 6, characterized in that: The mutual coupling coefficient when the configuration of the UAV array changes is: Among them, C′ mn Characterizes the mutual coupling effect between drone m and drone n when the drone array configuration changes, γ is a unit complex number, ω is the free space angular frequency, μ is the magnetic permeability, N d is the number of infinitesimal dipoles, is the dyadic Green's function when the configuration of the UAV array changes, is the complex dipole moment of the jth dipole of element n when the array configuration changes, is the complex dipole moment of the i-th dipole of element m when the array configuration changes; The actual excitation coefficient of each UAV considering the mutual coupling effect of the entire array is: Among them, V m ′ is the actual excitation coefficient of UAV m, V n ′ is the initial excitation coefficient of UAV n, is the initial excitation coefficient of UAV m, C′ mn is the corrected mutual coupling coefficient, β′ is the characteristic weight coefficient of UAV n, and M is the total number of array elements in the UAV array.

8. The method for analyzing scattering characteristics of UAV swarm distributed array antennas according to claim 1, characterized in that: Calculate radar cross section for drone arrays, including: The equilibrium equation considering the mutual coupling effect between UAV arrays is constructed as follows: in, is the actual excitation array of the entire UAV array composed of actual excitation coefficients, is the initial excitation array of the entire UAV array composed of initial excitation coefficients, C is the mutual coupling matrix, and K is the matrix composed of the characteristic weight coefficients of each UAV; Solve the balance equation to obtain the array excitation coefficient of each UAV considering the mutual coupling effect in the array environment: Where U is the unit matrix; Based on the superposition theorem, the total scattering field of the drone array is calculated, and the radar scattering cross section is calculated: Where σ is the radar cross section, R is the far field distance, and E s is the scattered field of the entire array, E inc is the initial incident field of the entire array.

9. A device for analyzing scattering characteristics of UAV swarm distributed array antennas according to any one of claims 1 to 8, characterized in that: include: An acquisition module is used to obtain infinitesimal dipole model parameters based on the geometric parameters of a single UAV, obtain infinitesimal dipole currents, and calculate the initial excitation coefficients of each UAV; A correction module is used to correct the initial excitation coefficient of each UAV according to the actual position vector of each UAV to obtain the UAV characteristic weight coefficient; The mutual coupling coefficient calculation module is used to construct the attitude relationship between the ideal state and the configuration change of the drone array through translation and rotation, and correct the mutual coupling coefficient when the configuration change of the drone array; The excitation coefficient calculation module is used to construct the mutual coupling matrix between the entire drone swarm when the drone array configuration changes, and obtain the excitation coefficient of each drone in the array considering the mutual coupling effect; The scattering cross section calculation module is used to construct and solve the equilibrium equation, calculate the actual excitation coefficient of each UAV in the array environment considering the mutual coupling effect, obtain the array factor of the entire array, calculate the total scattering field of the UAV array, and obtain the radar scattering cross section of the UAV array.

10. An electronic device, characterized in that: including a processor and a memory; The memory is used to store a computer program, wherein the computer program includes program instructions; The processor is used to call the program stored in the memory to execute the method according to any one of claims 1 to 8.

Images